Extraction report — Porter et al. 2025

Paper

paper_id	porteretalndpuzzleaboutknowledge
short_label	Porter et al. 2025
citation	Porter, B., Barr, K., Bencherifa, A., et al. (2025). A puzzle about knowledge ascriptions. Noûs.
doi	10.1111/nous.12515
year	2025
published	Yes
language	English
language_other	—
research_objective	Test cross-culturally whether stakes (high vs low) affect (a) knowledge ascriptions in an evidence-fixed prompt and (b) evidence requirements for knowledge in an evidence-seeking prompt, and interpret any divergence between the prompts as reflecting a tension between epistemic beliefs and epistemic practices.
data_available_online	Yes
data_url	https://osf.io/tyge9/files/osfstorage
notes	—

China (Mandarin)

study_id: 1

Study

study_id	1
label	China (Mandarin)
objective	Test in the China (Mandarin) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	261
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 22.75 (sd 5.53, range 18–52); Gender % M/F/other: 43.9/55.8/0.3; Total N=416; Passed comprehension check N=261 (62.7%).
mean_age	22.75

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

China: N=416; Passed Check=261 (62.7%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s1_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.058054932688 · v=0.009447700861

Effect

effect_id	s1_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.058054932688
v	0.009447700861
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-0.597
df1	—
df2	—
p	0.5504
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.1053; Std. Error=0.1763; Odds Ratio=0.900064.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

China: -0.1053 0.1763 -0.597 0.5504 0.900064

Quality Flags

—

s1_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s1_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	2.278
df1	—
df2	—
p	0.0227
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=182; Estimate=0.03758; Std. Error=0.09836.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

China 182 0.03758 0.09836 2.278 0.0227

Quality Flags

—

Russia (Russian)

study_id: 2

Study

study_id	2
label	Russia (Russian)
objective	Test in the Russia (Russian) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	558
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: non-students; Age mean 25.97 (sd 10.28, range 18–75); Gender % M/F/other: 40/60/0; Total N=739; Passed comprehension check N=558 (75.5%).
mean_age	25.97

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Russia: N=739; Passed Check=558 (75.5%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s2_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.068574288013 · v=0.002602475404

Effect

effect_id	s2_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.068574288013
v	0.002602475404
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-1.344
df1	—
df2	—
p	0.179
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.12438; Std. Error=0.09253; Odds Ratio=0.8830474.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Russia: -0.12438 0.09253 -1.344 0.179 0.8830474

Quality Flags

—

s2_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s2_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	24.758
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=530; Estimate=0.54644; Std. Error=0.02207; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Russia 530 0.54644 0.02207 24.758 < 2e-16

Quality Flags

—

Slovakia (Slovak)

study_id: 3

Study

study_id	3
label	Slovakia (Slovak)
objective	Test in the Slovakia (Slovak) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	290
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 26.28 (sd 9.07, range 18–74); Gender % M/F/other: 54.4/44.9/0.7; Total N=713; Passed comprehension check N=290 (40.7%).
mean_age	26.28

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Slovakia: N=713; Passed Check=290 (40.7%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s3_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.293141573696 · v=0.005494689077

Effect

effect_id	s3_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.293141573696
v	0.005494689077
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-3.955
df1	—
df2	—
p	7.67e-05
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.53170; Std. Error=0.13445; Odds Ratio=0.5876024.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Slovakia: -0.53170 0.13445 -3.955 7.67e-05 0.5876024

Quality Flags

—

s3_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s3_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	19.35
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=243; Estimate=0.68343; Std. Error=0.03532; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Slovakia 243 0.68343 0.03532 19.350 < 2e-16

Quality Flags

—

Ecuador (Spanish)

study_id: 4

Study

study_id	4
label	Ecuador (Spanish)
objective	Test in the Ecuador (Spanish) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	208
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: students; Age mean 21.39 (sd 3.21, range 18–42); Gender % M/F/other: 32.9/66.7/0.5; Total N=390; Passed comprehension check N=208 (53.3%).
mean_age	21.39

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Ecuador: N=390; Passed Check=208 (53.3%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s4_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-0.043373044203 · v=0.007490488797

Effect

effect_id	s4_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-0.043373044203
v	0.007490488797
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	0.501
df1	—
df2	—
p	0.6163
reported_d	—
reported_r	—
notes	Table 4: Estimate=0.07867; Std. Error=0.15698; Odds Ratio=1.0818479.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Ecuador - Spanish: 0.07867 0.15698 0.501 0.6163 1.0818479

Quality Flags

—

s4_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s4_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	12.97
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=172; Estimate=0.50301; Std. Error=0.03878; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Ecuador - Spanish 172 0.50301 0.03878 12.970 < 2e-16

Quality Flags

—

India (Hindi)

study_id: 5

Study

study_id	5
label	India (Hindi)
objective	Test in the India (Hindi) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	100
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 29.98 (sd 10.23, range 18–62); Gender % M/F/other: 45.3/53.8/0.9; Total N=200; Passed comprehension check N=100 (50%).
mean_age	29.98

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

India (Hindi): N=200; Passed Check=100 (50%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s5_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.075476925783 · v=0.01842458042

Effect

effect_id	s5_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.075476925783
v	0.01842458042
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-0.556
df1	—
df2	—
p	0.578
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.1369; Std. Error=0.2462; Odds Ratio=0.8720179.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

India - Hindi: -0.1369 0.2462 -0.556 0.578 0.8720179

Quality Flags

—

s5_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s5_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	5.459
df1	—
df2	—
p	4.79e-08
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=84; Estimate=0.37698; Std. Error=0.06906.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

India - Hindi 84 0.37698 0.06906 5.459 4.79e-08

Quality Flags

—

India (Meitei)

study_id: 6

Study

study_id	6
label	India (Meitei)
objective	Test in the India (Meitei) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	42
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: non-students; Age mean 23.26 (sd 6.26, range 18–45); Gender % M/F/other: 47.6/50/2.4; Total N=86; Passed comprehension check N=42 (48.8%).
mean_age	23.26

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

India (Meitei): N=86; Passed Check=42 (48.8%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s6_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-0.233542920101 · v=0.170068822598

Effect

effect_id	s6_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-0.233542920101
v	0.170068822598
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	0.566
df1	—
df2	—
p	0.571
reported_d	—
reported_r	—
notes	Table 4: Estimate=0.4236; Std. Error=0.7480; Odds Ratio=1.5275252.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

India - Meitei: 0.4236 0.7480 0.566 0.571 1.5275252

Quality Flags

—

s6_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s6_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	1.318
df1	—
df2	—
p	0.187
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=37; Estimate=0.216273; Std. Error=0.164037.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

India - Meitei 37 0.216273 0.164037 1.318 0.187

Quality Flags

—

Japan (Japanese)

study_id: 7

Study

study_id	7
label	Japan (Japanese)
objective	Test in the Japan (Japanese) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	445
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 30.31 (sd 10.76, range 19–62); Gender % M/F/other: 53.3/46.3/0.4; Total N=544; Passed comprehension check N=445 (81.8%).
mean_age	30.31

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Japan: N=544; Passed Check=445 (81.8%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s7_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.165949997522 · v=0.00461887598

Effect

effect_id	s7_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.165949997522
v	0.00461887598
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-2.442
df1	—
df2	—
p	0.0146
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.30100; Std. Error=0.12327; Odds Ratio=0.7400757.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Japan: -0.30100 0.12327 -2.442 0.0146 0.7400757

Quality Flags

—

s7_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s7_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	20.386
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=380; Estimate=0.389493; Std. Error=0.019106; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Japan 380 0.389493 0.019106 20.386 < 2e-16

Quality Flags

—

Morocco (Arabic)

study_id: 8

Study

study_id	8
label	Morocco (Arabic)
objective	Test in the Morocco (Arabic) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	323
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 32.96 (sd 11.81, range 18–76); Gender % M/F/other: 44.4/55.6/0; Total N=551; Passed comprehension check N=323 (58.6%).
mean_age	32.96

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Morocco: N=551; Passed Check=323 (58.6%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s8_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.057889534019 · v=0.005168644854

Effect

effect_id	s8_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.057889534019
v	0.005168644854
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-0.805
df1	—
df2	—
p	0.42072
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.1050; Std. Error=0.1304; Odds Ratio=0.9003190.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Morocco: -0.1050 0.1304 -0.805 0.42072 0.9003190

Quality Flags

—

s8_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s8_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	8.01
df1	—
df2	—
p	1.15e-15
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=301; Estimate=0.30593; Std. Error=0.03819.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Morocco 301 0.30593 0.03819 8.010 1.15e-15

Quality Flags

—

Peru (Shipibo)

study_id: 9

Study

study_id	9
label	Peru (Shipibo)
objective	Test in the Peru (Shipibo) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	102
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: non-students; Age mean 34.68 (sd 13.77, range 18–83); Gender % M/F/other: 53.9/46.1/0; Total N=200; Passed comprehension check N=102 (51%).
mean_age	34.68

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Peru (Shipibo): N=200; Passed Check=102 (51%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s9_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-2.841549127004 · v=59467.93811950743

Effect

effect_id	s9_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-2.841549127004
v	59467.93811950743
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low). Note: Std. Error is extremely large (442.314), yielding a very large variance (effect effectively uninformative). See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	0.012
df1	—
df2	—
p	0.991
reported_d	—
reported_r	—
notes	Table 4: Estimate=5.154; Std. Error=442.314; Odds Ratio=173.18192856.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Peru - Shipibo: 5.154 442.314 0.012 0.991 173.18192856

Quality Flags

—

s9_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s9_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Per Table 7 footnote, stakes effect could not be tested for Peru-Shipibo.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD: Table 7 reports no stakes-effect estimate for Peru-Shipibo (insufficient data; see Table 7 footnote).

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports NA for this sample (insufficient data to test stakes effect).

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	—
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7 reports N=3 and NA for Estimate/SE/z/p; footnote: all coded responses were from the high-stakes condition.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Peru - Shipibo 3 NA NA NA NA

Quality Flags

—

Peru (Spanish)

study_id: 10

Study

study_id	10
label	Peru (Spanish)
objective	Test in the Peru (Spanish) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	216
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: students; Age mean 22.75 (sd 3.28, range 18–49); Gender % M/F/other: 43.1/56.9/0; Total N=286; Passed comprehension check N=216 (75.5%).
mean_age	22.75

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

Peru (Spanish): N=286; Passed Check=216 (75.5%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s10_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.053704947703 · v=0.007998900664

Effect

effect_id	s10_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.053704947703
v	0.007998900664
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-0.6
df1	—
df2	—
p	0.548
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.09741; Std. Error=0.16222; Odds Ratio=0.9071871.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

Peru - Spanish: -0.09741 0.16222 -0.600 0.548 0.9071871

Quality Flags

—

s10_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s10_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	2.549
df1	—
df2	—
p	0.0108
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=126; Estimate=0.11756; Std. Error=0.04612.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

Peru - Spanish 126 0.11756 0.04612 2.549 0.01080

Quality Flags

—

South Africa (Afrikaans)

study_id: 11

Study

study_id	11
label	South Africa (Afrikaans)
objective	Test in the South Africa (Afrikaans) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	178
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 41.63 (sd 12.85, range 18–73); Gender % M/F/other: 34.3/65.7/0; Total N=270; Passed comprehension check N=178 (65.9%).
mean_age	41.63

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

South Africa (Afrikaans): N=270; Passed Check=178 (65.9%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s11_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.041685977783 · v=0.009335499556

Effect

effect_id	s11_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.041685977783
v	0.009335499556
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-0.431
df1	—
df2	—
p	0.666
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.07561; Std. Error=0.17525; Odds Ratio=0.9271746.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

South Africa - Afrikaans: -0.07561 0.17525 -0.431 0.666 0.9271746

Quality Flags

—

s11_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s11_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-1.313
df1	—
df2	—
p	0.189
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=132; Estimate=-0.06780; Std. Error=0.05164.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

South Africa - Afrikaans 132 -0.06780 0.05164 -1.313 0.189

Quality Flags

—

South Africa (Sepedi)

study_id: 12

Study

study_id	12
label	South Africa (Sepedi)
objective	Test in the South Africa (Sepedi) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	122
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: non-students; Age mean 29.33 (sd 7.88, range 18–57); Gender % M/F/other: 36.5/62/1.5; Total N=258; Passed comprehension check N=122 (47.3%).
mean_age	29.33

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

South Africa (Sepedi): N=258; Passed Check=122 (47.3%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s12_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-0.240213999735 · v=0.037983969242

Effect

effect_id	s12_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-0.240213999735
v	0.037983969242
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	1.233
df1	—
df2	—
p	0.218
reported_d	—
reported_r	—
notes	Table 4: Estimate=0.4357; Std. Error=0.3535; Odds Ratio=1.5461104.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

South Africa - Sepedi: 0.4357 0.3535 1.233 0.218 1.5461104

Quality Flags

—

s12_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s12_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	1.562
df1	—
df2	—
p	0.118
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=22; Estimate=0.364944; Std. Error=0.233666.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

South Africa - Sepedi 22 0.364944 0.233666 1.562 0.118

Quality Flags

—

South Africa (isiZulu)

study_id: 13

Study

study_id	13
label	South Africa (isiZulu)
objective	Test in the South Africa (isiZulu) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	130
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: non-students; Age mean 31.05 (sd 9.84, range 18–76); Gender % M/F/other: 27.9/69.9/2.2; Total N=268; Passed comprehension check N=130 (48.5%).
mean_age	31.05

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

South Africa (isiZulu): N=268; Passed Check=130 (48.5%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s13_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-0.046063529212 · v=0.047164531159

Effect

effect_id	s13_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-0.046063529212
v	0.047164531159
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	0.212
df1	—
df2	—
p	0.832
reported_d	—
reported_r	—
notes	Table 4: Estimate=0.08355; Std. Error=0.39391; Odds Ratio=1.0871401.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

South Africa - isiZulu: 0.08355 0.39391 0.212 0.832 1.0871401

Quality Flags

—

s13_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s13_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	0.192
df1	—
df2	—
p	0.8474
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=12; Estimate=0.04766; Std. Error=0.24772.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

South Africa - isiZulu 12 0.04766 0.24772 0.192 0.8474

Quality Flags

—

South Korea (Korean)

study_id: 14

Study

study_id	14
label	South Korea (Korean)
objective	Test in the South Korea (Korean) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	193
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: both; Age mean 35.40 (sd 10.37, range 18–68); Gender % M/F/other: 41.5/58.5/0; Total N=256; Passed comprehension check N=193 (75.4%).
mean_age	35.4

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

South Korea: N=256; Passed Check=193 (75.4%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s14_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=-0.159571122202 · v=0.009700160706

Effect

effect_id	s14_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	-0.159571122202
v	0.009700160706
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	1.62
df1	—
df2	—
p	0.105
reported_d	—
reported_r	—
notes	Table 4: Estimate=0.28943; Std. Error=0.17864; Odds Ratio=1.3356652.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

South Korea: 0.28943 0.17864 1.620 0.105 1.3356652

Quality Flags

—

s14_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s14_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	15.893
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=193; Estimate=0.40194; Std. Error=0.02529; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

South Korea 193 0.40194 0.02529 15.893 < 2e-16

Quality Flags

—

United States (English)

study_id: 15

Study

study_id	15
label	United States (English)
objective	Test in the United States (English) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design.
design	Between-Subjects
design_other	2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt.
manipulated_factors	Evidence: weak vs strong
paradigm	Other
paradigm_other	Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded).
notes	—

Sample

n_final	348
recruitment	other
recruitment_other	Convenience sample (students/non-students; see Table 1).
compensation	—
compensation_other	—
characteristics	Students: students; Age mean 35.85 (sd 10.52, range 19–73); Gender % M/F/other: 55.5/44.5/0; Total N=396; Passed comprehension check N=348 (87.9%).
mean_age	35.85

Provenance

page	4
table_ref	tabula_stream_p4_t1.csv
tei_id	—

United States: N=396; Passed Check=348 (87.9%).

Scale

label	other
points	—
anchors	Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks).
direction	Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required.

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Measures

knowledge_question_text	Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)
knowledge_question_first	—
additional_question_text	Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?

Scenarios

Scenarios (1)

dam · Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

scenario_code	dam
scenario_type	Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated.

High stakes text

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

Low stakes text

It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Provenance

page	5
table_ref	—
tei_id	—

High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level.

Effects

s15_e1 · Evidence-fixed (knowledge ascription) · Between-Subjects · d=0.080328620063 · v=0.003840202551

Effect

effect_id	s15_e1
subgroup	Evidence-fixed (knowledge ascription)
subgroup_desc	Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure.
design	Between-Subjects
design_other	Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design.
quality_flags	—
notes	—

Effect Size

metric	SMD
d	0.080328620063
v	0.003840202551
computed_from	other
needs_review	false
notes	Computed from Table 4 (log OR high vs low) using d=-Estimatesqrt(3)/pi and v=(sqrt(3)/pi)^2SE^2. See analysis/effect_sizes.qmd.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	logistic regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	-1.296
df1	—
df2	—
p	0.195
reported_d	—
reported_r	—
notes	Table 4: Estimate=-0.1457; Std. Error=0.1124; Odds Ratio=0.8644485.

Provenance

page	9
table_ref	camelot_stream_p9_t4.csv
tei_id	—

United States: -0.1457 0.1124 -1.296 0.195 0.8644485

Quality Flags

—

s15_e2 · Evidence-seeking (checks required) · Between-Subjects · needs_review

Effect

effect_id	s15_e2
subgroup	Evidence-seeking (checks required)
subgroup_desc	Free response (coded numeric): number of checks required before knowing.
design	Between-Subjects
design_other	Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7).
quality_flags	—
notes	—

Effect Size

metric	SMD
d	—
v	—
computed_from	unknown
needs_review	true
notes	Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes.

Moderators

scenario	other
skeptical_pressure	No
awareness	Yes
evidence	First Person
attribution_person	Other
evidence_reliability	—

Contrast

group_high	high_stakes
group_low	low_stakes
sign_convention	d = mean(low) - mean(high)
other_notes	Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns.

Moderator Coding

moderator value reason evidence

scenario

other

The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case).

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

skeptical_pressure

No

No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only.

Provenance

page	5
table_ref	—
tei_id	—

Once he has finished building the dam, he checks the logs once to make sure the dam is secure.

awareness

Yes

The stakes are stated in the vignette presented to participants/protagonist.

Provenance

page	5
table_ref	—
tei_id	—

It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water.

evidence

First Person

Evidence is the agent’s own checking of the logs (first-person evidence).

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

attribution_person

Other

Participants attribute knowledge to a third person ([name]).

Provenance

page	5
table_ref	—
tei_id	—

Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows.

evidence_reliability

—

Reliability is not explicitly specified/manipulated; coded null.

Provenance

page	5
table_ref	—
tei_id	—

Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure.

Groups

No `groups[]` provided.

Reported Test

test	Poisson regression coefficient (stakes; high vs low)
t	—
f	—
chi2	—
z	15.87
df1	—
df2	—
p	—
reported_d	—
reported_r	—
notes	Table 7: N (coded responses)=327; Estimate=0.41068; Std. Error=0.02588; p < 2e-16.

Provenance

page	13
table_ref	camelot_stream_p13_t7.csv
tei_id	—

United States 327 0.41068 0.02588 15.870 < 2e-16

Quality Flags

—

Raw YAML

schema_version: "1.1"

paper:
  paper_id: porteretalndpuzzleaboutknowledge
  citation: "Porter, B., Barr, K., Bencherifa, A., et al. (2025). A puzzle about knowledge ascriptions. Noûs."
  short_label: "Porter et al. 2025"
  doi: "10.1111/nous.12515"
  published: "Yes"
  year: 2025
  language: "English"
  language_other: null
  research_objective: "Test cross-culturally whether stakes (high vs low) affect (a) knowledge ascriptions in an evidence-fixed prompt and (b) evidence requirements for knowledge in an evidence-seeking prompt, and interpret any divergence between the prompts as reflecting a tension between epistemic beliefs and epistemic practices."
  data_availability:
    data_available_online: "Yes"
    url: "https://osf.io/tyge9/files/osfstorage"
    notes: "Paper states that data and code are available at this OSF location."
  notes: null

studies:
  - study_id: 1
    label: "China (Mandarin)"
    objective: "Test in the China (Mandarin) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 261
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 22.75 (sd 5.53, range 18–52); Gender % M/F/other: 43.9/55.8/0.3; Total N=416; Passed comprehension check N=261 (62.7%)."
      mean_age: 22.75
      mean_age_prov:
        page: 4
        quote: "China: Age mean 22.75 (range 18–52; sd 5.53)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "China: N=416; Passed Check=261 (62.7%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: &scale_common
      label: other
      points: null
      anchors: "Evidence-fixed: binary choice (knows vs only thinks he knows); Evidence-seeking: numeric free response (# checks)."
      direction: "Evidence-fixed: higher probability of selecting 'knows'; Evidence-seeking: higher numbers = more checks required."
      provenance:
        page: 5
        quote: "Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows. Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?"
        tei_id: null
        table_ref: null
    measures: &measures_common
      knowledge_question_text: "Evidence-fixed: [name] ____________ that the dam is secure. (options: knows / only thinks he knows)"
      knowledge_question_first: null
      additional_question_text: "Evidence-seeking: How many times do you think [name] has to check the logs before he knows that the dam is secure?"
    scenarios: &scenarios_common
      - scenario_code: dam
        scenario_type: "Dam-on-river vignette; stakes (high vs low) and evidence (weak vs strong) manipulated."
        high_stakes_text: "It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water."
        low_stakes_text: "It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level."
        provenance:
          page: 5
          quote: "High stakes: It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water. Low stakes: It is not at all important that the dam is secure. Due to the low water level, if it breaks, the water won't even rise to knee level."
          tei_id: null
          table_ref: null
    effects:
      - effect_id: s1_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: &mod_common
          scenario: other
          skeptical_pressure: "No"
          awareness: "Yes"
          evidence: "First Person"
          attribution_person: "Other"
          evidence_reliability: null
        moderators_coding: &mod_coding_common
          scenario:
            provenance:
              page: 5
              quote: "It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water."
              tei_id: null
              table_ref: null
            reason: "The vignette concerns building/checking a dam (not a bank/peanuts/bridge/typos case)."
          skeptical_pressure:
            provenance:
              page: 5
              quote: "Once he has finished building the dam, he checks the logs once to make sure the dam is secure."
              tei_id: null
              table_ref: null
            reason: "No explicit doubt/counterconsideration is introduced; stakes are manipulated via consequences only."
          awareness:
            provenance:
              page: 5
              quote: "It is very important that the dam is secure. Due to the high water level, if it breaks, his kids will be swept away by the water."
              tei_id: null
              table_ref: null
            reason: "The stakes are stated in the vignette presented to participants/protagonist."
          evidence:
            provenance:
              page: 5
              quote: "Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure."
              tei_id: null
              table_ref: null
            reason: "Evidence is the agent’s own checking of the logs (first-person evidence)."
          attribution_person:
            provenance:
              page: 5
              quote: "Evidence-fixed: [name] ____________ that the dam is secure. ○ knows ○ only thinks he knows."
              tei_id: null
              table_ref: null
            reason: "Participants attribute knowledge to a third person ([name])."
          evidence_reliability:
            provenance:
              page: 5
              quote: "Weak evidence: Once he has finished building the dam, he checks the logs once to make sure the dam is secure. Strong evidence: Once he has finished building the dam, he checks the logs several times to make sure the dam is secure."
              tei_id: null
              table_ref: null
            reason: "Reliability is not explicitly specified/manipulated; coded null."
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -0.597
          df1: null
          df2: null
          p: 0.5504
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.1053; Std. Error=0.1763; Odds Ratio=0.900064."
          provenance:
            page: 9
            quote: "China: -0.1053 0.1763 -0.597 0.5504 0.900064"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.058054932688
          v: 0.009447700861
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s1_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 2.278
          df1: null
          df2: null
          p: 0.0227
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=182; Estimate=0.03758; Std. Error=0.09836."
          provenance:
            page: 13
            quote: "China 182 0.03758 0.09836 2.278 0.0227"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 2
    label: "Russia (Russian)"
    objective: "Test in the Russia (Russian) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 558
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: non-students; Age mean 25.97 (sd 10.28, range 18–75); Gender % M/F/other: 40/60/0; Total N=739; Passed comprehension check N=558 (75.5%)."
      mean_age: 25.97
      mean_age_prov:
        page: 4
        quote: "Russia: Age mean 25.97 (range 18–75; sd 10.28)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Russia: N=739; Passed Check=558 (75.5%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s2_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -1.344
          df1: null
          df2: null
          p: 0.179
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.12438; Std. Error=0.09253; Odds Ratio=0.8830474."
          provenance:
            page: 9
            quote: "Russia: -0.12438 0.09253 -1.344 0.179 0.8830474"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.068574288013
          v: 0.002602475404
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s2_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 24.758
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=530; Estimate=0.54644; Std. Error=0.02207; p < 2e-16."
          provenance:
            page: 13
            quote: "Russia 530 0.54644 0.02207 24.758 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 3
    label: "Slovakia (Slovak)"
    objective: "Test in the Slovakia (Slovak) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 290
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 26.28 (sd 9.07, range 18–74); Gender % M/F/other: 54.4/44.9/0.7; Total N=713; Passed comprehension check N=290 (40.7%)."
      mean_age: 26.28
      mean_age_prov:
        page: 4
        quote: "Slovakia: Age mean 26.28 (range 18–74; sd 9.07)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Slovakia: N=713; Passed Check=290 (40.7%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s3_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -3.955
          df1: null
          df2: null
          p: 7.67e-05
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.53170; Std. Error=0.13445; Odds Ratio=0.5876024."
          provenance:
            page: 9
            quote: "Slovakia: -0.53170 0.13445 -3.955 7.67e-05 0.5876024"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.293141573696
          v: 0.005494689077
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s3_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 19.35
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=243; Estimate=0.68343; Std. Error=0.03532; p < 2e-16."
          provenance:
            page: 13
            quote: "Slovakia 243 0.68343 0.03532 19.350 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 4
    label: "Ecuador (Spanish)"
    objective: "Test in the Ecuador (Spanish) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 208
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: students; Age mean 21.39 (sd 3.21, range 18–42); Gender % M/F/other: 32.9/66.7/0.5; Total N=390; Passed comprehension check N=208 (53.3%)."
      mean_age: 21.39
      mean_age_prov:
        page: 4
        quote: "Ecuador: Age mean 21.39 (range 18–42; sd 3.21)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Ecuador: N=390; Passed Check=208 (53.3%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s4_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 0.501
          df1: null
          df2: null
          p: 0.6163
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=0.07867; Std. Error=0.15698; Odds Ratio=1.0818479."
          provenance:
            page: 9
            quote: "Ecuador - Spanish: 0.07867 0.15698 0.501 0.6163 1.0818479"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -0.043373044203
          v: 0.007490488797
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s4_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 12.97
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=172; Estimate=0.50301; Std. Error=0.03878; p < 2e-16."
          provenance:
            page: 13
            quote: "Ecuador - Spanish 172 0.50301 0.03878 12.970 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 5
    label: "India (Hindi)"
    objective: "Test in the India (Hindi) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 100
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 29.98 (sd 10.23, range 18–62); Gender % M/F/other: 45.3/53.8/0.9; Total N=200; Passed comprehension check N=100 (50%)."
      mean_age: 29.98
      mean_age_prov:
        page: 4
        quote: "India (Hindi): Age mean 29.98 (range 18–62; sd 10.23)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "India (Hindi): N=200; Passed Check=100 (50%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s5_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -0.556
          df1: null
          df2: null
          p: 0.578
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.1369; Std. Error=0.2462; Odds Ratio=0.8720179."
          provenance:
            page: 9
            quote: "India - Hindi: -0.1369 0.2462 -0.556 0.578 0.8720179"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.075476925783
          v: 0.018424580420
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s5_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 5.459
          df1: null
          df2: null
          p: 4.79e-08
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=84; Estimate=0.37698; Std. Error=0.06906."
          provenance:
            page: 13
            quote: "India - Hindi 84 0.37698 0.06906 5.459 4.79e-08"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 6
    label: "India (Meitei)"
    objective: "Test in the India (Meitei) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 42
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: non-students; Age mean 23.26 (sd 6.26, range 18–45); Gender % M/F/other: 47.6/50/2.4; Total N=86; Passed comprehension check N=42 (48.8%)."
      mean_age: 23.26
      mean_age_prov:
        page: 4
        quote: "India (Meitei): Age mean 23.26 (range 18–45; sd 6.26)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "India (Meitei): N=86; Passed Check=42 (48.8%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s6_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 0.566
          df1: null
          df2: null
          p: 0.571
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=0.4236; Std. Error=0.7480; Odds Ratio=1.5275252."
          provenance:
            page: 9
            quote: "India - Meitei: 0.4236 0.7480 0.566 0.571 1.5275252"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -0.233542920101
          v: 0.170068822598
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s6_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 1.318
          df1: null
          df2: null
          p: 0.187
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=37; Estimate=0.216273; Std. Error=0.164037."
          provenance:
            page: 13
            quote: "India - Meitei 37 0.216273 0.164037 1.318 0.187"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 7
    label: "Japan (Japanese)"
    objective: "Test in the Japan (Japanese) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 445
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 30.31 (sd 10.76, range 19–62); Gender % M/F/other: 53.3/46.3/0.4; Total N=544; Passed comprehension check N=445 (81.8%)."
      mean_age: 30.31
      mean_age_prov:
        page: 4
        quote: "Japan: Age mean 30.31 (range 19–62; sd 10.76)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Japan: N=544; Passed Check=445 (81.8%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s7_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -2.442
          df1: null
          df2: null
          p: 0.0146
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.30100; Std. Error=0.12327; Odds Ratio=0.7400757."
          provenance:
            page: 9
            quote: "Japan: -0.30100 0.12327 -2.442 0.0146 0.7400757"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.165949997522
          v: 0.004618875980
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s7_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 20.386
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=380; Estimate=0.389493; Std. Error=0.019106; p < 2e-16."
          provenance:
            page: 13
            quote: "Japan 380 0.389493 0.019106 20.386 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 8
    label: "Morocco (Arabic)"
    objective: "Test in the Morocco (Arabic) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 323
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 32.96 (sd 11.81, range 18–76); Gender % M/F/other: 44.4/55.6/0; Total N=551; Passed comprehension check N=323 (58.6%)."
      mean_age: 32.96
      mean_age_prov:
        page: 4
        quote: "Morocco: Age mean 32.96 (range 18–76; sd 11.81)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Morocco: N=551; Passed Check=323 (58.6%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s8_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -0.805
          df1: null
          df2: null
          p: 0.42072
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.1050; Std. Error=0.1304; Odds Ratio=0.9003190."
          provenance:
            page: 9
            quote: "Morocco: -0.1050 0.1304 -0.805 0.42072 0.9003190"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.057889534019
          v: 0.005168644854
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s8_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 8.01
          df1: null
          df2: null
          p: 1.15e-15
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=301; Estimate=0.30593; Std. Error=0.03819."
          provenance:
            page: 13
            quote: "Morocco 301 0.30593 0.03819 8.010 1.15e-15"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 9
    label: "Peru (Shipibo)"
    objective: "Test in the Peru (Shipibo) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 102
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: non-students; Age mean 34.68 (sd 13.77, range 18–83); Gender % M/F/other: 53.9/46.1/0; Total N=200; Passed comprehension check N=102 (51%)."
      mean_age: 34.68
      mean_age_prov:
        page: 4
        quote: "Peru (Shipibo): Age mean 34.68 (range 18–83; sd 13.77)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Peru (Shipibo): N=200; Passed Check=102 (51%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s9_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 0.012
          df1: null
          df2: null
          p: 0.991
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=5.154; Std. Error=442.314; Odds Ratio=173.18192856."
          provenance:
            page: 9
            quote: "Peru - Shipibo: 5.154 442.314 0.012 0.991 173.18192856"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -2.841549127004
          v: 59467.938119507431
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low). Note: Std. Error is extremely large (442.314), yielding a very large variance (effect effectively uninformative). See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s9_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Per Table 7 footnote, stakes effect could not be tested for Peru-Shipibo."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports NA for this sample (insufficient data to test stakes effect)."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: null
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7 reports N=3 and NA for Estimate/SE/z/p; footnote: all coded responses were from the high-stakes condition."
          provenance:
            page: 13
            quote: "Peru - Shipibo 3 NA NA NA NA"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD: Table 7 reports no stakes-effect estimate for Peru-Shipibo (insufficient data; see Table 7 footnote)."
        quality_flags: []
        notes: null

  - study_id: 10
    label: "Peru (Spanish)"
    objective: "Test in the Peru (Spanish) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 216
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: students; Age mean 22.75 (sd 3.28, range 18–49); Gender % M/F/other: 43.1/56.9/0; Total N=286; Passed comprehension check N=216 (75.5%)."
      mean_age: 22.75
      mean_age_prov:
        page: 4
        quote: "Peru (Spanish): Age mean 22.75 (range 18–49; sd 3.28)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "Peru (Spanish): N=286; Passed Check=216 (75.5%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s10_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -0.6
          df1: null
          df2: null
          p: 0.548
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.09741; Std. Error=0.16222; Odds Ratio=0.9071871."
          provenance:
            page: 9
            quote: "Peru - Spanish: -0.09741 0.16222 -0.600 0.548 0.9071871"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.053704947703
          v: 0.007998900664
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s10_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 2.549
          df1: null
          df2: null
          p: 0.0108
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=126; Estimate=0.11756; Std. Error=0.04612."
          provenance:
            page: 13
            quote: "Peru - Spanish 126 0.11756 0.04612 2.549 0.01080"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 11
    label: "South Africa (Afrikaans)"
    objective: "Test in the South Africa (Afrikaans) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 178
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 41.63 (sd 12.85, range 18–73); Gender % M/F/other: 34.3/65.7/0; Total N=270; Passed comprehension check N=178 (65.9%)."
      mean_age: 41.63
      mean_age_prov:
        page: 4
        quote: "South Africa (Afrikaans): Age mean 41.63 (range 18–73; sd 12.85)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "South Africa (Afrikaans): N=270; Passed Check=178 (65.9%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s11_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -0.431
          df1: null
          df2: null
          p: 0.666
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.07561; Std. Error=0.17525; Odds Ratio=0.9271746."
          provenance:
            page: 9
            quote: "South Africa - Afrikaans: -0.07561 0.17525 -0.431 0.666 0.9271746"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.041685977783
          v: 0.009335499556
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s11_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -1.313
          df1: null
          df2: null
          p: 0.189
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=132; Estimate=-0.06780; Std. Error=0.05164."
          provenance:
            page: 13
            quote: "South Africa - Afrikaans 132 -0.06780 0.05164 -1.313 0.189"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 12
    label: "South Africa (Sepedi)"
    objective: "Test in the South Africa (Sepedi) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 122
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: non-students; Age mean 29.33 (sd 7.88, range 18–57); Gender % M/F/other: 36.5/62/1.5; Total N=258; Passed comprehension check N=122 (47.3%)."
      mean_age: 29.33
      mean_age_prov:
        page: 4
        quote: "South Africa (Sepedi): Age mean 29.33 (range 18–57; sd 7.88)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "South Africa (Sepedi): N=258; Passed Check=122 (47.3%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s12_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 1.233
          df1: null
          df2: null
          p: 0.218
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=0.4357; Std. Error=0.3535; Odds Ratio=1.5461104."
          provenance:
            page: 9
            quote: "South Africa - Sepedi: 0.4357 0.3535 1.233 0.218 1.5461104"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -0.240213999735
          v: 0.037983969242
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s12_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 1.562
          df1: null
          df2: null
          p: 0.118
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=22; Estimate=0.364944; Std. Error=0.233666."
          provenance:
            page: 13
            quote: "South Africa - Sepedi 22 0.364944 0.233666 1.562 0.118"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 13
    label: "South Africa (isiZulu)"
    objective: "Test in the South Africa (isiZulu) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 130
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: non-students; Age mean 31.05 (sd 9.84, range 18–76); Gender % M/F/other: 27.9/69.9/2.2; Total N=268; Passed comprehension check N=130 (48.5%)."
      mean_age: 31.05
      mean_age_prov:
        page: 4
        quote: "South Africa (isiZulu): Age mean 31.05 (range 18–76; sd 9.84)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "South Africa (isiZulu): N=268; Passed Check=130 (48.5%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s13_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 0.212
          df1: null
          df2: null
          p: 0.832
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=0.08355; Std. Error=0.39391; Odds Ratio=1.0871401."
          provenance:
            page: 9
            quote: "South Africa - isiZulu: 0.08355 0.39391 0.212 0.832 1.0871401"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -0.046063529212
          v: 0.047164531159
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s13_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 0.192
          df1: null
          df2: null
          p: 0.8474
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=12; Estimate=0.04766; Std. Error=0.24772."
          provenance:
            page: 13
            quote: "South Africa - isiZulu 12 0.04766 0.24772 0.192 0.8474"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 14
    label: "South Korea (Korean)"
    objective: "Test in the South Korea (Korean) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 193
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: both; Age mean 35.40 (sd 10.37, range 18–68); Gender % M/F/other: 41.5/58.5/0; Total N=256; Passed comprehension check N=193 (75.4%)."
      mean_age: 35.4
      mean_age_prov:
        page: 4
        quote: "South Korea: Age mean 35.40 (range 18–68; sd 10.37)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "South Korea: N=256; Passed Check=193 (75.4%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s14_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 1.62
          df1: null
          df2: null
          p: 0.105
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=0.28943; Std. Error=0.17864; Odds Ratio=1.3356652."
          provenance:
            page: 9
            quote: "South Korea: 0.28943 0.17864 1.620 0.105 1.3356652"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: -0.159571122202
          v: 0.009700160706
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s14_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 15.893
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=193; Estimate=0.40194; Std. Error=0.02529; p < 2e-16."
          provenance:
            page: 13
            quote: "South Korea 193 0.40194 0.02529 15.893 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null

  - study_id: 15
    label: "United States (English)"
    objective: "Test in the United States (English) sample whether stakes (high vs low) affect (a) evidence-fixed knowledge ascription and (b) evidence-seeking judgments of required checks, in a 2×2 (evidence×stakes) between-subjects design."
    sample:
      n_final: 348
      recruitment: other
      recruitment_other: "Convenience sample (students/non-students; see Table 1)."
      compensation: null
      compensation_other: null
      characteristics: "Students: students; Age mean 35.85 (sd 10.52, range 19–73); Gender % M/F/other: 55.5/44.5/0; Total N=396; Passed comprehension check N=348 (87.9%)."
      mean_age: 35.85
      mean_age_prov:
        page: 4
        quote: "United States: Age mean 35.85 (range 19–73; sd 10.52)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
      provenance:
        page: 4
        quote: "United States: N=396; Passed Check=348 (87.9%)."
        tei_id: null
        table_ref: "tabula_stream_p4_t1.csv"
    design: "Between-Subjects"
    design_other: "2 (Evidence: weak vs strong) × 2 (Stakes: low vs high) between-subjects; participants answered comprehension check, evidence-fixed prompt, and evidence-seeking prompt."
    manipulated_factors:
      - "Evidence: weak vs strong"
    paradigm: "Other"
    paradigm_other: "Mixed DVs: evidence-fixed knowledge ascription (binary) and evidence-seeking checks-required free response (numeric; coded)."
    scale: *scale_common
    measures: *measures_common
    scenarios: *scenarios_common
    effects:
      - effect_id: s15_e1
        subgroup: "Evidence-fixed (knowledge ascription)"
        subgroup_desc: "Binary choice: '[name] knows' vs 'only thinks he knows' that the dam is secure."
        design: "Between-Subjects"
        design_other: "Reported as per-sample logistic regression stakes coefficient (Table 4) in a 2×2 (evidence×stakes) between-subjects design."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Converted from Table 4 odds ratio (log OR high vs low) to d using Cox log(OR)->d."
        reported_test:
          test: "logistic regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: -1.296
          df1: null
          df2: null
          p: 0.195
          reported_d: null
          reported_r: null
          notes: "Table 4: Estimate=-0.1457; Std. Error=0.1124; Odds Ratio=0.8644485."
          provenance:
            page: 9
            quote: "United States: -0.1457 0.1124 -1.296 0.195 0.8644485"
            tei_id: null
            table_ref: "camelot_stream_p9_t4.csv"
        effect_size:
          metric: SMD
          d: 0.080328620063
          v: 0.003840202551
          computed_from: other
          needs_review: false
          notes: "Computed from Table 4 (log OR high vs low) using d=-Estimate*sqrt(3)/pi and v=(sqrt(3)/pi)^2*SE^2. See analysis/effect_sizes.qmd."
        quality_flags: []
        notes: null

      - effect_id: s15_e2
        subgroup: "Evidence-seeking (checks required)"
        subgroup_desc: "Free response (coded numeric): number of checks required before knowing."
        design: "Between-Subjects"
        design_other: "Reported as per-sample Poisson regression stakes coefficient on coded responses (Table 7)."
        moderators: *mod_common
        moderators_coding: *mod_coding_common
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Table 7 reports Poisson regression coefficients but not per-condition means/SDs or split Ns."
        reported_test:
          test: "Poisson regression coefficient (stakes; high vs low)"
          t: null
          f: null
          chi2: null
          z: 15.87
          df1: null
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Table 7: N (coded responses)=327; Estimate=0.41068; Std. Error=0.02588; p < 2e-16."
          provenance:
            page: 13
            quote: "United States 327 0.41068 0.02588 15.870 < 2e-16"
            tei_id: null
            table_ref: "camelot_stream_p13_t7.csv"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute SMD from available outputs: Table 7 reports Poisson regression stakes coefficient (and SE) but not per-condition means/SDs or split Ns for high vs low stakes."
        quality_flags: []
        notes: null