Extraction report — Turri & Buckwalter 2017

Source: papers/turridescartessschismlockes2017/turridescartessschismlockes2017.yaml · Generated: 2026-02-16 20:00 UTC
2 studies2 effects2 needs_review

Paper

paper_idturridescartessschismlockes2017
short_labelTurri & Buckwalter 2017
citationTurri, J., & Buckwalter, W. (2017). Descartes's Schism, Locke's Reunion: Completing the Pragmatic Turn in Epistemology. American Philosophical Quarterly, 54(1), 25–45.
doi
year2017
publishedYes
languageEnglish
language_other
research_objectiveTest whether manipulating practical factors (stakes/importance and actionability) changes knowledge attributions, and whether any pragmatic effect is direct or mediated by traditional truth-related factors.
data_available_online
data_url
notesStable URL: https://www.jstor.org/stable/44982122

Experiment 1

study_id: 1

Study

study_id1
labelExperiment 1
objectiveTest whether manipulating practical factors (stakes and actionability) influences knowledge judgments, and whether any stakes effect is direct or mediated by truth-related judgments (truth, evidence, belief).
designBetween-Subjects
design_other5 (belief source) × 2 (stakes) × 2 (person) × 2 (content) between-subjects design (40 conditions).
manipulated_factorsBelief source: hunch, inference, testimony, memory, perception; Person: third vs first; Content: positive vs negative
paradigmAgreement with knowledge claim
paradigm_other
notes

Sample

n_final602
recruitmentmTurk
recruitment_other
compensationmoney
compensation_other$0.30 (approx. two minutes; online Qualtrics survey).
characteristicsAll US residents; 211 female; aged 18–78; 97% reported English as a native language.
mean_age29.7
Provenance
page
table_ref
tei_id
Participants (N = 602) were randomly assigned to one of forty conditions... / participants were recruited using Amazon Mechanical Turk (AMT)... compensated $0.30...

Scale

labelLikert 7-point
points7
anchors"Strongly Disagree" to "Strongly Agree" (coded −3 to +3 for analysis).
directionHigher values indicate stronger agreement with the statement.
Provenance
page9
table_ref
tei_id
Responses were collected on a standard 7-point Likert scale... We coded responses −3 to +3... creating a neutral midpoint of “0”.

Measures

knowledge_question_textKnowledge statement varied by condition (e.g., “Jennifer knows that Ivan is left-handed.” / “You know that Ivan did not purchase a nuclear weapon.”).
knowledge_question_first
additional_question_textOther statements measured belief (“thinks”), truth, evidence, action (“should write/should act”), and importance (“It’s important whether …”).

Scenarios

Scenarios (1)
other · Intelligence analyst (Ivan): low stakes = dominant hand; high stakes = nuclear weapon.
scenario_codeother
scenario_typeIntelligence analyst (Ivan): low stakes = dominant hand; high stakes = nuclear weapon.
Provenance
page8
table_ref
tei_id
The stakes factor varies whether the information pertains to something seemingly trivial (Ivan’s dominant hand) or something obviously very important (a nuclear weapon).

Effects

s1_e1 · Experiment 1 — Stakes → knowledge attribution · Between-Subjects · needs_review

Effect

effect_ids1_e1
subgroupExperiment 1 — Stakes → knowledge attribution
subgroup_descKnowledge score (agreement with knowledge statement), high vs low stakes (collapsed across source/person/content)
designBetween-Subjects
design_other
quality_flags
notes

Effect Size

metricSMD
d
v
computed_fromunknown
needs_reviewtrue
notesCannot compute signed SMD (d,v): the paper does not report the low vs high stakes knowledge means/SDs (or otherwise clarify direction for the stakes contrast) and does not report split Ns for the stakes levels.

Moderators

scenarioother
skeptical_pressureNo
awarenessYes
evidence
attribution_person
evidence_reliability

Contrast

group_highhigh_stakes
group_lowlow_stakes
sign_conventiond = mean(low) - mean(high)
other_notesKnowledge attribution measured by agreement with a knowledge statement (7-point Likert; coded −3 to +3 for analysis).

Moderator Coding

moderatorvaluereasonevidence
scenariootherThe vignette concerns an intelligence analyst (Ivan); it is not a bank/peanuts/bridge/typos scenario.
Provenance
page8
table_ref
tei_id
The stakes factor varies whether the information pertains to something seemingly trivial (Ivan’s dominant hand) or something obviously very important (a nuclear weapon).
skeptical_pressureNoNo explicit counterconsideration/doubt prompt is introduced (evidence source is manipulated, but no skepticism cue like 'might be wrong' is stated).
Provenance
page9
table_ref
tei_id
You are an intelligence analyst... you have a hunch which strongly suggests that Ivan did not purchase a nuclear weapon.
awarenessYesStakes are manipulated via topic importance (trivial vs very important); the agent is presented as working on that topic.
Provenance
page8
table_ref
tei_id
something obviously very important (a nuclear weapon).
evidenceEvidence type is manipulated across multiple levels (some first-person, some external), and the reported stakes effect is collapsed across these levels.
Provenance
page8
table_ref
tei_id
Source: hunch, inference, testimony, memory, and perception.
attribution_personAttribution person is manipulated (Jennifer vs You) and the reported stakes effect is collapsed across person.
Provenance
page8
table_ref
tei_id
Person: third, first.
evidence_reliabilityReliability is not explicitly quantified/manipulated for the stakes contrast; coded null.
Provenance
page
table_ref
tei_id
Even holding constant the reliability of source, people can view perception, testimony, and inference very differently in relation to knowledge.

Groups

No `groups[]` provided.

Reported Test

testregression
t-2.85
f
chi2
z
df1600
df2
p
reported_d
reported_r
notesPaper reports: t(600) = −2.85, Beta = −0.116, p < .005, adjusted R2 = .012 (Note 11). Sign of the corresponding low-vs-high knowledge mean difference is not stated.
Provenance
page16
table_refNote 11
tei_id
11. t(600) = −2.85, Beta = −0.116, p < .005, adjusted R2 = .012

Quality Flags

Experiment 2

study_id: 2

Study

study_id2
labelExperiment 2
objectiveReplicate Experiment 1 findings using a different cover story (coffee shop) and a reduced factorial design (without the person factor).
designBetween-Subjects
design_other5 (source) × 2 (stakes) × 2 (content) between-subjects design (20 conditions).
manipulated_factorsBelief source: hunch, inference, testimony, memory, perception; Content: positive vs negative
paradigmAgreement with knowledge claim
paradigm_other
notes

Sample

n_final302
recruitmentmTurk
recruitment_other
compensationmoney
compensation_other$0.30 (approx. two minutes; online Qualtrics survey).
characteristicsAll US residents (per Note 4); 113 female; aged 18–75; 96% reported English as a native language.
mean_age
Provenance
page
table_ref
tei_id
Participants (N = 302) were randomly assigned... / participants were recruited using Amazon Mechanical Turk (AMT)... compensated $0.30...

Scale

labelLikert 7-point
points7
anchors"Strongly Disagree" to "Strongly Agree" (coded −3 to +3 for analysis).
directionHigher values indicate stronger agreement with the statement.
Provenance
page9
table_ref
tei_id
Responses were collected on a standard 7-point Likert scale... We coded responses −3 to +3... creating a neutral midpoint of “0”.

Measures

knowledge_question_text(6) Christina knows that the coffee is from northern Colombia/does not contain trace amounts of pine nuts.
knowledge_question_first
additional_question_textOther statements measured belief (“thinks”), truth, evidence, action (“should write”), and importance (“It’s important whether …”).

Scenarios

Scenarios (1)
peanuts · Coffee shop / nut allergy (pine nuts).
scenario_codepeanuts
scenario_typeCoffee shop / nut allergy (pine nuts).
Provenance
page11
table_ref
tei_id
To some customers with severe nut allergies, it matters whether the coffee contains pine nuts.

Effects

s2_e1 · Experiment 2 — Stakes → knowledge attribution · Between-Subjects · needs_review

Effect

effect_ids2_e1
subgroupExperiment 2 — Stakes → knowledge attribution
subgroup_descKnowledge score (agreement with knowledge statement), high vs low stakes (collapsed across source/content)
designBetween-Subjects
design_other
quality_flags
notes

Effect Size

metricSMD
d
v
computed_fromunknown
needs_reviewtrue
notesCannot compute signed SMD (d,v): the paper does not report the low vs high stakes knowledge means/SDs (or otherwise clarify direction for the stakes contrast) and does not report split Ns for the stakes levels.

Moderators

scenariopeanuts
skeptical_pressureNo
awarenessYes
evidence
attribution_personOther
evidence_reliability

Contrast

group_highhigh_stakes
group_lowlow_stakes
sign_conventiond = mean(low) - mean(high)
other_notesKnowledge attribution measured by agreement with a knowledge statement (7-point Likert; coded −3 to +3 for analysis).

Moderator Coding

moderatorvaluereasonevidence
scenariopeanutsThe high-stakes case explicitly involves nut allergies (pine nuts), matching the 'peanuts' scenario category.
Provenance
page11
table_ref
tei_id
To some customers with severe nut allergies, it matters whether the coffee contains pine nuts.
skeptical_pressureNoNo explicit counterconsideration/doubt prompt is introduced; the evidence source varies but skepticism cues are not stated.
Provenance
page11
table_ref
tei_id
Christina notices a persistent pattern in the supplier’s shipments, which strongly suggests that the latest shipment of coffee does not contain trace amounts of pine nuts.
awarenessYesThe vignette frames the situation as important to customers and the protagonist is updating the menu with that in mind.
Provenance
page11
table_ref
tei_id
To some customers with severe nut allergies, it matters whether the coffee contains pine nuts.
evidenceEvidence source is manipulated across multiple levels (some first-person, some external), and the reported stakes effect is collapsed across these levels.
Provenance
page10
table_ref
tei_id
Participants... were randomly assigned to... a 5 (source) × 2 (stakes) × 2 (content) between-subjects design.
attribution_personOtherThe knowledge attribution is about Christina (third-person), not a self-ascription.
Provenance
page11
table_ref
tei_id
(6) Christina knows that the coffee is from northern Colombia/does not contain trace amounts of pine nuts.
evidence_reliabilitySource reliability is not explicitly quantified/manipulated for the stakes contrast; coded null.
Provenance
page10
table_ref
tei_id
The source and content manipulations were the same as in Experiment 1.

Groups

No `groups[]` provided.

Reported Test

testregression
t0.27
f
chi2
z
df1300
df2
p0.787
reported_d
reported_r
notesPaper reports: t(300) = 0.27, Beta = 0.016, p = .787, n.s. (Note 31). Sign of the corresponding low-vs-high knowledge mean difference is not stated.
Provenance
page17
table_refNote 31
tei_id
31. t(300) = 0.27, Beta = 0.016, p = .787, n.s.

Quality Flags

Raw YAML
schema_version: "1.1"

paper:
  paper_id: turridescartessschismlockes2017
  citation: "Turri, J., & Buckwalter, W. (2017). Descartes's Schism, Locke's Reunion: Completing the Pragmatic Turn in Epistemology. American Philosophical Quarterly, 54(1), 25–45."
  short_label: "Turri & Buckwalter 2017"
  doi: null
  published: "Yes"
  year: 2017
  language: "English"
  language_other: null
  research_objective: "Test whether manipulating practical factors (stakes/importance and actionability) changes knowledge attributions, and whether any pragmatic effect is direct or mediated by traditional truth-related factors."
  data_availability:
    data_available_online: null
    url: null
    notes: null
  notes: "Stable URL: https://www.jstor.org/stable/44982122"

studies:
  - study_id: 1
    label: "Experiment 1"
    objective: "Test whether manipulating practical factors (stakes and actionability) influences knowledge judgments, and whether any stakes effect is direct or mediated by truth-related judgments (truth, evidence, belief)."
    sample:
      n_final: 602
      recruitment: "mTurk"
      recruitment_other: null
      compensation: "money"
      compensation_other: "$0.30 (approx. two minutes; online Qualtrics survey)."
      characteristics: "All US residents; 211 female; aged 18–78; 97% reported English as a native language."
      mean_age: 29.7
      mean_age_prov:
        page: 16
        quote: "All US residents, 211 female, aged 18–78, mean age = 29.7; 97 percent reporting English as a native language."
        tei_id: null
        table_ref: "Note 4"
      provenance:
        page: null
        quote: "Participants (N = 602) were randomly assigned to one of forty conditions... / participants were recruited using Amazon Mechanical Turk (AMT)... compensated $0.30..."
        tei_id: null
        table_ref: null
    design: "Between-Subjects"
    design_other: "5 (belief source) × 2 (stakes) × 2 (person) × 2 (content) between-subjects design (40 conditions)."
    manipulated_factors:
      - "Belief source: hunch, inference, testimony, memory, perception"
      - "Person: third vs first"
      - "Content: positive vs negative"
    paradigm: "Agreement with knowledge claim"
    paradigm_other: null
    scale:
      label: "Likert 7-point"
      points: 7
      anchors: "\"Strongly Disagree\" to \"Strongly Agree\" (coded −3 to +3 for analysis)."
      direction: "Higher values indicate stronger agreement with the statement."
      provenance:
        page: 9
        quote: "Responses were collected on a standard 7-point Likert scale... We coded responses −3 to +3... creating a neutral midpoint of “0”."
        tei_id: null
        table_ref: null
    measures:
      knowledge_question_text: "Knowledge statement varied by condition (e.g., “Jennifer knows that Ivan is left-handed.” / “You know that Ivan did not purchase a nuclear weapon.”)."
      knowledge_question_first: null
      additional_question_text: "Other statements measured belief (“thinks”), truth, evidence, action (“should write/should act”), and importance (“It’s important whether …”)."
    scenarios:
      - scenario_code: other
        scenario_type: "Intelligence analyst (Ivan): low stakes = dominant hand; high stakes = nuclear weapon."
        high_stakes_text: null
        low_stakes_text: null
        provenance:
          page: 8
          quote: "The stakes factor varies whether the information pertains to something seemingly trivial (Ivan’s dominant hand) or something obviously very important (a nuclear weapon)."
          tei_id: null
          table_ref: null
    effects:
      - effect_id: s1_e1
        subgroup: "Experiment 1 — Stakes → knowledge attribution"
        subgroup_desc: "Knowledge score (agreement with knowledge statement), high vs low stakes (collapsed across source/person/content)"
        design: "Between-Subjects"
        design_other: null
        moderators:
          scenario: other
          skeptical_pressure: "No"
          awareness: "Yes"
          evidence: null
          attribution_person: null
          evidence_reliability: null
        moderators_coding:
          scenario:
            provenance:
              page: 8
              quote: "The stakes factor varies whether the information pertains to something seemingly trivial (Ivan’s dominant hand) or something obviously very important (a nuclear weapon)."
              tei_id: null
              table_ref: null
            reason: "The vignette concerns an intelligence analyst (Ivan); it is not a bank/peanuts/bridge/typos scenario."
          skeptical_pressure:
            provenance:
              page: 9
              quote: "You are an intelligence analyst... you have a hunch which strongly suggests that Ivan did not purchase a nuclear weapon."
              tei_id: null
              table_ref: null
            reason: "No explicit counterconsideration/doubt prompt is introduced (evidence source is manipulated, but no skepticism cue like 'might be wrong' is stated)."
          awareness:
            provenance:
              page: 8
              quote: "something obviously very important (a nuclear weapon)."
              tei_id: null
              table_ref: null
            reason: "Stakes are manipulated via topic importance (trivial vs very important); the agent is presented as working on that topic."
          evidence:
            provenance:
              page: 8
              quote: "Source: hunch, inference, testimony, memory, and perception."
              tei_id: null
              table_ref: null
            reason: "Evidence type is manipulated across multiple levels (some first-person, some external), and the reported stakes effect is collapsed across these levels."
          attribution_person:
            provenance:
              page: 8
              quote: "Person: third, first."
              tei_id: null
              table_ref: null
            reason: "Attribution person is manipulated (Jennifer vs You) and the reported stakes effect is collapsed across person."
          evidence_reliability:
            provenance:
              page: null
              quote: "Even holding constant the reliability of source, people can view perception, testimony, and inference very differently in relation to knowledge."
              tei_id: null
              table_ref: null
            reason: "Reliability is not explicitly quantified/manipulated for the stakes contrast; coded null."
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Knowledge attribution measured by agreement with a knowledge statement (7-point Likert; coded −3 to +3 for analysis)."
        groups: []
        reported_test:
          test: "regression"
          t: -2.85
          f: null
          chi2: null
          z: null
          df1: 600
          df2: null
          p: null
          reported_d: null
          reported_r: null
          notes: "Paper reports: t(600) = −2.85, Beta = −0.116, p < .005, adjusted R2 = .012 (Note 11). Sign of the corresponding low-vs-high knowledge mean difference is not stated."
          provenance:
            page: 16
            quote: "11. t(600) = −2.85, Beta = −0.116, p < .005, adjusted R2 = .012"
            tei_id: null
            table_ref: "Note 11"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute signed SMD (d,v): the paper does not report the low vs high stakes knowledge means/SDs (or otherwise clarify direction for the stakes contrast) and does not report split Ns for the stakes levels."
        quality_flags: []
        notes: null

  - study_id: 2
    label: "Experiment 2"
    objective: "Replicate Experiment 1 findings using a different cover story (coffee shop) and a reduced factorial design (without the person factor)."
    sample:
      n_final: 302
      recruitment: "mTurk"
      recruitment_other: null
      compensation: "money"
      compensation_other: "$0.30 (approx. two minutes; online Qualtrics survey)."
      characteristics: "All US residents (per Note 4); 113 female; aged 18–75; 96% reported English as a native language."
      mean_age: null
      mean_age_prov:
        page: null
        quote: null
        tei_id: null
        table_ref: null
      provenance:
        page: null
        quote: "Participants (N = 302) were randomly assigned... / participants were recruited using Amazon Mechanical Turk (AMT)... compensated $0.30..."
        tei_id: null
        table_ref: null
    design: "Between-Subjects"
    design_other: "5 (source) × 2 (stakes) × 2 (content) between-subjects design (20 conditions)."
    manipulated_factors:
      - "Belief source: hunch, inference, testimony, memory, perception"
      - "Content: positive vs negative"
    paradigm: "Agreement with knowledge claim"
    paradigm_other: null
    scale:
      label: "Likert 7-point"
      points: 7
      anchors: "\"Strongly Disagree\" to \"Strongly Agree\" (coded −3 to +3 for analysis)."
      direction: "Higher values indicate stronger agreement with the statement."
      provenance:
        page: 9
        quote: "Responses were collected on a standard 7-point Likert scale... We coded responses −3 to +3... creating a neutral midpoint of “0”."
        tei_id: null
        table_ref: null
    measures:
      knowledge_question_text: "(6) Christina knows that the coffee is from northern Colombia/does not contain trace amounts of pine nuts."
      knowledge_question_first: null
      additional_question_text: "Other statements measured belief (“thinks”), truth, evidence, action (“should write”), and importance (“It’s important whether …”)."
    scenarios:
      - scenario_code: peanuts
        scenario_type: "Coffee shop / nut allergy (pine nuts)."
        high_stakes_text: null
        low_stakes_text: null
        provenance:
          page: 11
          quote: "To some customers with severe nut allergies, it matters whether the coffee contains pine nuts."
          tei_id: null
          table_ref: null
    effects:
      - effect_id: s2_e1
        subgroup: "Experiment 2 — Stakes → knowledge attribution"
        subgroup_desc: "Knowledge score (agreement with knowledge statement), high vs low stakes (collapsed across source/content)"
        design: "Between-Subjects"
        design_other: null
        moderators:
          scenario: peanuts
          skeptical_pressure: "No"
          awareness: "Yes"
          evidence: null
          attribution_person: "Other"
          evidence_reliability: null
        moderators_coding:
          scenario:
            provenance:
              page: 11
              quote: "To some customers with severe nut allergies, it matters whether the coffee contains pine nuts."
              tei_id: null
              table_ref: null
            reason: "The high-stakes case explicitly involves nut allergies (pine nuts), matching the 'peanuts' scenario category."
          skeptical_pressure:
            provenance:
              page: 11
              quote: "Christina notices a persistent pattern in the supplier’s shipments, which strongly suggests that the latest shipment of coffee does not contain trace amounts of pine nuts."
              tei_id: null
              table_ref: null
            reason: "No explicit counterconsideration/doubt prompt is introduced; the evidence source varies but skepticism cues are not stated."
          awareness:
            provenance:
              page: 11
              quote: "To some customers with severe nut allergies, it matters whether the coffee contains pine nuts."
              tei_id: null
              table_ref: null
            reason: "The vignette frames the situation as important to customers and the protagonist is updating the menu with that in mind."
          evidence:
            provenance:
              page: 10
              quote: "Participants... were randomly assigned to... a 5 (source) × 2 (stakes) × 2 (content) between-subjects design."
              tei_id: null
              table_ref: null
            reason: "Evidence source is manipulated across multiple levels (some first-person, some external), and the reported stakes effect is collapsed across these levels."
          attribution_person:
            provenance:
              page: 11
              quote: "(6) Christina knows that the coffee is from northern Colombia/does not contain trace amounts of pine nuts."
              tei_id: null
              table_ref: null
            reason: "The knowledge attribution is about Christina (third-person), not a self-ascription."
          evidence_reliability:
            provenance:
              page: 10
              quote: "The source and content manipulations were the same as in Experiment 1."
              tei_id: null
              table_ref: null
            reason: "Source reliability is not explicitly quantified/manipulated for the stakes contrast; coded null."
        contrast:
          group_high: high_stakes
          group_low: low_stakes
          sign_convention: "d = mean(low) - mean(high)"
          other_notes: "Knowledge attribution measured by agreement with a knowledge statement (7-point Likert; coded −3 to +3 for analysis)."
        groups: []
        reported_test:
          test: "regression"
          t: 0.27
          f: null
          chi2: null
          z: null
          df1: 300
          df2: null
          p: 0.787
          reported_d: null
          reported_r: null
          notes: "Paper reports: t(300) = 0.27, Beta = 0.016, p = .787, n.s. (Note 31). Sign of the corresponding low-vs-high knowledge mean difference is not stated."
          provenance:
            page: 17
            quote: "31. t(300) = 0.27, Beta = 0.016, p = .787, n.s."
            tei_id: null
            table_ref: "Note 31"
        effect_size:
          metric: SMD
          d: null
          v: null
          computed_from: unknown
          needs_review: true
          notes: "Cannot compute signed SMD (d,v): the paper does not report the low vs high stakes knowledge means/SDs (or otherwise clarify direction for the stakes contrast) and does not report split Ns for the stakes levels."
        quality_flags: []
        notes: null