schema_version: '1.2'
paper:
  paper_id: pinillossimpsonndexperimentalevidencesupporting
  citation: 'Pinillos, N. Á., & Simpson, S. (2014). Experimental Evidence Supporting Anti-intellectualism About Knowledge.
    In J. R. Beebe (Ed.), Advances in Experimental Epistemology (Chapter 1, pp. 9–44). Bloomsbury Academic. ISBN: 978-1-4725-0737-2.'
  short_label: Pinillos & Simpson 2014
  doi: null
  published: 'Yes'
  year: null
  language: English
  language_other: null
  research_objective: Provide experimental evidence for anti-intellectualism about knowledge by testing whether folk judgments
    about when an agent knows are sensitive to practical interests (stakes), using evidence-seeking and agreement paradigms,
    and by addressing objections to evidence-seeking probes.
  data_availability:
    data_available_online: null
    url: null
    notes: null
  notes: Year/venue details were not recoverable from the provided PDF text/metadata; keep as n.d. pending manual bibliographic
    completion.
studies:
- study_id: 1
  label: Study 1, Experiment 1 (Water purifier; evidence-seeking)
  language: English
  language_other: null
  objective: Test whether participants require more evidence for knowledge under higher stakes (water purifier vignette; numeric
    evidence-seeking prompt).
  sample:
    n_final: 94
    recruitment: mTurk
    recruitment_other: null
    compensation: money
    compensation_other: 15 cents (US)
    characteristics: Amazon Turk workers; initial N=141; exclusions reported; computed statistics for N=94. Given 10 minutes
      to respond
    mean_age: null
    provenance:
      page: 10
      quote: A total of 141 subjects from Amazon Turk were paid 15 cents (US) each to take exactly one of two surveys.
  design: Between-Subjects
  design_other: 'Two independent conditions: Low Stakes vs High Stakes.'
  manipulated_factors: []
  paradigm: Rating how much evidence is needed for knowledge
  paradigm_other: null
  scale:
    label: numeric/text input
    points: null
    anchors: 'Numeric free response (whole number). Instructions: write “0” if already knows; write “never” if never knows.'
    direction: Higher numbers indicate more checks/comparisons required (more evidence needed for knowledge).
    provenance:
      page: 11
      quote: 'After how many comparisons will Brian know he has written them down correctly? ... This should be a whole number.
        (Note: If you think Brian already knows, write “0.” If you think he’ll never know, no matter how many times he checks,
        write “never”).'
  measures:
    knowledge_question_text: "(Opinion question) Suppose Brian goes back and compares his entire \r\nwritten copy to the instructions\
      \ online, and he can do this as many times \r\nas he wants. After how many comparisons will Brian know he has written\
      \ \r\nthem down correctly? Please write your answer in the box below. This \r\nshould be a whole number. (Note: If you\
      \ think Brian already knows, write \r\n“0.” If you think he’ll never know, no matter how many times he checks, \r\n\
      write “never”)."
    knowledge_question_first: null
    additional_question_text: The reading comprehension checks were placed before the target question and included a question
      to see if subjects were aware of what was at stake.
  scenarios:
  - scenario_code: water_purifier
    scenario_type: Installing a water purifier; high-stakes manipulation involves unknown poisoning risk.
    high_stakes_text: In High Stakes, it is also the case that the water supply has been poisoned... If Brian fails to assemble
      the water purifier properly, he and his family might die. However, Brian is ignorant of these high stakes.
    low_stakes_text: 'Low Stakes: Brian installs the purifier because he does not like the taste of tap water.'
    provenance:
      page: 10
      quote: They both concern a protagonist, Brian, who is installing a water purifier... However, in High Stakes, it is
        also the case that the water supply has been poisoned... he and his family might die. However, Brian is ignorant of
        these high stakes.
  effects:
  - effect_id: s1_e1
    subgroup: Water purifier — evidence-seeking knowledge
    subgroup_desc: Number of comparisons required for knowledge
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: other
      skeptical_pressure: 'No'
      awareness: 'No'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 10
          quote: Brian... is installing a water purifier at home... in High Stakes... the water supply has been poisoned.
          tei_id: null
          table_ref: null
        reason: The vignette is about a water purifier/poisoning scenario, not a bank/peanuts/bridge/typos vignette.
      skeptical_pressure:
        provenance:
          page: 11
          quote: After how many comparisons will Brian know he has written them down correctly?
          tei_id: null
          table_ref: null
        reason: No explicit alternative/error possibility is raised as a live option; the manipulation concerns consequences.
      awareness:
        provenance:
          page: 10
          quote: However, Brian is ignorant of these high stakes.
          tei_id: null
          table_ref: null
        reason: High-stakes consequences are explicitly unknown to the protagonist.
      evidence:
        provenance:
          page: 11
          quote: Suppose Brian goes back and compares his entire written copy to the instructions online...
          tei_id: null
          table_ref: null
        reason: The evidence is generated by the agent’s own checking/comparing (first-person evidence).
      attribution_person:
        provenance:
          page: 11
          quote: After how many comparisons will Brian know...
          tei_id: null
          table_ref: null
        reason: Participants attribute knowledge to Brian (third-person attribution).
      evidence_reliability:
        provenance:
          page: 11
          quote: "In order to get a copy, Brian logged onto his computer down the hall and pulled up the instructions from\
            \ the manufacturer’s website. He wrote the instructions on a sheet of paper \r\n(he didn’t have a printer). Feeling\
            \ confident and believing he wrote them down correctly, he headed back to the faucet."
          tei_id: null
          table_ref: null
        reason: compared the instructions once
    contrast:
      group_high: WaterPurifier_high
      group_low: WaterPurifier_low
      sign_convention: d = mean(low) - mean(high)
      other_notes: Outcome is number of comparisons/checks; higher scores indicate more evidence needed.
    groups:
    - group_id: WaterPurifier_low
      label: null
      n: 46
      mean: 0.72
      sd: 0.72
      se: null
      provenance:
        page: 11
        quote: Low Stakes (N  46, m  0.72, sd  0.72)
        tei_id: null
        table_ref: null
    - group_id: WaterPurifier_high
      label: null
      n: 48
      mean: 1.29
      sd: 1.254
      se: null
      provenance:
        page: 11
        quote: High Stakes (N  48, m  1.29, sd  1.254)
        tei_id: null
        table_ref: null
    reported_test:
      test: t
      t: -2.7
      df1: 75.54
      reported_d: 0.54
      notes: Reported as p < 0.01. Paper’s reported Cohen’s d is unsigned/positive; extraction uses sign convention d = mean(low)
        - mean(high).
      provenance:
        page: 11
        quote: t(75.54)  2.70, p  0.01. Cohen’s d  0.54 (this is a medium-size effect).
    effect_size:
      metric: SMD
      d: -0.554440139474935
      v: 0.0442431369651865
      computed_from: groups
      needs_review: false
      notes: Computed from group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups).
    quality_flags: []
    notes: null
  notes: full texts of the vignettes in the Appendix
- study_id: 2
  label: Study 1, Experiment 2 (Airplane; evidence-seeking; stakes × probability)
  language: English
  language_other: null
  objective: Test whether participants require more evidence for knowledge under higher stakes and/or higher probability of
    negative outcomes (airline roster vignette; 2×2 between-subjects).
  sample:
    n_final: 230
    recruitment: students
    recruitment_other: Volunteer students taking introductory courses at Arizona State University (randomly distributed surveys).
    compensation: no compensation
    compensation_other: Volunteer students
    characteristics: Students taking introductory courses at Arizona State University. Four conditions (LSLP/LSHP/HSLP/HSHP);
      initial surveys distributed total=305; exclusions reported; computed statistics for N=230.
    mean_age: null
    provenance:
      page: 13
      quote: We discarded 75 surveys... We computed statistics for N  230 subjects. LSLP (N  50, m  1.6, sd  0.969), LSHP
        (N  58, m  1.76, sd  0.823), HSLP (N  61, m  1.93, sd  0.944), and HSHP (N  61, m  2.15, sd  1.152) (Figure
        1.1).
      table_ref: Figure 1.1
  design: Between-Subjects
  design_other: '2 (stakes: low vs high) × 2 (probability: low vs high) between-subjects.'
  manipulated_factors:
  - 'Probability of outcome: low vs high'
  paradigm: Rating how much evidence is needed for knowledge
  paradigm_other: null
  scale:
    label: numeric/text input
    points: null
    anchors: 'Numeric free response: number of additional roster surveys (whole number 0,1,2,3...) or “never”.'
    direction: Higher numbers indicate more evidence needed for knowledge.
    provenance:
      page: 13
      quote: How many more times do you think Jessie needs to survey the entire roster before he knows the name is not on
        the list (enter a whole number... or write “never” if you think Jessie will never know).
  measures:
    knowledge_question_text: "We are now interested in your opinion about what it would take for Jessie \r\nto know that the\
      \ name is not on the roster (the name of the nice guy/\r\nhijacker). Recall that according to the story, Jessie has\
      \ already surveyed \r\nthe entire roster once. How many more times do you think Jessie needs to \r\nsurvey the entire\
      \ roster before he knows the name is not on the list (enter a \r\nwhole number: 0,1,2,3, . . . etc. or write “never”\
      \ if you think Jessie will never \r\nknow)."
    knowledge_question_first: null
    additional_question_text: "The surveys contained reading comprehension checks. The reading comprehension checks occurred\
      \ before the target question and they included \r\nquestions checking to see if subjects knew what was at stake (and\
      \ the probabilities)."
  scenarios:
  - scenario_code: airplane_roster
    scenario_type: Airline steward checks passenger roster; stakes and probability of hijacking (high) vs first-class upgrade
      acceptance (low).
    high_stakes_text: 'High stakes: if wrong, (low/high probability) a criminal would hijack the plane; Jessie is unaware
      of hijacker/probability.'
    low_stakes_text: 'Low stakes: if wrong, (low/high probability) a nice guy would accept first class; Jessie is unaware
      of nice guy/probability.'
    provenance:
      page: 13
      quote: In high stakes–high probability (HSHP)... a criminal, would hijack the plane... In low stakes–high probability
        (LSHP)... a nice guy, would accept the invitation to go to first class... Again, Jessie is unaware...
  effects:
  - effect_id: s2_e1
    subgroup: Airplane — Low probability (LSLP vs HSLP)
    subgroup_desc: 'Evidence-seeking: roster checks required for knowledge (low probability)'
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: airport
      skeptical_pressure: 'No'
      awareness: 'No'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 13
          quote: They are about an airline steward, Jessie, who is assigned to find a name on a roster of 200 passengers before
            a flight.
          tei_id: null
          table_ref: null
        reason: The scenario is an airplane/roster vignette; coded airport.
      skeptical_pressure:
        provenance:
          page: 13
          quote: How many more times do you think Jessie needs to survey the entire roster before he knows the name is not
            on the list...
          tei_id: null
          table_ref: null
        reason: No explicit alternative/error possibility is raised as a conversational challenge; stakes/probability are
          manipulated as consequences.
      awareness:
        provenance:
          page: 13
          quote: Again, Jessie is unaware that the name belongs to a nice guy/hijacker and unaware of the probability...
          tei_id: null
          table_ref: null
        reason: The protagonist is explicitly unaware of the stake-relevant facts and probabilities.
      evidence:
        provenance:
          page: 13
          quote: How many more times do you think Jessie needs to survey the entire roster...
          tei_id: null
          table_ref: null
        reason: Evidence is generated by the agent’s own repeated surveying of the roster (first-person).
      attribution_person:
        provenance:
          page: 13
          quote: before he knows the name is not on the list
          tei_id: null
          table_ref: null
        reason: Participants attribute knowledge to Jessie (third-person attribution).
      evidence_reliability:
        provenance:
          page: 13
          quote: "After looking through the roster \r\nonce, Jessie thinks this name is not on the list, and in fact it is\
            \ not on the list."
          tei_id: null
          table_ref: null
        reason: checked once
    contrast:
      group_high: HSLP
      group_low: LSLP
      sign_convention: d = mean(low) - mean(high)
      other_notes: Probability held constant at low probability; outcome is number of additional roster surveys required.
    groups:
    - group_id: LSLP
      label: null
      n: 50
      mean: 1.6
      sd: 0.969
      se: null
      provenance:
        page: 13
        quote: LSLP (N  50, m  1.6, sd  0.969)
        tei_id: null
        table_ref: Figure 1.1
    - group_id: HSLP
      label: null
      n: 61
      mean: 1.93
      sd: 0.944
      se: null
      provenance:
        page: 13
        quote: HSLP (N  61, m  1.93, sd  0.944)
        tei_id: null
        table_ref: Figure 1.1
    reported_test:
      notes: No simple-effect test for LSLP vs HSLP reported; paper reports an overall main effect for stakes across probability
        conditions.
      provenance:
        page: 14
        quote: Comparing all the low-stakes cases against the high-stakes cases reveals a statistically significant main effect
          for stakes F(1,224)  7.639, p  0.01. Cohen’s d  0.38 (moderate effect size).
    effect_size:
      metric: SMD
      d: -0.345434178152552
      v: 0.0369408039598129
      computed_from: groups
      needs_review: false
      notes: Computed from group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups).
    quality_flags: []
    notes: null
  - effect_id: s2_e2
    subgroup: Airplane — High probability (LSHP vs HSHP)
    subgroup_desc: 'Evidence-seeking: roster checks required for knowledge (high probability)'
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: airport
      skeptical_pressure: 'No'
      awareness: 'No'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 13
          quote: They are about an airline steward, Jessie, who is assigned to find a name on a roster of 200 passengers before
            a flight.
          tei_id: null
          table_ref: null
        reason: The scenario is an airplane/roster vignette; coded airport.
      skeptical_pressure:
        provenance:
          page: 13
          quote: How many more times do you think Jessie needs to survey the entire roster before he knows the name is not
            on the list...
          tei_id: null
          table_ref: null
        reason: No explicit alternative/error possibility is raised as a conversational challenge; stakes/probability are
          manipulated as consequences.
      awareness:
        provenance:
          page: 13
          quote: Again, Jessie is unaware that the name belongs to a nice guy/hijacker and unaware of the probability...
          tei_id: null
          table_ref: null
        reason: The protagonist is explicitly unaware of the stake-relevant facts and probabilities.
      evidence:
        provenance:
          page: 13
          quote: How many more times do you think Jessie needs to survey the entire roster...
          tei_id: null
          table_ref: null
        reason: Evidence is generated by the agent’s own repeated surveying of the roster (first-person).
      attribution_person:
        provenance:
          page: 13
          quote: before he knows the name is not on the list
          tei_id: null
          table_ref: null
        reason: Participants attribute knowledge to Jessie (third-person attribution).
      evidence_reliability:
        provenance:
          page: 13
          quote: "After looking through the roster \r\nonce, Jessie thinks this name is not on the list, and in fact it is\
            \ not on the list."
          tei_id: null
          table_ref: null
        reason: checked once
    contrast:
      group_high: HSHP
      group_low: LSHP
      sign_convention: d = mean(low) - mean(high)
      other_notes: Probability held constant at high probability; outcome is number of additional roster surveys required.
    groups:
    - group_id: LSHP
      label: null
      n: 58
      mean: 1.76
      sd: 0.823
      se: null
      provenance:
        page: 13
        quote: LSHP (N  58, m  1.76, sd  0.823)
        tei_id: null
        table_ref: Figure 1.1
    - group_id: HSHP
      label: null
      n: 61
      mean: 2.15
      sd: 1.152
      se: null
      provenance:
        page: 13
        quote: HSHP (N  61, m  2.15, sd  1.152)
        tei_id: null
        table_ref: Figure 1.1
    reported_test:
      notes: No simple-effect test for LSHP vs HSHP reported; paper reports an overall main effect for stakes across probability
        conditions.
      provenance:
        page: 14
        quote: Comparing all the low-stakes cases against the high-stakes cases reveals a statistically significant main effect
          for stakes F(1,224)  7.639, p  0.01. Cohen’s d  0.38 (moderate effect size).
    effect_size:
      metric: SMD
      d: -0.387959471896737
      v: 0.034278037966776
      computed_from: groups
      needs_review: false
      notes: Computed from group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups).
    quality_flags: []
    notes: full vignettes not provided in the article
  notes: full vignettes in the Appendix
- study_id: 3
  label: Study 2 (Coin; agreement with knowledge ascription)
  language: English
  language_other: null
  objective: Test whether stakes affect agreement with a knowledge ascription in a coin-counting vignette.
  sample:
    n_final: 165
    recruitment: mTurk
    recruitment_other: null
    compensation: money
    compensation_other: null
    characteristics: Amazon Turk workers in the United States; coin-counting vignette; Table 1.1 reports group Ns.
    mean_age: null
    provenance:
      page: 15
      quote: The surveys were taken by Amazon Turk workers in the United States.
  design: Between-Subjects
  design_other: 'Two independent conditions: Low stakes vs High stakes.'
  manipulated_factors: []
  paradigm: Agreement with knowledge claim
  paradigm_other: null
  scale:
    label: Likert 7-point
    points: 7
    anchors: 0–6; 6 = strongly agree; 3 = neutral
    direction: Higher numbers indicate stronger agreement with the knowledge ascription.
    provenance:
      page: 15
      quote: a 7-point Likert scale (0-6) where 6 is "strongly agree" and 3 is "neutral"
  measures:
    knowledge_question_text: 'To what extent do you agree with the statement: "PETER KNOWS THERE ARE 134 COINS IN THE JAR"'
    knowledge_question_first: 'No'
    additional_question_text: "For these experiments, we also added a “normative” question before the \r\nknowledge prompt.\
      \ For example, in the COIN case we asked whether the \r\nsubject thought Peter should count the pennies again."
  scenarios:
  - scenario_code: coin
    scenario_type: Counting coins in a jar for a contest; stakes manipulation via prize importance and mother’s operation.
    high_stakes_text: "Coin High Stakes: Peter is a college student who has entered a contest \r\nsponsored by a local bank.\
      \ His task is to count the coins in a jar. The jar contains 134 coins. Peter mistakenly thinks the contest prize is\
      \ one hundred dollars. In fact, the prize is $10,000 which Peter really needs. He would use the money to help pay for\
      \ a life-saving operation for his mother who is sick and cannot afford healthcare. So the stakes are high for Peter\
      \ since if he \r\ndoesn’t win the contest, his mother could die. After counting the coins just once, Peter concludes\
      \ there are 134 coins in the jar. His friend, who also thinks the prize is one hundred dollars says to Peter “you only\
      \ counted once, even if there are in fact 134 coins in the jar, you don’t know there are 134 coins in the jar. You should\
      \ count them again.”"
    low_stakes_text: "Coin Low Stakes: Peter is a college student who has entered a contest sponsored by a local bank. His\
      \ task is to count the coins in a jar. The jar contains 134 coins. Peter mistakenly thinks the contest prize is one\
      \ hundred dollars. In fact, the prize is just a pair of movie passes for this weekend. Peter wouldn’t want them, however,\
      \ since he is leaving town this weekend. So \r\nnothing bad would happen if Peter doesn’t win the contest. After counting\
      \ the coins just once, Peter concludes there are 134 coins in the jar. His friend, who also thinks the prize is one\
      \ hundred dollars says to Peter “you only counted once, even if there are in fact 134 coins in the jar, you don’t know\
      \ there are 134 coins in the jar. You should count them again.”"
    provenance:
      page: 15
      quote: Coin Low Stakes... the prize is just a pair of movie passes... So nothing bad would happen... Coin High Stakes...
        the prize is $10,000... life-saving operation for his mother... his mother could die.
  effects:
  - effect_id: s3_e1
    subgroup: Coin — knowledge ascription agreement
    subgroup_desc: Agreement with knowledge statement (Likert 0–6)
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: other
      skeptical_pressure: 'Yes'
      awareness: 'No'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 15
          quote: Coin... count the coins in a jar. The jar contains 134 coins.
          tei_id: null
          table_ref: null
        reason: The vignette concerns coin-counting (not bank/peanuts/bridge/typos).
      skeptical_pressure:
        provenance:
          page: 15
          quote: His friend... says to Peter “you only counted once... you don’t know there are 134 coins in the jar... You
            should count them again.”
          tei_id: null
          table_ref: null
        reason: A friend explicitly denies knowledge and challenges the adequacy of the evidence.
      awareness:
        provenance:
          page: 15
          quote: the protagonist is ignorant of what is at stake... the protagonist is always mistaken about what is at stake
          tei_id: null
          table_ref: null
        reason: The paper states protagonists are ignorant/mistaken about the stakes in both low/high conditions.
      evidence:
        provenance:
          page: 15
          quote: After counting the coins just once, Peter concludes there are 134 coins in the jar.
          tei_id: null
          table_ref: null
        reason: Evidence is generated by the agent’s own counting (first-person evidence).
      attribution_person:
        provenance:
          page: 15
          quote: '"PETER KNOWS THERE ARE 134 COINS IN THE JAR"'
          tei_id: null
          table_ref: null
        reason: Participants judge a third-person knowledge ascription.
      evidence_reliability:
        provenance:
          page: 15
          quote: After counting the coins just once...
          tei_id: null
          table_ref: null
        reason: counted once
    contrast:
      group_high: Coin_high
      group_low: Coin_low
      sign_convention: d = mean(low) - mean(high)
      other_notes: Outcome is agreement with the knowledge statement; higher scores indicate more agreement.
    groups:
    - group_id: Coin_low
      label: null
      n: 87
      mean: 3.68
      sd: 1.8
      se: null
      provenance:
        page: 17
        quote: 'Coin (Likert: 0–6) N  87, m  3.68, sd  1.80'
        tei_id: null
        table_ref: Table 1.1
    - group_id: Coin_high
      label: null
      n: 78
      mean: 3.06
      sd: 1.76
      se: null
      provenance:
        page: 17
        quote: 'Coin (Likert: 0–6) N  78, m  3.06, sd  1.76'
        tei_id: null
        table_ref: Table 1.1
    reported_test:
      test: t
      t: 2.23
      df1: 161.78
      p: 0.023
      reported_d: 0.35
      provenance:
        page: 17
        quote: Coin vignettes t(161.78)  2.23, p  0.023, d  0.35 (small effect size)
    effect_size:
      metric: SMD
      d: 0.348076772822079
      v: 0.0246864142823528
      computed_from: groups
      needs_review: false
      notes: Computed from Table 1.1 group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups).
    quality_flags: []
    notes: null
  notes: null
- study_id: 4
  label: Study 2 (Air; agreement with knowledge ascription)
  language: English
  language_other: null
  objective: Test whether stakes affect agreement with a knowledge ascription in the Air probe.
  sample:
    n_final: 55
    recruitment: mTurk
    recruitment_other: null
    compensation: money
    compensation_other: null
    characteristics: Amazon Turk workers in the United States; Air probe appendix material located in out/external/pinillos
      IRI paper with shawn october 2014.pdf; Table 1.1 reports group Ns.
    mean_age: null
    provenance:
      page: 15
      quote: The surveys were taken by Amazon Turk workers in the United States.
  design: Between-Subjects
  design_other: 'Two independent conditions: Low stakes vs High stakes.'
  manipulated_factors: []
  paradigm: Agreement with knowledge claim
  paradigm_other: null
  scale:
    label: Likert 5-point
    points: 5
    anchors: 0–4; 4 = strongly agree; 2 = neutral
    direction: Higher numbers indicate stronger agreement with the knowledge ascription.
    provenance:
      page: 15
      quote: Air and Bridge, with 5-point Likert scales (0-4) where 4 is "strongly agree" and 2 is "neutral" (See Web Appendix).
  measures:
    knowledge_question_text: After surveying the roster just that one time, Jason knew that the name was not on the list
    knowledge_question_first: 'No'
    additional_question_text: "For these experiments, we also added a “normative” question before the \r\nknowledge prompt.\
      \ For example, in the COIN case we asked whether the \r\nsubject thought Peter should count the pennies again."
  scenarios:
  - scenario_code: air
    scenario_type: Air probe; appendix includes Air vignettes and the level-of-agreement prompt.
    high_stakes_text: Jessie checks a flight roster once, thinks the stakes are low, but the name actually belongs to a dangerous
      individual wanted by the FBI; if the individual were on the flight, the plane could be hijacked.
    low_stakes_text: Jessie checks a flight roster once, thinks the stakes are low, and the name actually belongs to a nice
      passenger who might be bumped up to first class.
    provenance:
      page: 45
      quote: APPENDIX (This will be a WEB Appendix)... AIR (HSHP)... AIR(HSLP)... AIR (LSHP)... AIR(LSLP)... Level of Agreement
        Question for Air.
  effects:
  - effect_id: s4_e1
    subgroup: Air — knowledge ascription agreement
    subgroup_desc: Agreement with knowledge statement (Likert 0–4)
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: other
      skeptical_pressure: 'No'
      awareness: 'No'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 15
          quote: We developed three pairs of vignettes (Coin, Air, and Bridge)
          tei_id: null
          table_ref: null
        reason: Probe is labeled 'Air'; the vignette is not bank/peanuts/bridge/typos.
      skeptical_pressure:
        provenance:
          page: 15
          quote: null
          tei_id: null
          table_ref: null
        reason: no skeptical pressure
      awareness:
        provenance:
          page: 15
          quote: in both the low-stakes and high-stakes conditions, the protagonist is ignorant of what is at stake.
          tei_id: null
          table_ref: null
        reason: Paper explicitly states protagonists are ignorant of the stakes in Study 2 vignettes.
      evidence:
        provenance:
          page: 32
          quote: The normative prompt for AIR was “Do you think Jason should look through the entire roster at least one more
            time?”
          tei_id: null
          table_ref: null
        reason: The Air probe involves the agent looking through a roster, indicating first-person evidence from the agent’s
          own checking.
      attribution_person:
        provenance:
          page: 15
          quote: Subjects are asked about the extent to which they agree or disagree with a statement that says that the protagonist
            knows P.
          tei_id: null
          table_ref: null
        reason: The DV is agreement with a third-person knowledge ascription.
      evidence_reliability:
        provenance:
          page: 15
          quote: null
          tei_id: null
          table_ref: null
        reason: checked once
    contrast:
      group_high: Air_high
      group_low: Air_low
      sign_convention: d = mean(low) - mean(high)
      other_notes: Outcome is agreement with the knowledge statement; higher scores indicate more agreement.
    groups:
    - group_id: Air_low
      label: null
      n: 25
      mean: 2.16
      sd: 1.03
      se: null
      provenance:
        page: 17
        quote: Air (Likert 0–4) N  25, m  2.16, sd  1.03
        tei_id: null
        table_ref: Table 1.1
    - group_id: Air_high
      label: null
      n: 30
      mean: 2.03
      sd: 1.0
      se: null
      provenance:
        page: 17
        quote: Air (Likert 0–4) N  30, m  2.03, sd  1.0
        tei_id: null
        table_ref: Table 1.1
    reported_test:
      test: t
      t: 0.462
      df1: 53.0
      p: 0.646
      provenance:
        page: 32
        quote: '21 Air: t(53)  0.462, p  0.646.'
    effect_size:
      metric: SMD
      d: 0.128243714633482
      v: 0.0734884885252484
      computed_from: groups
      needs_review: false
      notes: Computed from Table 1.1 group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups). Appendix material
        located in out/external/pinillos IRI paper with shawn october 2014.pdf; Air vignette/prompt reviewed.
    quality_flags: []
    notes: null
  notes: Appendix material located in out/external/pinillos IRI paper with shawn october 2014.pdf.
- study_id: 5
  label: Study 2 (Bridge; agreement with knowledge ascription)
  language: English
  language_other: null
  objective: Test whether stakes affect agreement with a knowledge ascription in the Bridge probe.
  sample:
    n_final: null
    recruitment: mTurk
    recruitment_other: null
    compensation: money
    compensation_other: null
    characteristics: Amazon Turk workers in the United States; Bridge probe appendix material located in out/external/pinillos
      IRI paper with shawn october 2014.pdf; Table 1.1 reports group Ns.
    mean_age: null
    provenance:
      page: 15
      quote: The surveys were taken by Amazon Turk workers in the United States.
  design: Between-Subjects
  design_other: 'Two independent conditions: Low stakes vs High stakes.'
  manipulated_factors: []
  paradigm: Agreement with knowledge claim
  paradigm_other: null
  scale:
    label: Likert 5-point
    points: 5
    anchors: 0–4; 4 = strongly agree; 2 = neutral
    direction: Higher numbers indicate stronger agreement with the knowledge ascription.
    provenance:
      page: 15
      quote: Air and Bridge, with 5-point Likert scales (0-4) where 4 is "strongly agree" and 2 is "neutral" (See Web Appendix).
  measures:
    knowledge_question_text: 'Assume the bridge is safe enough to cross. We want your sincere opinion on this question: to
      what extent do you agree or disagree with the following sentence: "JOHN KNOWS HIS TRUCK WILL MAKE IT ACROSS THE BRIDGE"?'
    knowledge_question_first: 'No'
    additional_question_text: "“Do you think that John should just cross the bridge.” For BRIDGE and \r\nAIR, subjects were\
      \ not given a “Neutral” option in responding, it was just a \r\nbinary “Yes” and “No.”"
  scenarios:
  - scenario_code: bridge
    scenario_type: Bridge probe; full low/high vignettes available in the appendix.
    high_stakes_text: John drives a truck over a rickety bridge after hearing that two other trucks crossed safely. He is
      unaware that dangerous explosive materials are in his cargo; if the bridge fails, the truck will explode and kill John
      and many nearby people.
    low_stakes_text: John drives a truck over a rickety bridge after hearing that two other trucks crossed safely. He is
      unaware that eggs are in his cargo; if the bridge fails, the eggs will break and can be easily replaced.
    provenance:
      page: 48
      quote: BRIDGE LOW... BRIDGE HIGH... LEVEL OF AGREEMENT QUESTION BRIDGE.
  effects:
  - effect_id: s5_e1
    subgroup: Bridge — knowledge ascription agreement
    subgroup_desc: Agreement with knowledge statement (Likert 0–4)
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: bridge
      skeptical_pressure: 'No'
      awareness: 'No'
      evidence: External
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 15
          quote: We developed three pairs of vignettes (Coin, Air, and Bridge)
          tei_id: null
          table_ref: null
        reason: Probe is explicitly labeled Bridge; coded as the bridge scenario.
      skeptical_pressure:
        provenance:
          page: 15
          quote: null
          tei_id: null
          table_ref: null
        reason: no indication
      awareness:
        provenance:
          page: 15
          quote: But John is not at all aware that there are dangerous explosive materials delicately arranged in his cargo.
          tei_id: null
          table_ref: null
        reason: Paper explicitly states protagonists are ignorant of the stakes in Study 2 vignettes.
      evidence:
        provenance:
          page: 15
          quote: He radios ahead to find out whether other trucks have made it across. He is told that the other two trucks
            in the caravan made it over safely.
          tei_id: null
          table_ref: null
        reason: talks to someone
      attribution_person:
        provenance:
          page: 15
          quote: "to what extent do you agree or disagree with the following sentence: \"JOHN KNOWS HIS TRUCK \r\nWILL MAKE\
            \ IT ACROSS THE BRIDGE\"?"
          tei_id: null
          table_ref: null
        reason: The DV is agreement with a third-person knowledge ascription.
      evidence_reliability:
        provenance:
          page: 15
          quote: "He radios ahead to find out whether other trucks \r\nhave made it across. He is told that the other two\
            \ trucks in the caravan made it over safely."
          tei_id: null
          table_ref: null
        reason: simple induction
    contrast:
      group_high: Bridge_high
      group_low: Bridge_low
      sign_convention: d = mean(low) - mean(high)
      other_notes: Outcome is agreement with the knowledge statement; higher scores indicate more agreement.
    groups:
    - group_id: Bridge_low
      label: null
      n: 28
      mean: 2.32
      sd: 1.16
      se: null
      provenance:
        page: 17
        quote: Bridge (Likert 0–4) N  28, m  2.32, sd  1.16
        tei_id: null
        table_ref: Table 1.1
    - group_id: Bridge_high
      label: null
      n: 31
      mean: 1.71
      sd: 1.13
      se: null
      provenance:
        page: 17
        quote: Bridge (Likert 0–4) N  31, m  1.71, sd  1.13
        tei_id: null
        table_ref: Table 1.1
    reported_test:
      test: t
      t: 2.053
      df1: 57.0
      reported_d: 0.53
      notes: p-value not reported in the extracted text for this t-test.
      provenance:
        page: 17
        quote: Bridge vignettes t(57)  2.053, d  0.53 (medium effect size)
    effect_size:
      metric: SMD
      d: 0.53307299757469
      v: 0.0704650416404434
      computed_from: groups
      needs_review: false
      notes: Computed from Table 1.1 group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups). Appendix material
        located in out/external/pinillos IRI paper with shawn october 2014.pdf; Bridge vignette/prompt reviewed.
    quality_flags: []
    notes: null
  notes: null
- study_id: 6
  label: Modal-reading test (Typo; evidence-seeking; Knows vs Hopes)
  language: English
  language_other: null
  objective: Test whether stakes effects on evidence-seeking prompts can be explained by a ‘modal reading’ by presenting Knows
    and Hopes prompts side-by-side; includes a stakes contrast for the Knows question.
  sample:
    n_final: 70
    recruitment: mTurk
    recruitment_other: null
    compensation: money
    compensation_other: Assumed monetary compensation; amount not reported for Study 6.
    characteristics: Amazon Turk workers in the United States assumed by continuity with the surrounding Pinillos & Simpson
      2014 mTurk studies; Study 6 itself does not explicitly report participant recruitment or compensation. Stakes manipulated
      via low vs high Typo vignette; Knows/Hopes prompts asked.
    mean_age: null
    provenance:
      page: 26
      quote: The mean for the Knows low-stakes response was 3.31 (N  39, SD  0.86). The mean for the Knows high-stakes response
        was 4.42 (N  31, SD  1.36).
  design: Between-Subjects
  design_other: 'Mixed: stakes manipulated between-subjects (low vs high Typo vignette); Knows vs Hopes prompts asked to the
    same participants (order manipulated).'
  manipulated_factors:
  - 'Question type: Knows vs Hopes (within-subjects)'
  - Question order (between-subjects)
  paradigm: Rating how much evidence is needed for knowledge
  paradigm_other: null
  scale:
    label: numeric/text input
    points: null
    anchors: 'Numeric free response: number of proofreads required before the agent knows; whole number.'
    direction: Higher numbers indicate more evidence needed for knowledge.
    provenance:
      page: 22
      quote: “How many times do you think Peter has to proofread his paper before he knows that there are no typos? times.”
  measures:
    knowledge_question_text: How many times do you think Peter has to proofread his paper before he knows that there are no
      typos?
    knowledge_question_first: null
    additional_question_text: How many times do you think Peter has to proofread his paper before he hopes that there are
      no typos?
  scenarios:
  - scenario_code: typos
    scenario_type: Proofreading for typos; stakes vary with consequences of a typo.
    high_stakes_text: '(Typo-High): John, a good college student has just finished writing a two-page paper for an English
      class. The paper is due tomorrow. Even though John is a pretty good speller, he has a dictionary with him that he can
      use to check and make sure there are no typos. There is a lot at stake. The teacher is a stickler and guarantees that
      no one will get an A for the paper if it has a typo. He demands perfection. John, however, finds himself in an unusual
      circumstance. He needs an A for this paper to get an A in the class. And he needs an A in the class to keep his scholarship.
      Without the scholarship, he can’t stay in school. Leaving college would be devastating for John and his family who have
      sacrificed a lot to help John through school. So it turns out that it is extremely important for John that there are
      no typos in this paper. And he is well aware of this.'
    low_stakes_text: '(Typo-Low): Peter, a good college student has just finished writing a two-page paper for an English
      class. The paper is due tomorrow. Even though Peter is a pretty good speller, he has a dictionary with him that he can
      use to check and make sure there are no typos. But very little is at stake. The teacher is just asking for a rough draft
      and it won’t matter if there are a few typos. Nonetheless Peter would like to have no typos at all.'
    provenance:
      page: 22
      quote: To test Buckwalter and Schaffer's hypothesis, we ran an experiment where we presented a set of subjects with
        the low-stakes Typo vignette and another set, the high-stakes Typo vignette.
  effects:
  - effect_id: s6_e1
    subgroup: Typo — evidence-seeking knowledge (Knows question)
    subgroup_desc: Number of proofreads required for knowledge
    design: Between-Subjects
    design_other: null
    moderators:
      scenario: typos
      skeptical_pressure: 'No'
      awareness: 'Yes'
      evidence: First Person
      attribution_person: Other
      evidence_reliability: Medium
    moderators_coding:
      scenario:
        provenance:
          page: 22
          quote: low stakes Typo vignette and another set, the high stakes Typo vignette
          tei_id: null
          table_ref: null
        reason: The Study 6 text says the experiment reused the low- and high-stakes Typo vignettes; full wording is taken
          from the local Pinillos 2012 extraction.
      skeptical_pressure:
        provenance:
          page: 22
          quote: How many times do you think Peter has to proofread his paper before he knows that there are no typos?
          tei_id: null
          table_ref: null
        reason: No explicit skeptical challenge/alternative is presented; the manipulation concerns consequences of error.
      awareness:
        provenance:
          page: 8
          quote: And he is well aware of this.
          tei_id: null
          table_ref: null
        reason: The reused Pinillos 2012 Typo-High vignette explicitly states that the protagonist is well aware of the high
          stakes; Study 6 gives no indication that it used the ignorant high-stakes variant.
      evidence:
        provenance:
          page: 8
          quote: Even though Peter is a pretty good speller, he has a dictionary with him that he can use to check and make
            sure there are no typos.
          tei_id: null
          table_ref: null
        reason: Evidence is generated by the agent’s own proofreading/checking with a dictionary (first-person evidence);
          full wording is taken from the local Pinillos 2012 extraction.
      attribution_person:
        provenance:
          page: 22
          quote: before he knows that there are no typos
          tei_id: null
          table_ref: null
        reason: Participants attribute knowledge to Peter (third-person attribution).
      evidence_reliability:
        provenance:
          page: 8
          quote: pretty good speller... has a dictionary with him that he can use to check and make sure there are no typos
          tei_id: null
          table_ref: null
        reason: The reused Pinillos 2012 Typo vignette describes a good speller with a dictionary, but the evidence-seeking
          task asks how many proofreads are required, so reliability remains coded Medium as in the Pinillos 2012 extraction.
    contrast:
      group_high: Typo_high
      group_low: Typo_low
      sign_convention: d = mean(low) - mean(high)
      other_notes: Outcome is number of proofreads required; higher scores indicate more evidence needed for knowledge.
    groups:
    - group_id: Typo_low
      label: null
      n: 39
      mean: 3.31
      sd: 0.86
      se: null
      provenance:
        page: 26
        quote: The mean for the Knows low-stakes response was 3.31 (N  39, SD  0.86).
        tei_id: null
        table_ref: null
    - group_id: Typo_high
      label: null
      n: 31
      mean: 4.42
      sd: 1.36
      se: null
      provenance:
        page: 26
        quote: The mean for the Knows high-stakes response was 4.42 (N  31, SD  1.36).
        tei_id: null
        table_ref: null
    reported_test:
      test: t
      t: 3.95
      df1: 48.35
      notes: Reported as p < 0.01.
      provenance:
        page: 26
        quote: 'The difference was statistically significant: t(48.35)  3.95, p  0.01.'
    effect_size:
      metric: SMD
      d: -1.0011358164739
      v: 0.0652687440029404
      computed_from: groups
      needs_review: false
      notes: Computed from group means/SDs/Ns in analysis/effect_sizes.qmd (method=between_groups). Review resolved by using
        the local Pinillos 2012 extraction for the reused Typo vignette wording; participant recruitment/compensation coded
        as mTurk/money by continuity with the surrounding Pinillos & Simpson 2014 studies.
    quality_flags: []
    notes: Study 6 says it presented the low-stakes and high-stakes Typo vignettes. Full Typo wording is not in the located
      Pinillos & Simpson appendix; it is taken from the local Pinillos 2012 extraction. There is no indication that Study 6
      used the ignorant high-stakes variant.
  notes: Full Typo vignette wording not provided in the located Pinillos & Simpson appendix; coded from the local Pinillos
    2012 extraction because Study 6 explicitly reused the low-stakes and high-stakes Typo vignettes. Recruitment/compensation
    coded as mTurk/money by continuity with the surrounding Pinillos & Simpson 2014 studies; amount not reported.
