Bibliographic Information
Creator: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer
Contributor: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer
Funding: German Research Foundation (DFG) within the Research Training Group 1712 “Trust and Communication in a Digitized World”
Title: Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI): Three Datasets.
Year of Publication: 2015
Citation: Hendriks, F., Kienhues, D., & Bromme, R. (2015). Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI): Three Datasets. [Translated Title] (Version 1.0.0) [Data and Documentation]. Trier: Center for Research Data in Psychology: PsychData of the Leibniz Institute for Psychology ZPID. https://doi.org/10.5160/psychdata.hsfe15mu08
Abstract
Given their lack of background knowledge, laypeople require expert help when dealing with scientific information. To decide whose help is dependable, laypeople must judge an expert’s epistemic trustworthiness in terms of competence, adherence to scientific standards, and good intentions. Online, this may be difficult due to the often limited and sometimes unreliable source information available. To measure laypeople’s evaluations of experts (encountered online), we constructed an inventory to assess epistemic trustworthiness on the dimensions expertise, integrity, and benevolence. Exploratory (n = 237) and confirmatory factor analyses (n = 345) showed that the Muenster Epistemic Trustworthiness Inventory (METI) is composed of these three factors. A subsequent experimental study (n = 137) showed that all three dimensions of the METI are sensitive to variation in source characteristics. We propose using this inventory to measure assignments of epistemic trustworthiness, that is, all judgments laypeople make when deciding whether to place epistemic trust in – and defer to – an expert in order to solve a scientific informational problem that is beyond their understanding.
Codebook
Codebook_hsfe15mu08_hendricks_kb1
| Position | Name | Label | Valid_values | Missing_values |
|---|---|---|---|---|
| 1 | SUBJECT_ID | subject ID | 1-237 "identification number" | -777 "missing value" |
| 2 | DURATION | Time to complete survey | 128-50797 "seconds" | -1 "missing value due to interrupted participation" |
| 3 | AGE | Age | 19-47 "years" | 9 "missing value" |
| 4 | GENDER | Gender | 1 "male" 2 "female" | -77 "missing value" |
| 5 | EDUCATION | Highest education degree | 1 "no degree" 2 "9 years in German education" 3 "10 years in German education" 4 "qualification for college entry" 5 "qualification for university entry" 6 "university or college degree" 7 "vocational training" | -77 "missing value" |
| 6 | V_1 | Rating of the scientific expert: Competence | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 7 | V_2 | Rating of the scientific expert: Intelligence | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 8 | V_3 | Rating of the scientific expert: Education | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 9 | V_4 | Rating of the scientific expert: Professionalism | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unprofessional" | -77 "missing value" |
| 10 | V_5 | Rating of the scientific expert: Experience | 1 "experienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexperienced" | -77 "missing value" |
| 11 | V_6 | Rating of the scientific expert: Qualification | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 12 | V_7 | Rating of the scientific expert: Reliability | 1 "reliable" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unreliable" | -77 "missing value" |
| 13 | V_8 | Rating of the scientific expert: Sincereness | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 14 | V_9 | Rating of the scientific expert: Honesty | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 15 | V_10 | Rating of the scientific expert: Morality | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 16 | V_11 | Rating of the scientific expert: Ethical | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 17 | V_12 | Rating of the scientific expert: Impartiality | 1 "impartial" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "partial" | -77 "missing value" |
| 18 | V_13 | Rating of the scientific expert: Responsibility | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresponsible" | -77 "missing value" |
| 19 | V_14 | Rating of the scientific expert: Justice | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "injust" | -77 "missing value" |
| 20 | V_15 | Rating of the scientific expert: Selfishness | 1 "unselfish" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "selfish" | -77 "missing value" |
| 21 | V_16 | Rating of the scientific expert: Considerateness | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 22 | V_17 | Rating of the scientific expert: Helpfulness | 1 "helpful" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unhelpful" | -77 "missing value" |
| 23 | V_18 | Rating of the scientific expert: Fairness | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 24 | EXPERTISE_MEAN | Mean expertise (derived variable) | 1-7 "expertise-no expertise" | 9 "missing value" |
| 25 | INTEGRITY_MEAN | Mean integrity (derived variable) | 1-7 "integrity-no integrity" | 9 "missing value" |
| 26 | BENEVOLENCE_MEAN | Mean benevolence (derived variable) | 1-7 "benevolence-no benevolence" | 9 "missing value" |
Codebook_hsfe15mu08_hendricks_kb2
| Position | Name | Label | Valid_values | Missing_values |
|---|---|---|---|---|
| 2 | DURATION | time to complete survey | 182-10089 "seconds" | -1 "missing value due to interrupted participation" |
| 3 | AGE | Age | 18-50 "years" | -77 "missing value" |
| 4 | GENDER | Gender | 1 "male" 2 "female" | -77 "missing value" |
| 5 | EDUCATION | Highest educational degree | 1 "no degree" 2 "9 years in German education" 3 "10 years in German education" 4 "qualification for college entry" 5 "qualification for university entry" 6 "university or college degree" 7 "vocational training" | -77 "missing value" |
| 6 | E_1 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 7 | E_2 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 8 | E_3 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 9 | E_4 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 10 | E_5 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 5 | 1 "expierienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexpierienced" | -77 "missing value" |
| 11 | E_6 | Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 12 | I_1 | Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 13 | I_2 | Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 14 | W_1 | Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 15 | W_2 | Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 16 | W_3 | Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresponsible" | -77 "missing value" |
| 17 | I_3 | Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "injust" | -77 "missing value" |
| 18 | I_4 | Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 4 | 1 "unselfish" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "selfish" | -77 "missing value" |
| 19 | W_4 | Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 20 | E_7 | hilfreich - hinderlich | 1 "helpful" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unhelpful" | -77 "missing value" |
| 21 | I_5 | Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 22 | EXPERTISE_MEAN | Mean expertise (derived variable) | 1-7 "expertise-no expertise" | 9 "missing value" |
| 23 | INTEGRITY_MEAN | Mean integrity (derived variable) | 1-7 "integrity-no integrity" | 9 "missing value" |
| 24 | BENEVOLENCE_MEAN | Mean benevolence (derived variable) | 1-7 "benevolence-no benevolence" | 9 "missing value" |
| 1 | SUBJECT_ID | subject ID | 1-345 "identification number" | -777 "missing value" |
Codebook_hsfe15mu08_hendricks_kb3
| Position | Name | Label | Valid_values | Missing_values |
|---|---|---|---|---|
| 63 | E_2_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 2 | CONSENT | Consent | 1 "yes" 2 "no" | -77 "missing value" |
| 3 | AGE | Age | 19-53 "years" | -77 "missing value" |
| 4 | GENDER | Gender | 1 "male" 2 "female" | -77 "missing value" |
| 5 | EDUCATION | Highest education degree | 1 "no degree" 2 " 9 years in German education" 3 "10 years in German education" 4 "qualification for college entry" 5 "qualification for university entry" 6 " university or college degree" 7 " vocational training" | -77 "missing value" |
| 6 | E_1_EXPERTISELOW | Experimental condition: Low expertise. Muenster Epistemic Trustworthiness Inventory (METI): Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 7 | E_2_EXPERTISELOW | Experimental condition: Low expertise. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 8 | E_3_EXPERTISELOW | Experimental condition: Low expertise. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 9 | E_4_EXPERTISELOW | Experimental condition: Low expertise. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 10 | E_5_EXPERTISELOW | Experimental condition: Low expertise. METI: Expertise, Item 5 | 1 "experienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexperienced" | -77 "missing value" |
| 11 | E_6_EXPERTISELOW | Experimental condition: Low expertise. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 12 | I_1_EXPERTISELOW | Experimental condition: Low expertise. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 13 | I_2_EXPERTISELOW | Experimental condition: Low expertise. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 14 | W_1_EXPERTISELOW | Experimental condition: Low expertise. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 15 | W_2_EXPERTISELOW | Experimental condition: Low expertise. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 16 | W_3_EXPERTISELOW | Experimental condition: Low expertise. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 17 | I_3_EXPERTISELOW | Experimental condition: Low expertise. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 18 | W_4_EXPERTISELOW | Experimental condition: Low expertise. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 19 | I_5_EXPERTISELOW | Experimental condition: Low expertise. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 20 | E_1_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 21 | E_2_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 22 | E_3_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 23 | E_4_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 24 | E_5_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 5 | 1 "expierienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexpierienced" | -77 "missing value" |
| 25 | E_6_EXPERTISEHIGH | Experimental condition: High expertise. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 26 | I_1_EXPERTISEHIGH | Experimental condition: High expertise. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 27 | I_2_EXPERTISEHIGH | Experimental condition: High expertise. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 28 | W_1_EXPERTISEHIGH | Experimental condition: High expertise. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 29 | W_2_EXPERTISEHIGH | Experimental condition: High expertise. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 30 | W_3_EXPERTISEHIGH | Experimental condition: High expertise. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 31 | I_3_EXPERTISEHIGH | Experimental condition: High expertise. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 32 | W_4_EXPERTISEHIGH | Experimental condition: High expertise. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 33 | I_5_EXPERTISEHIGH | Experimental condition: High expertise. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 34 | E_1_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 35 | E_2_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 36 | E_3_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 37 | E_4_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 38 | E_5_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Experience, Item 5 | 1 "experienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexperienced" | -77 "missing value" |
| 39 | E_6_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 40 | I_1_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 41 | I_2_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 42 | W_1_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 43 | W_2_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 44 | W_3_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 45 | I_3_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 46 | W_4_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 47 | I_5_INTEGRITYLOW | Experimental condition: Low Integrity. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 48 | E_1_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 49 | E_2_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 50 | E_3_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 51 | E_4_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 52 | E_5_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 5 | 1 "expierienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexpierienced" | -77 "missing value" |
| 53 | E_6_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 54 | I_1_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 55 | I_2_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 56 | W_1_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 57 | W_2_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 58 | W_3_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 59 | I_3_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 60 | W_4_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 61 | I_5_INTEGRITYHIGH | Experimental condition: High Integrity. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 62 | E_1_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 64 | E_3_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 65 | E_4_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 66 | E_5_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 5 | 1 "expierienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexpierienced" | -77 "missing value" |
| 67 | E_6_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 68 | I_1_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 69 | I_2_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 70 | W_1_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 71 | W_2_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 72 | W_3_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 73 | I_3_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 74 | W_4_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 75 | I_5_BENEVOLENCELOW | Experimental condition: Low Benevolence. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 76 | E_1_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 1 | 1 "competent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "incompetent" | -77 "missing value" |
| 77 | E_2_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 2 | 1 "intelligent" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unintelligent" | -77 "missing value" |
| 78 | E_3_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 3 | 1 "well educated" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "poorly educated" | -77 "missing value" |
| 79 | E_4_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 4 | 1 "professional" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "improfessional" | -77 "missing value" |
| 80 | E_5_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 5 | 1 "experienced" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inexperienced" | -77 "missing value" |
| 81 | E_6_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Expertise, Item 6 | 1 "qualified" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unqualified" | -77 "missing value" |
| 82 | I_1_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Integrity, Item 1 | 1 "sincere" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "insincere" | -77 "missing value" |
| 83 | I_2_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Integrity, Item 2 | 1 "honest" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "dishonest" | -77 "missing value" |
| 84 | W_1_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Benevolence, Item 1 | 1 "moral" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "immoral" | -77 "missing value" |
| 85 | W_2_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Benevolence, Item 2 | 1 "ethical" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unethical" | -77 "missing value" |
| 86 | W_3_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Benevolence, Item 3 | 1 "responsible" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "irresposible" | -77 "missing value" |
| 87 | I_3_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Integrity, Item 3 | 1 "just" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unjust" | -77 "missing value" |
| 88 | W_4_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Benevolence, Item 4 | 1 "considerate" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "inconsiderate" | -77 "missing value" |
| 89 | I_5_BENEVOLENCEHIGH | Experimental condition: High Benevolence. METI: Integrity, Item 5 | 1 "fair" 2 "2" 3 "3" 4 "4" 5 "5" 6 "6" 7 "unfair" | -77 "missing value" |
| 90 | E1U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 91 | E2U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 92 | E3U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 93 | E4U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 94 | E5U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 95 | E6U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 96 | I1U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 97 | I2U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 98 | W1U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 99 | W2U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 100 | W3U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 101 | I3U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 102 | W4U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 103 | I5U_EXPERTISELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 3,0-7,0 "" | 9 "missing value" |
| 104 | E1U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 105 | E2U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 106 | E3U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 107 | E4U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 108 | E5U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 109 | E6U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 110 | I1U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 111 | I2U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 3,0-7,0 "" | 9 "missing value" |
| 112 | W1U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 113 | W2U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 114 | W3U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 115 | I3U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 116 | W4U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 117 | I5U_EXPERTISEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 118 | E1U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 119 | E2U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 120 | E3U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 121 | E4U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 122 | E5U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 123 | E6U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 124 | I1U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 125 | I2U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 126 | W1U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 127 | W2U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 128 | W3U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 129 | I3U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 130 | W4U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 131 | I5U_INTEGRITYLOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 132 | E1U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 133 | E2U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 134 | E3U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 135 | E4U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 136 | E5U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 137 | E6U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 138 | I1U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 139 | I2U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 140 | W1U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 141 | W2U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 142 | W3U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 143 | I3U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 144 | W4U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 145 | I5U_INTEGRITYHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 146 | E1U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 147 | E2U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 148 | E3U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 149 | E4U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 150 | E5U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 151 | E6U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 152 | I1U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 153 | I2U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 154 | W1U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 155 | W2U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 156 | W3U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 157 | I3U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 158 | W4U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 159 | I5U_BENEVOLENCELOW | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-6,0 "" | 9 "missing value" |
| 160 | E1U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "incompetent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "competent" | 9 "missing value" |
| 161 | E2U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1 "unintelligent" 2 "" 3 "" 4 "" 5 "" 6 "" 7 "intelligent" | 9 "missing value" |
| 162 | E3U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 3,0-7,0 "" | 9 "missing value" |
| 163 | E4U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 164 | E5U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 165 | E6U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 166 | I1U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 167 | I2U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 168 | W1U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 169 | W2U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 1,0-7,0 "" | 9 "missing value" |
| 170 | W3U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 171 | I3U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 172 | W4U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 2,0-7,0 "" | 9 "missing value" |
| 173 | I5U_BENEVOLENCEHIGH | recoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable) | 4,0-7,0 "" | 9 "missing value" |
| 174 | EXPERTISE_EXPERTISELOW | Mean expertise in condition expertise low (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 175 | INTEGRITY_EXPERTISELOW | Mean integrity in condition expertise low (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 176 | BENEVOLENCE_EXPERTISELOW | Mean benevolence in condition expertise low (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 177 | EXPERTISE_EXPERTISEHIGH | Mean expertise in condition expertise high (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 178 | INTEGRITY_EXPERTISEHIGH | Mean integrity in condition expertise high (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 179 | BENEVOLENCE_EXPERTISEHIGH | Mean benevolence in condition expertise high (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 180 | EXPERTISE_INTEGRITYLOW | Mean expertise in condition integrity low (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 181 | INTEGRITY_INTEGRITYLOW | Mean integrity in condition integrity low (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 182 | BENEVOLENCE_INTEGRITYLOW | Mean benevolence in condition integrity low (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 183 | EXPERTISE_INTEGRITYHIGH | Mean expertise in condition integrity high (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 184 | INTEGRITY_INTEGRITYHIGH | Mean integrity in condition integrity high (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 185 | BENEVOLENCE_INTEGRITYHIGH | Mean benevolence in condition integrity high (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 186 | EXPERTISE_BENEVOLENCELOW | Mean expertise in condition benevolence low (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 187 | INTEGRITY_BENEVOLENCELOW | Mean integrity in condition benevolence low (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 188 | BENEVOLENCE_BENEVOLENCELOW | Mean benevolence in condition benevolence low (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 189 | EXPERTISE_BENEVOLENCEHIGH | Mean expertise in condition benevolence high (derived variable) | 1-7 "no expertise-expertise" | 9 "missing value" |
| 190 | INTEGRITY_BENEVOLENCEHIGH | Mean integrity in condition benevolence high (derived variable) | 1-7 "no integrity-integrity" | 9 "missing value" |
| 191 | BENEVOLENCE_BENEVOLENCEHIGH | Mean benevolence in condition benevolence high (derived variable) | 1-7 "no benevolence-benevolence" | 9 "missing value" |
| 1 | SUBJECT_ID | subject ID | 1-137 "identification number" | -777 "missing value" |
Study Description
Research Questions/Hypotheses:
1. Epistemic trustworthiness can be differentiated in the three dimensions expertise, integrity and benevolence.
2. These dimensions are separable, though to some extent correlated.
Research Design: Research Instrument; repeated measurements
Measurement Instruments/Apparatus:
Study 1: Participants received 18 semantic opposites to rate a scientific expert on Likert scales ranging from 1 (e.g. professional) to 7 (e.g., unprofessional).
Exploratory factor analysis revealed three factors – “expertise”, “integrity” and “benevolence” – explaining 61.66% of the total variance.
Study 2: The constructed Muenster Epistemic Trustworthiness Inventory (METI) was reduced to 16 items. To test the three-factor structure of the inventory, a new data set was assessed with confirmatory factor analysis. The results confirmed the three-factor structure.
After elimination of two items, the final version of the METI consists of 14 items. All three factors are related to the comprehensive theoretical construct “epistemic trustworthiness”.
Study 3: The final version of the METI consisting of 14 items was administered in an experimental study. Participants had to rate the epistemic thrustworthiness of six ficticious persons, who were indicated as potential authors of a blog entry. The blog entry was about a study from the field of neurology. Descriptions of authors varied along each of the dimensions of epistemic trustworthiness (low vs. high expertise, low vs. high integrity, low vs. high benevolence). The results indicated that the METI is able to measure epistemic trustworthiness in a differentiated way.
For detailed information see Hendriks, Kienhues & Bromme (2015).
Data Collection Method:
Data collection in the absence of an experimenter
– Online-Survey
Population: Young German graduates
Survey Time Period:
Study 1: August & Septembre 2013
Study 2: January, February & March 2014
Study 3: July & August 2015
Sample: Convenience Sample
Gender Distribution:
Study 1:
75,5% female subjects
24,5% male subjects
Study 2:
69,3% female subjects
30,7% male subjects
Study 3:
75,2% female subjects
24,8% male subjects
Age Distribution: Study 1: 19-47 years; Study 2: 18-50 years; Study 3: 19-53 years
Spatial Coverage (Country/Region/City): Germany
Subject Recruitment:
Study 1: Participants registered in the Bromme research unit’s internal volunteer database were contacted via e-mail containing the link to the online survey. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 200 euro.
Study 2: Participants were recruited in lectures at the University of Muenster. Students interested in participation could leave their email adress for contact. They were contacted via e-mail containing the link to the online survey. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 200 euro.
Study 3: Participants registered in the Bromme research unit’s internal volunteer database were contacted via email containing the link to the online survey. Furthermore, advertisements were posted in a newsletter for students at the University of Muenster and on the German magazine “Psychologie Heute”’s website. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 100 euro.
Sample Size: Study 1: 237 individuals; Study 2: 345 individuals; Study 3: 137 individuals
Return/DropOut:
Study 1: 300 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (79%).
Study 2: 406 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (85%).
Study 3: 243 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (56%).
Literature
Publications Directly Related to the Dataset
| Publications Directly Related to the Dataset |
|---|
| Hendriks, F., Kienhues, D., Bromme, R. (2015). Measuring Laypeople's Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI). PLoS ONE 10(10): e0139309. doi:10.1371/journal.pone.0139309Datensatz 0305481 |
Further Reading
| Further Reading |
|---|
| Bromme, R., & Goldman, S.R. (2014). The public's Bounded Understanding of Science. Educational Psychologist, 49 (2), 59-69. DOI:10.1080/00461520.2014.921572Datensatz 0282214 |
| Bromme, R., Kienhues, D. & Porsch, T. (2010). Who knows what and who can we believe? Epistemological beliefs are beliefs about knowledge (mostly) to be attained from others. In L. D. Bendixen & F. C. Feucht (Eds.), Personal epistemology in the classroom: Theory, research, and implications for practice (pp. 163-193). Cambridge: Cambridge University Press. Datensatz 0232884 |
| Origgi G. (2004). Is trust an epistemological notion? Episteme, 1(1), 61–72. |
| Origgi G. (2014). Epistemic trust. In P. Capet & T. Delavallade (Eds.), Information Evaluation (pp. 35-54). New York: John Wiley & Sons. DOI: 10.1002/9781118899151.ch2 |
| Sinatra, G. M., Kienhues, D., & Hofer, B. K. (2014). Addressing challenges to public understanding of science: Epistemic cognition, motivated reasoning, and conceptual change. Educational Psychologist, 49 (2), 123-138. DOI: 10.1080/00461520.2014.916216 Datensatz 0282216 |
| Sperber, D., Clément, F., Heintz, C., Mascaro, O., Mercier, H., Origgi, G., & Wilson, D. (2010). Epistemic vigilance. Mind & Language, 25 (4), 359–393. DOI: 10.1111/j.1468-0017.2010.01394.x |