Bibliografische Informationen
Ersteller: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer
Mitwirkende: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer
Förderung: Deutsche Forschungsgemeinschaft (DFG): Graduiertenkolleg 1712 „Vertrauen und Kommunikation in einer digitalisierten Welt“
Titel: Wie sich das von Laien in Experten gesetzte Vertrauen im digitalen Zeitalter messen lässt: „The Muenster Epistemic Trustworthiness Inventory (METI)“: Drei Forschungsdatensätze.
Jahr der Publikation: 2015
Zitation: Hendriks, F., Kienhues, D., & Bromme, R. (2015). Wie sich das von Laien in Experten gesetzte Vertrauen im digitalen Zeitalter messen lässt: „The Muenster Epistemic Trustworthiness Inventory (METI)“: Drei Forschungsdatensätze. (Version 1.0.0) [Daten und Dokumentation]. Trier: Forschungsdatenzentrum des Leibniz Institut für Psychologie ZPID. https://doi.org/10.5160/psychdata.hsfe15mu08
Zusammenfassung
Aufgrund ihres fehlenden Hintergrundwissens benötigen Laien die Hilfe von Experten, wenn sie sich mit wissenschaftlichen Informationen auseinandersetzen. Um zu entscheiden, auf wessen Hilfe sie sich verlassen können, müssen Laien Experten in Bezug auf ihre epistemische Vertrauenswürdigkeit bestehend aus Kompetenz, Einhaltung wissenschaftlicher Standards und guten Absichten einschätzen. Online kann diese Einschätzung schwierig sein, da häufig nur begrenzte und manchmal wenig vertrauenswürdige Informationen zur Verfügung stehen. Um zu messen, wie Experten (in Online-Medien) von Laien beurteilt werden, wurde ein Inventar zur Erfassung epistemischer Vetrauenswürdigkeit mit den Dimensionen Expertise, Integrität und Wohlwollen konstruiert. Sowohl mit explorativer (n=237) wie auch konfirmatorischer Faktorenanalyse (n=345) konnte belegt werden, dass der Muenster Epistemic Trustworthiness Inventory (METI) sich aus diesen drei Faktoren zusammensetzt. In einer anschließenden experimentellen Untersuchung zeigte sich, dass alle drei Dimensionen des METI veränderungssensitiv sind. Die Autoren schlagen daher vor, dieses Inventar zur Messung von epistemischer Vertrauenswürdigkeit einzusetzen; sprich alle Einschätzungen, die Laien vornehmen, um zu entscheiden, ob sie epistemisches Vertrauen in einen Experten setzen und sich nach ihm richten, um ein wissenschaftliches Problem zu erfassen, das sie nicht verstehen.
Kodebuch
Kodebuch_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" |
Kodebuch_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" |
Kodebuch_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" |
Studienbeschreibung
Forschungsfragen/Hypothesen:
1. Epistemisches Vertrauen lässt sich in die Dimensionen Expertise, Integrität und Wohlwollen unterteilen.
2. Diese Dimensionen sind trennbar, wenn auch möglicherweise korreliert.
Forschungsdesign: Forschungsinstrument; mehrmalige Erhebung
Messinstrumente/Apparate:
Studie 1: Die Probanden erhielten 18 Adjektiv-Gegensatzpaare, anhand derer sie einen wissenschaftlichen Experten auf einer Likert-Skala von 1 (z.B. fachmännisch) bis 7 (z.B. unfachmännisch) einschätzen sollten. Eine explorative Faktorenanalyse ergab 3 Faktoren – „Expertise“, „Integrität“ und „Wohlwollen“ – die insgesamt 61,66% der Varianz aufklärten.
Studie 2: Das zu konstruierende Muenster Epistemic Trustworthiness Inventory (METI) wurde auf 16 Items reduziert. Um die drei-dimensionale Struktur des Inventars zu überprüfen, wurde ein neuer Datensatz erhoben und eine konfirmatorische Faktorenanalyse gerechnet. Die Ergebnisse bestätigten die drei-dimensionale Struktur.
Nach Eliminierung von zwei Items besteht die endgültige Version des METI aus 14 Items. Alle drei Faktoren laden auf dem theoretischen Konstrukt „epistemische Vetrauenswürdigkeit“.
Studie 3: Die endgültige Version des METI mit 14 Items wurde in einer experimentellen Untersuchung eingesetzt. Die Teilnehmer sollten 6 fiktive Personen, die potentielle Autoren eines Blog-Eintrags darstellten, bezüglich ihrer epistemischen Vertrauenswürdigkeit einschätzen. Der Blog-Eintrag behandelte eine Untersuchung aus dem Bereich der Neurologie. Die Beschreibungen der Autoren wurden systematisch in den Dimensionen von epistemischer Vertrauenswürdigkeit (low vs. high expertise, low vs. high integrity, low vs. high benevolence) variiert. Die Ergebnisse zeigten, dass es der METI ermöglicht, epistemische Vertrauenswürdigkeit in differenzierter Form zu erfassen.
Für detaillierte Informationen zu den Studien siehe Hendriks, Kienhues & Bromme (2015).
Datenerhebungsmethode:
Erhebung in Abwesenheit eines Versuchsleiters
– Online-Erhebung
Population: Junge deutsche Akademiker
Erhebungszeitraum:
Studie 1: August & September 2013
Studie 2: Januar, Februar & März 2014
Studie 3: Juli & August 2015
Stichprobe: Anfallende Stichprobe
Geschlechtsverteilung:
Studie 1:
75,5% weibliche Probanden
24,5% männliche Probanden
Studie 2:
69,3% weibliche Probanden
30,7% männliche Probanden
Studie 3:
75,2& weibliche Probanden
24,8% männliche Probanden
Altersverteilung: Studie 1: 19 bis 47 Jahre; Studie 2: 18 bis 50 Jahre; Studie 3: 19 bis 53 Jahre
Räumlicher Erfassungsbereich (Land/Region/Stadt): Deutschland
Probandenrekrutierung:
Studie 1: Mitglieder einer Datenbank für Studienteilnahme an Studien der Arbeitseinheit Bromme wurden einmalig per Email kontaktiert, der Link zur Umfrage war darin enthalten. Die Teilnehmerinnen konnten selbstständig über Ort und Zeit der Teilnahme entscheiden. Es wurde eine Verlosung von Amazongutscheinen im Wert von insgesamt 200€ durchgeführt.
Studie 2: In Vorlesungen der Universität Münster wurde um die Emailadressen von Studierenden geworben. Diese wurden daraufhin einmalig per Email kontaktiert, der Link zur Umfrage war darin enthalten. Die Teilnehmerinnen konnten selbstständig über Ort und Zeit der Teilnahme entscheiden.
Es wurde eine Verlosung von Amazongutscheinen im Wert von insgesamt 200€ durchgeführt.
Studie 3: Personen aus einer Datenbank zur Studienteilnahme an der AE Bromme wurden einmalig per Email kontaktiert, der Link zur Umfrage war darin enthalten. Weiterhin wurde über den Studierendennewsletter der Universität Münster sowie die Website von Psychologie Heute geworben. Die Teilnehmerinnen konnten selbstständig über Ort und Zeit der Teilnahme entscheiden.
Es wurde eine Verlosung von Amazongutscheinen im Wert von insgesamt 100€ durchgeführt.
Stichprobengröße: Studie 1: 237 Individuen; Studie 2: 345 Individuen; Studie 3: 137 Individuen
Rücklauf/Ausfall:
Study 1: Der Fragebogen wurde von 300 Personen angeklickt (online). Nur die Daten derjenigen wurden verwendet, die den Fragebogen nicht abbrachen (79%).
Study 2: Der Fragebogen wurde von 406 Personen angeklickt (online). Nur die Daten derjenigen wurden verwendet, die den Fragebogen nicht abbrachen (85%).
Study 3: Der Fragebogen wurde von 243 Personen angeklickt (online). Nur die Daten derjenigen wurden verwendet, die den Fragebogen nicht abbrachen und die nicht weniger als 5.20 min oder mehr als 42.54 min für die Durchführung benötigten (56%).
Literatur
Unmittelbar auf den Datensatz bezogene Veröffentlichungen
| Unmittelbar auf den Datensatz bezogene Veröffentlichungen |
|---|
| 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 |
Weiterführende Literatur
| Weiterführende Literatur |
|---|
| 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 |