What are you assessing when you measure "trust" in scientists with a direct measure?

被引:18
作者
Besley, John C. C. [1 ]
Tiffany, Leigh Anne [2 ,3 ,4 ]
机构
[1] Michigan State Univ, 404 Wilson Rd, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Advertising & Publ Relat, E Lansing, MI 48824 USA
[3] Michigan State Univ, Sch Journalism, E Lansing, MI 48824 USA
[4] Michigan State Univ, Environm Sci & Policy Program ESPP, E Lansing, MI 48824 USA
基金
美国食品与农业研究所;
关键词
ability; benevolence; caring; competence; expertise; Gallup; General Social Survey; honesty; integrity; Pew Research Center; secondary data analysis; trust; trustworthiness; warmth; CREDIBILITY;
D O I
10.1177/09636625231161302
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
This article analyzes three publicly available datasets focused on trust in science and scientists. It specifically seeks to understand what direct measures of trust (i.e. questions that directly ask respondents how much they trust scientists) assess in terms of discrete measures of trustworthiness (i.e. perceptions of scientists' ability, integrity, and benevolence). Underlying the analyses is a concern that direct measures of trust are a poor substitute for differentiating between discrete trustworthiness perceptions and behavioral trust in the form of a specific willingness to make oneself vulnerable. The research concludes that it is unclear what direct trust measures are capturing in any given context and suggests that researchers should better use trust-related theory when designing surveys and trust-focused campaigns. The secondary data used come from the General Social Survey, Gallup, and the Pew Research Center.
引用
收藏
页码:709 / 726
页数:18
相关论文
共 34 条
  • [11] Gaining trust as well as respect in communicating to motivated audiences about science topics
    Fiske, Susan T.
    Dupree, Cydney
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2014, 111 : 13593 - 13597
  • [12] Competent and cold: a directed content analysis of warmth and competence dimensions to identify and categorise stereotypes of scientists portrayed in meme-based GIFs
    Fujiwara, Y.
    Velasco, R. C. L.
    Jones, L. K.
    Hite, R. L.
    [J]. INTERNATIONAL JOURNAL OF SCIENCE EDUCATION, 2022, 44 (04) : 694 - 715
  • [13] Funk Cary., 2019, TRUST MISTRUST AMERI
  • [14] Gallup, 2021, WELLC GLOB MON 2020
  • [15] After the flood - Anger, attribution, and the seeking of information
    Griffin, Robert J.
    Yang, Zheng
    ter Hume, Ellen
    Boerner, Francesca
    Ortiz, Sherry
    Dunwoody, Sharon
    [J]. SCIENCE COMMUNICATION, 2008, 29 (03) : 285 - 315
  • [16] Measuring Laypeople's Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI)
    Hendriks, Friederike
    Kienhues, Dorothe
    Bromme, Rainer
    [J]. PLOS ONE, 2015, 10 (10):
  • [17] Making sense of policy choices: understanding the roles of value predispositions, mass media, and cognitive processing in public attitudes toward nanotechnology
    Ho, Shirley S.
    Scheufele, Dietram A.
    Corley, Elizabeth A.
    [J]. JOURNAL OF NANOPARTICLE RESEARCH, 2010, 12 (08) : 2703 - 2715
  • [18] Hon L.C., 1998, J PUBLIC RELAT RES, V10, P103, DOI [10.1207/s1532754xjprr1002_02, https://doi.org/10.1207/s1532754xjprr1002_02, DOI 10.1207/S1532754XJPRR1002_02]
  • [19] The Influence of Source Credibility on Communication Effectiveness
    Hovland, Carl I.
    Weiss, Walter
    [J]. PUBLIC OPINION QUARTERLY, 1951, 15 (04) : 635 - 650
  • [20] The Impact of Perceived Scientific and Social Consensus on Scientific Beliefs
    Kobayashi, Keiichi
    [J]. SCIENCE COMMUNICATION, 2018, 40 (01) : 63 - 88