Scholarlink

<p>The public relies on source credibility as a cognitive shortcut when deciding whether to accept or reject science-informed policies. Using data from a subsample of a nationally representative U.S. survey (<i>N</i> = 927), we applied Latent Class Analysis to identify five distinct audience segments based on their perceptions of scientists’ source credibility, defined as competence, integrity, and goodwill. The LCA was replicated across two environmental health contexts: extreme heat and a zoonotic disease associated with foodborne illness. Multiple regression models were also estimated to determine how individuals’ characteristics, such as a priori attitudes about science and scientific institutions, attention to media and interpersonal sources, general social trust/distrust, and sociodemographic variables were associated with perceived scientific source credibility and policy support across both contexts. Enthusiasts were characterized by exceptionally high credibility perceptions, institutional confidence, and policy support with Optimists having similarly high, though context-dependent responses. Moderates had intermediate levels of perceived scientific source credibility and exhibited balanced information-seeking patterns, relying on both technical and personal sources. Skeptics and Estranged groups exhibited lower credibility perceptions and institutional trust than other groups, with the Estranged representing the most disconnected segment. Perceptions of scientific competence were higher across all the segments compared to integrity and goodwill. Regressions revealed strong associations between source credibility, perceived scientific motivations, and institutional confidence in scientists. Class assignments were also strongly associated with optimistic beliefs about science and support for science-informed policies. By recognizing these segments and their context-dependent concerns, scientists can tailor messages to support evidence-informed policymaking.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

There is not one public: divergent perceptions of scientists’ source credibility in the United States

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月2日

查看全文
  • Shumaila J. Bhatti,
  • Dara M. Wald

摘要

The public relies on source credibility as a cognitive shortcut when deciding whether to accept or reject science-informed policies. Using data from a subsample of a nationally representative U.S. survey (N = 927), we applied Latent Class Analysis to identify five distinct audience segments based on their perceptions of scientists’ source credibility, defined as competence, integrity, and goodwill. The LCA was replicated across two environmental health contexts: extreme heat and a zoonotic disease associated with foodborne illness. Multiple regression models were also estimated to determine how individuals’ characteristics, such as a priori attitudes about science and scientific institutions, attention to media and interpersonal sources, general social trust/distrust, and sociodemographic variables were associated with perceived scientific source credibility and policy support across both contexts. Enthusiasts were characterized by exceptionally high credibility perceptions, institutional confidence, and policy support with Optimists having similarly high, though context-dependent responses. Moderates had intermediate levels of perceived scientific source credibility and exhibited balanced information-seeking patterns, relying on both technical and personal sources. Skeptics and Estranged groups exhibited lower credibility perceptions and institutional trust than other groups, with the Estranged representing the most disconnected segment. Perceptions of scientific competence were higher across all the segments compared to integrity and goodwill. Regressions revealed strong associations between source credibility, perceived scientific motivations, and institutional confidence in scientists. Class assignments were also strongly associated with optimistic beliefs about science and support for science-informed policies. By recognizing these segments and their context-dependent concerns, scientists can tailor messages to support evidence-informed policymaking.