G2TT
来源类型Report
规范类型报告
DOIhttps://doi.org/10.7249/RR-A112-17
来源IDRR-A112-17
Individual Differences in Resistance to Truth Decay: Exploring the Role of Reasoning and Cognitive Biases
Luke J. Matthews; Andrew M. Parker; Katherine Grace Carman; Rose Kerber; Jennifer Kavanagh
发表日期2022-03-29
出版年2022
语种英语
结论
  • The most consistent finding across models was that greater numerical and scientific reasoning and lower magical reasoning were associated with greater resistance to Truth Decay.
  • No strong or consistent associations were found between resistance/susceptibility to Truth Decay and well-known cognitive biases (for example, availability bias, unjustified confidence). Rather, the greatest predictors for resistance/susceptibility to Truth Decay were reasoning processes that are developed over an individual's lifetime and are all at least somewhat adaptive within their proper context.
  • A concerning finding across models was that self-reported non-White respondents were consistently more susceptible to Truth Decay. Although race was not always significant, it often was significant even after controlling for other variables, such as education, political party, and biases or reasoning processes. This finding potentially reflects distrust of traditional sources of factual information among groups that have, at times, been systematically persecuted by societal institutions for government, medicine, and science.
  • The models also highlight how perceptions of key issues, worldviews, and even ways of processing information in the United States are now split according to partisanship and religiosity. Controlling for these variables in a multiple regression often eliminated the significance of many of the reasoning processes and biases seen in bivariate correlations.
摘要

In this report, the authors address one of Truth Decay's proposed drivers: characteristics of human cognitive processing, such as cognitive biases. The authors describe development of a survey measure that they used to examine characteristics of human cognitive processing (such as cognitive biases) and assess the results for individuals' resistance or susceptibility to Truth Decay. The authors focused on six Truth Decay measures: endorsement of scientific consensus, endorsement of verifiable facts, rejection of false conspiracy theories, distinguishing fact from opinion, willingness to accept expert recommendations, and philosophical positivism versus skepticism. The survey used six measures of cognitive biases and reasoning: numeracy, scientific reasoning, magical reasoning, availability bias, unjustified confidence, and ingroup bias.

,

Generally speaking, greater resistance to Truth Decay on each of the six scales was predicted by greater numeracy, greater scientific reasoning, and less magical reasoning. Among the cognitive biases, greater availability bias was associated with greater susceptibility to false conspiracy theories but also greater trust in experts. Greater unjustified confidence by individuals in their own knowledge was associated with greater trust in experts. Ingroup bias was at times associated with greater susceptibility to Truth Decay (lower endorsement of scientific consensus and verifiable fact, lower philosophical positivism) and at other times associated with greater resistance to Truth Decay (rejecting false conspiracy theories, distinguishing fact from opinion). In terms of demographics, resistance to Truth Decay was most consistently associated with those who had a higher income, those who were White, and those who voted for Hillary Clinton in 2016.

目录
  • Chapter One

    Introduction

  • Chapter Two

    Identifying Indicators of Individual Resistance/Susceptibility to Truth Decay

  • Chapter Three

    Identifying Reasoning Processes and Cognitive Biases Relevant to Resistance/Susceptibility to Truth Decay

  • Chapter Four

    Survey Administration and Analytic Approach

  • Chapter Five

    Results

  • Chapter Six

    Discussion

  • Appendix A

    Survey Questions

  • Appendix B

    Scale Characteristics

  • Appendix C

    Methods

主题Civic Education ; Communities ; Survey Research Methodology ; United States
URLhttps://www.rand.org/pubs/research_reports/RRA112-17.html
来源智库RAND Corporation (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/524753
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Luke J. Matthews,Andrew M. Parker,Katherine Grace Carman,et al. Individual Differences in Resistance to Truth Decay: Exploring the Role of Reasoning and Cognitive Biases. 2022.
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