Abstract

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking.

Highlights

  • Misinformation, defined as information initially presented as true that is later found to be false (Lewandowsky et al 2012), is a societal issue of growing concern

  • We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims

  • Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science

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Summary

Introduction

Misinformation, defined as information initially presented as true that is later found to be false (Lewandowsky et al 2012), is a societal issue of growing concern. Inoculation theory provides a framework for helping people develop immunity to persuasive misinformation (McGuire and Papageorgis 1961). This approach applies the concept of vaccination to knowledge—it is possible to build resistance to misinformation by exposing people to a weak form of the misinformation. We examine a different approach to pre-emptively refuting climate denial misinformation using critical thinking techniques—one that focuses on understanding the logical structure of denialist arguments rather than the truth claims they consist of. Reasonbased inoculation is consistent with Compton (2005), who argued that Aristotelian rationality offers a useful framework for inoculating refutations This approach has been tested experimentally, with an inoculation explaining a misleading technique without including competing factual information demonstrating success in neutralizing the influence of the misinformation (Cook et al 2017). This paper introduces key critical thinking concepts and outlines a straightforward process for identifying reasoning errors that allows for people who lack expertise in climate science to confidently reject certain denialist arguments

Understanding arguments
Conclusion changed?
Definitive and provisional claims
Evaluating denialist claims as arguments
Identification of claim
Construction of argument
Determine inferential intent
Check for validity
Identify hidden premises
Check for ambiguity
Check premises for truth or plausibility
Findings
Discussion
Full Text
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