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Self-assessed understanding of climate change

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Abstract

Survey researchers often treat self-assessed understanding of climate change as a rough proxy for knowledge, which might affect what people believe about this topic. Self-assessments can be unrealistically high, however, and correlated with politics, so they deserve study in their own right. Turning the usual perspective around to view self-assessed understanding as dependent variable, problematically related to actual knowledge, casts self-assessments in a new light. Analysis of a 2016 US survey that carried a five-item test of very basic, belief-neutral but climate-relevant knowledge (such as knowing about the location of North and South Poles) finds that, at any given level of knowledge, people saying they “understand a great deal” about climate change are more likely to be older, college-educated, and male. Self-assessed understanding exhibits a U-shaped political pattern: highest among liberals and the most conservative, but lowest among moderate conservatives. Among liberal and middle-of-the-road respondents, self-assessed understanding of climate change is positively related to knowledge. Among the most conservative, however, understanding is unrelated or even negatively related to knowledge. For that group in particular, high self-assessed understanding reflects confidence in political views, rather than knowledge about the physical world.

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Notes

  1. Weights take into account the regional population; number of adults and telephone numbers within households; and respondent age, sex, and race. Response rates in the August and November/December stages of the POLES survey were 27–30% for Alaska, and 15–24% for the other 49 states, as calculated by AAPOR 2016 definition 4.

  2. Similar U-shaped relationships between political identity and high self-assessed understanding of climate change can also be found in many other national or regional survey datasets including those described by Hamilton (2012), Hamilton and Saito (2015), or Hamilton et al. (2016a, 2018a, 2018b). In each of these datasets as in Figure 1d, non-Tea Party Republicans or moderate conservatives express the least confidence in their understanding of climate change.

  3. Principal components analysis (not shown) confirms that these five items load on the first component with roughly similar weights, so a coefficient-weighted knowledge index behaves no differently (r = 0.996) from the simple additive index.

  4. For straightforward interpretation in terms of overconfidence, understanding is here coded as 1 for “a great deal” and 0 otherwise. Alternative specifications using ordinal codes (understanding coded from 1 “nothing” to 4 “a great deal”), estimated by probability-weighted ordered logit regression, yield generally similar conclusions. In the ordinal versions of models 1 and 3, the same predictors have significant effects, with the same signs, as their counterparts in Table 2. The knowledge × party or knowledge × ideology interaction terms are, if anything, slightly stronger in these two ordinal versions. In the ordinal version of model 2, the education effect is stronger but the knowledge × ideology interaction slightly weaker, falling short of statistical significance (p = 0.09), although with the same sign. Otherwise, the significance as well as signs of coefficients are the same for ordinal and dichotomous versions of model 2.

  5. Nor are there significant election × party or election × ideology interactions, which were tested in alternative versions of models 1 and 2 (not shown). Previous analyses looking at different variables on the POLES surveys likewise found little difference between pre- and post-election responses (Hamilton 2017, 2018b).

  6. Because party and ideology interact with knowledge, their main effects in Table 2 describe the effect of party or ideology when knowledge = 0, that is, when no questions are answered correctly.

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Acknowledgments

Additional climate questions on the Granite State Poll have been supported by the Carsey School of Public Policy and the Sustainability Institute at the University of New Hampshire. Any opinions, findings, conclusions, or recommendations in this paper are those of the author, and do not necessarily represent the views of the National Science Foundation or other supporting organizations.

Funding

The POLES survey and polar questions on the Granite State Poll were supported through the PoLAR Partnership grant from the National Science Foundation (DUE-1239783).

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Correspondence to Lawrence C. Hamilton.

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Hamilton, L.C. Self-assessed understanding of climate change. Climatic Change 151, 349–362 (2018). https://doi.org/10.1007/s10584-018-2305-0

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  • DOI: https://doi.org/10.1007/s10584-018-2305-0

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