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The accuracy of German citizens’ confidence in their climate change knowledge


Accurate confidence—confidence that reflects the accuracy of knowledge—can be relevant for decision-making in areas of high uncertainty. Accuracy of confidence is of particular importance in the area of climate change where scientifically correct information exists alongside misinformation in the public discourse and media. Here we assess the accuracy of confidence in climate change knowledge in a national German sample (n = 509). The accuracy of the confidence of the citizens in their climate change knowledge was only around half of what it could be based on the accuracy of their knowledge. Moreover, the accuracy of confidence controlling for knowledge accuracy was lower for climate change than for two benchmark comparisons: general science knowledge in another national German sample (n = 588), and climate change knowledge in a scientist sample (n = 207). Although these results cannot necessarily be generalized to the population of all indicators of climate change knowledge, the results suggest that the confidence of citizens in their climate change knowledge is unnecessarily fuzzy given their actual knowledge.

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Fig. 1: Calibration curves for confidence judgements.
Fig. 2: Distributions of confidence judgements.
Fig. 3: Relative confidence sensitivity.

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The data that support the plots within this paper and other findings of this study are available at

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  1. Simon, M. & Houghton, S. M. The relationship between overconfidence and the introduction of risky products: evidence from a field study. Acad. Manage. J. 46, 139–149 (2003).

    Google Scholar 

  2. Berner, E. S. & Graber, M. L. Overconfidence as a cause of diagnostic error in medicine. Am. J. Med. 121, S2–S23 (2008).

    Article  Google Scholar 

  3. Johnson, D. D. P. Overconfidence and War (Harvard Univ. Press, 2009).

  4. Shi, J., Visschers, V. H., Siegrist, M. & Arvai, J. Knowledge as a driver of public perceptions about climate change reassessed. Nat. Clim. Change 6, 759–762 (2016).

    Article  Google Scholar 

  5. Sundblad, E.-L., Biel, A. & Gärling, T. Knowledge and confidence in knowledge about climate change among experts, journalists, politicians, and laypersons. Environ. Behav. 41, 281–302 (2009).

    Article  Google Scholar 

  6. Juslin, P., Olsson, N. & Winman, A. Calibration and diagnosticity of confidence in eyewitness identification: comments on what can be inferred from the low confidence–accuracy correlation. J. Exp. Psychol. Learn. Mem. Cogn. 22, 1304–1316 (1996).

    Article  Google Scholar 

  7. Hadar, L., Sood, S. & Fox, C. R. Subjective knowledge in consumer financial decisions. J. Mark. Res. 50, 303–316 (2013).

    Article  Google Scholar 

  8. Meyer, A. N., Payne, V. L., Meeks, D. W., Rao, R. & Singh, H. Physicians’ diagnostic accuracy, confidence, and resource requests: a vignette study. JAMA Intern. Med. 173, 1952–1958 (2013).

    Article  Google Scholar 

  9. Jackson, S. A. & Kleitman, S. Individual differences in decision-making and confidence: capturing decision tendencies in a fictitious medical test. Metacogn. Learn. 9, 25–49 (2014).

    Article  Google Scholar 

  10. Hiles, S. S. & Hinnant, A. Climate change in the newsroom: journalists’ evolving standards of objectivity when covering global warming. Sci. Commun. 36, 428–453 (2014).

    Article  Google Scholar 

  11. Elsasser, S. W. & Dunlap, R. E. Leading voices in the denier choir: conservative columnists’ dismissal of global warming and denigration of climate science. Am. Behav. Sci. 57, 754–776 (2013).

    Article  Google Scholar 

  12. Williamson, P. Take the time and effort to correct misinformation. Nature 540, 171 (2016).

    Article  Google Scholar 

  13. Miller, T. M. & Geraci, L. Training metacognition in the classroom: the influence of incentives and feedback on exam predictions. Metacogn. Learn. 6, 303–314 (2011).

    Article  Google Scholar 

  14. Sanbonmatsu, D. M., Posavac, S. S., Kardes, F. R. & Mantel, S. P. Selective hypothesis testing. Psychon. Bull. Rev. 5, 197–220 (1998).

    Article  Google Scholar 

  15. Park, J., Konana, P., Gu, B., Kumar, A. & Raghunathan, R. Confirmation Bias, Overconfidence, and Investment Performance: Evidence from Stock Message Boards McCombs Research Paper Series No. IROM-07-10 (SSRN, 2010).

  16. Lewandowsky, S., Oberauer, K. & Gignac, G. E. NASA faked the moon landing—therefore, (climate) science is a hoax: an anatomy of the motivated rejection of science. Psychol. Sci. 24, 622–633 (2013).

    Article  Google Scholar 

  17. Fleming, S. M. HMeta-d: hierarchical Bayesian estimation of metacognitive efficiency from confidence ratings. Neurosci. Conscious. 2017, nix007 (2017).

    Article  Google Scholar 

  18. Dienes, Z., Altmann, G., Kwan, L. & Goode, A. Unconscious knowledge of artificial grammars is applied strategically. J. Exp. Psychol. Learn. Mem. Cogn. 21, 1322–1338 (1995).

    Article  Google Scholar 

  19. Burton, R. F. & Miller, D. J. Statistical modelling of multiple-choice and true/false tests: ways of considering, and of reducing, the uncertainties attributable to guessing. Assess. Eval. High. Educ. 24, 399–411 (1999).

    Article  Google Scholar 

  20. Gigerenzer, G., Hoffrage, U. & Kleinbölting, H. Probabilistic mental models: a Brunswikian theory of confidence. Psychol. Rev. 98, 506 (1991).

    Article  CAS  Google Scholar 

  21. Allgood, S. & Walstad, W. B. The effects of perceived and actual financial literacy on financial behaviors. Econ. Inq. 54, 675–697 (2016).

    Article  Google Scholar 

  22. Tenney, E. R., Spellman, B. A. & MacCoun, R. J. The benefits of knowing what you know (and what you don’t): how calibration affects credibility. J. Exp. Soc. Psychol. 44, 1368–1375 (2008).

    Article  Google Scholar 

  23. Baldiga, K. Gender differences in willingness to guess. Manage. Sci. 60, 434–448 (2014).

    Article  Google Scholar 

  24. Science & Engineering Indicators 2018. Science and Techology: Public Attitudes and Understanding Ch. 7 (National Science Board, accessed 24 May 2019);

  25. Weber, N. & Brewer, N. The effect of judgment type and confidence scale on confidence-accuracy calibration in face recognition. J. Appl. Psychol. 88, 490 (2003).

    Article  Google Scholar 

  26. Bornstein, B. H. & Zickafoose, D. J. “I know I know it, I know I saw it”: the stability of the confidence–accuracy relationship across domains. J. Exp. Psychol. Appl. 5, 76–88 (1999).

    Article  Google Scholar 

  27. Overgaard, M. Behavioral Methods in Consciousness Research (Oxford Univ. Press, 2015).

  28. Galvin, S. J., Podd, J. V., Drga, V. & Whitmore, J. Type 2 tasks in the theory of signal detectability: discrimination between correct and incorrect decisions. Psychon. Bull. Rev. 10, 843–876 (2003).

    Article  Google Scholar 

  29. Maniscalco, B. & Lau, H. A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Conscious. Cogn. 21, 422–430 (2012).

    Article  Google Scholar 

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We acknowledge support by the Excellence Initiative, Institutional Strategy ZUK 5.4 (Scientific Computing in the Social and Behavioral Sciences), Heidelberg University, and support of the Heidelberg Center for the Environment, Heidelberg University.

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Authors and Affiliations



H.F., D.A. and N.S. designed the study for the knowledge of climate change in citizens. H.F. designed the study for the knowledge of climate change in scientists and general science knowledge in citizens. H.F. and N.S. analysed the data. H.F. wrote the paper. All authors edited and approved the manuscript.

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Correspondence to Helen Fischer.

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The authors declare no competing interests.

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Peer review information: Nature Climate Change thanks Sander van der Linden and other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Figs. 1, 2, Supplementary Note 1, Supplementary Table 1.

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Fischer, H., Amelung, D. & Said, N. The accuracy of German citizens’ confidence in their climate change knowledge. Nat. Clim. Chang. 9, 776–780 (2019).

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