Motivated numeracy and active reasoning in a Western European sample

Alfano, M. (2019), ‘Nietzsche’s affective perspectivism as a philosophical methodology’, in Nietzsche’s Metaphilosophy, Cambridge University Press.

Cohen, G., Aronson, J. and Steele, C. (2000), ‘When beliefs yield to evidence: Reducing biased evaluation by affirmation of the self’, Personality and Social Psychology Bulletin, 26(9): 1151–64.

Cook, J., Lewandowsky, S. and Ecker, U. K. (2017), ‘Neutralizing misinformation through inoculation: Exposing misleading argumentation techniques reduces their influence’, PLoS ONE, 12(5): e0175799.

Flore, P. and Wicherts, J. (2014), ‘Does stereotype threat influence performance of girls in stereotyped domains? a meta-analysis’, Journal of School Psychology, 53(1): 2544.

Garrett, R. K. (2011), ‘Troubling consequences of online political rumoring’, Human Communication Research, 37(2): 255274.

Holzer, A., Govaerts, S., Bendahan, S. and Gillet, D. (2015), ‘Towards mobile blended interaction fostering critical thinking’, in MobileHCI’15, 735742. ACM.

Holzer, A., Tintarev, N., Bendahan, S., Kocher, B., Greenup, S. and Gillet, D. (2018), ‘Digitally scaffolding debate in the classroom’, in Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems,ACM, LBW054.

Kahan, D. and Peters, E. (2017), ‘Rumors of the ‘nonreplication’ of the ‘motivated numeracy effect’ are greatly exaggerated’, SSRN electronic journal, Yale Law & Economics Research (584).

Kahan, D., Braman, D., Slovic, P., Gastil, J. and Cohen, G. (2005), ‘Cultural cognition of the risks and benefits of nanotechnology’, Nature Nanotechnology, 4:8790.

Kahan, D., Braman, D., Slovic, P. and Mertz, C. (2007), ‘Culture and identity-protective cognition: Explaining the white-male effect in risk perception’, Journal of Empirical Legal Studies, 4(3): 465505.

Kahan, D., Slovic, P., Braman, D. and Gastil, J. (2006), ‘Fear of democracy: A cultural evaluation of sunstein on risk’, Harvard Law Review, 119(4): 10711109.

Kahan, D. M. (2012), ‘Cultural cognition as a conception of the cultural theory of risk’, in Handbook of risk theory, 725759. Springer.

Kahan, D. M., Peters, E., Dawson, E. C. and Slovic, P. (2017), ‘Motivated numeracy and enlightened self-government’, Behavioural Public Policy, 1(1): 5486.

Khanna, K. and Sood, G. (2018), ‘Motivated responding in studies of factual learning’, Political Behavior, 40(1): 79101.

Lewandowsky, S., Ecker, U. K., Seifert, C. M., Schwarz, N. and Cook, J. (2012), ‘Misinformation and its correction continued influence and successful debiasing’, Psychological Science in the Public Interest, 13(3): 106131.

Liberali, J. M., Reyna, V. F., Furlan, S., Stein, L. M. and Pardo, S. T. (2012), ‘Individual differences in numeracy and cognitive reflection, with implications for biases and fallacies in probability judgment’, Journal of behavioral decision making, 25(4): 361381.

Marris, C., Langford, I. H. and O’Riordan, T. (1998), ‘A quantitative test of the cultural theory of risk perceptions: Comparison with the psychometric paradigm’, Risk analysis, 18(5): 635647.

McFadden, D. (1979), ‘Quantitative methods for analysing travel behavior of individuals: Some recent developments’, in Stopher, D. A. H. P. R. (eds), Behavioural travel modelling, London, England: Croom Helm, 279318.

Miller, R. L. and Wozniak, W. (2001), ‘Counter-attitudinal advocacy: Effort vs. self-generation of arguments’, Current Research in Social Psychology, 6(4): 4657.

Nguyen, H., Masthoff, J. and Edwards, P. (2007), ‘Modelling a receiver’s position to persuasive arguments’, Persuasive Technology, pages 271282.

Nurse, M. and Grant, W. (2019), ‘Numeracy in perceptions of climate change risk’, Environmental Communications.

Paulette, F., Mulder, J. and Wicherts, J. (2019), ‘The influence of gender stereotype threat on mathematics test scores of dutch high school students: A registered report’, Comprehensive Results in Social Psychology, pp. 135.

Peters, E., Västfjäll, D., Slovic, P., Mertz, C., Mazzocco, K. and Dickert, S. (2006), ‘Numeracy and decision making’, Psychological science, 17(5): 407413.

Poortinga, W., Steg, L. and Vlek, C. (2002), ‘Environmental risk concern and preferences for energy-saving measures’, Environment and behavior, 34(4): 455478.

R Core Team (2018), ‘A language and environment for statistical computing’, R Foundation for Statistical Computing, Vienna, Austria.

Scherer, L. D., Yates, J. F., Baker, S. G. and Valentine, K. D. (2017), ‘The influence of effortful thought and cognitive proficiencies on the conjunction fallacy: implications for dual-process theories of reasoning and judgment’, Personality and Social Psychology Bulletin, 43(6): 874887.

Schneider, J., Groza, T. and Passant, A. (2013), ‘A review of argumentation for the social semantic web’, Semantic Web, 4(2): 159218.

Shtulman, A. (2013), ‘Epistemic similarities between students’ scientific and supernatural beliefs’, Journal of Educational Psychology, 105(1): 199.

Stanovich, K. E. (2009), What intelligence tests miss: The psychology of rational thought, Yale University Press.

Stanovich, K. E. and West, R. F. (1998), ‘Who uses base rates andp(d/âijĹijh)? an analysis of individual differences’, Memory & Cognition, 26(1): 161179.

Steg, L. and Sievers, I. (2000), ‘Cultural theory and individual perceptions of environmental risks’, Environment and behavior, 32(2): 250269.

Sunstein, C. (2005), Laws of Fear: Beyond the Precautionary Principle, Cambridge University Press.

Thomson, K. S. and Oppenheimer, D. M. (2016), ‘Investigating an alternate form of the cognitive reflection test’, Judgment and Decision making, 11(1): 99.

Toplak, M. E., West, R. F. and Stanovich, K. E. (2014), ‘Assessing miserly information processing: An expansion of the cognitive reflection test’, Thinking & Reasoning, 20(2): 147168.

Tsai, C.-Y., Lin, C.-N., Shih, W.-L. and Wu, P.-L. (2015), ‘The effect of online argumentation upon students’ pseudoscientific beliefs’, Computers & Education, 80:187197.

Van Bavel, J. and Pereira, A. (2018), ‘The partisan brain: An identity-based model of political belief’, Trends in Cognitive Science, 22:213–24.

Van Boven, L., Ramos, J., Montal-Rosenberg, R., Kogut, T., Sherman, D. and Slovic, P. (2019), ‘It depends: Partisan evaluation of conditional probability importance’, Cognition, 188:5163.

van Buuren, S. and Groothuis-Oudshoorn, K. (2011), ‘mice: Multivariate imputation by chained equations in r’, Journal of Statistical Software, 45(3): 167.

Washburn, A. and Skitka, L. (2018), ‘Science denial across the political divide: Liberals and conservatives are similarly motivated to deny attitude-inconsistent science’, Social Psychological and Personality Science, 9(8): 972–80.

Wasserman, E. A., Dorner, W. and Kao, S. (1990), ‘Contributions of specific cell information to judgments of interevent contingency’, Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(3): 509.

Weller, J. A., Dieckmann, N. F., Tusler, M., Mertz, C., Burns, W. J. and Peters, E. (2013), ‘Development and testing of an abbreviated numeracy scale: A rasch analysis approach’, Journal of Behavioral Decision Making, 26(2): 198212.

Latest posts