Allaire-Duquette, G., Foisy, L. M. B., Potvin, P., Riopel, M., Larose, M., & Masson, S. (2021) An fMRI study of scientists with a PhD in physics confronted with naïve ideas in science. Science of Learning.Google Scholar

Associated Press (2014) AP-Gfk poll: confidence in science. The Associated Press.Google Scholar

Au, T. K. F., Chan, C. K., Chan, T. K., Cheung, M. W., Ho, J. Y., & Ip, G. W. (2008) Folkbiology meets microbiology: a study of conceptual and behavioral change. Cognitive Psychology, 57(1), 1–19.Google Scholar

Baillargeon, R., Needham, A., & DeVos, J. (1992) The development of young infants’ intuitions about support. Early Development and Parenting, 1(2), 69–78.Google Scholar

Barlev, M., Mermelstein, S., & German, T. C. (2017) Core intuitions about persons coexist and interfere with acquired Christian beliefs about God. Cognitive Science, 41(S3), 425–454.Google Scholar

Bishop, B. & Anderson, C. A. (1990) Student conceptions of natural selection and its role in evolution. Journal of Research in Science Teaching, 27(5), 415–427.Google Scholar

Blancke, S., Hjermitslev, H. H., & Kjaergaard, P. C. (Eds.) (2014) Creationism in Europe. John Hopkins University Press.Google Scholar

Blancke, S., Van Breusegem, F., De Jaeger, G., Braeckman, J., & Van Montagu, M. (2015) Fatal attraction: the intuitive appeal of GMO opposition. Trends in Plant Science, 20 (7), 414–418.Google Scholar

Bordelon, C. (2021) Conspiracies attack coroner: families demand COVID-19 diagnoses be removed from loved ones’ death certificates. KOAA News, 5. www.koaa.com/news/coronavirus/conspiracies-attack-coroner-families-demand-covid-19-diagnoses-be-removed-from-loved-ones-death-certificatesGoogle Scholar

Bowler, P. J. (1983) The eclipse of Darwinism: anti-Darwinian theories in the decades around 1900. John Hopkins University Press.Google Scholar

Boyd, R. (2008) Do people only use 10 percent of their brains? Scientific American.Google Scholar

Caramazza, A., McCloskey, M., & Green, B. (1981) Naïve beliefs in “sophisticated” subjects: misconceptions about trajectories of objects. Cognition, 9(2), 117–123.Google Scholar

Carey, S. (2000) Science education as conceptual change. Journal of Applied Developmental Psychology, 21(1), 13–19.Google Scholar

Carey, S. (2009). The origin of concepts. Oxford University Press.Google Scholar

Chi, M. T. H. (2005) Commonsense conceptions of emergent processes: why some misconceptions are robust. The Journal of the Learning Sciences, 14(2), 161–199.Google Scholar

Clark, D. B., D’Angelo, C. M., & Schleigh, S. P. (2011) Comparison of students’ knowledge structure coherence and understanding of force in the Philippines, Turkey, China, Mexico, and the United States. The Journal of the Learning Sciences, 20(2), 207–0261.Google Scholar

Clement, J. (1982) Students’ preconceptions in introductory mechanics. American Journal of Physics, 50(1), 66–71.Google Scholar

Clement, J. (1993) Using bridging analogies and anchoring intuitions to deal with students’ preconceptions in physics. Journal of Research in Science Teaching, 30(10), 1241–1257.Google Scholar

Cope, E. D. (1896) The primary factors of organic evolution. Open Court.Google Scholar

diSessa, A. (1993) Toward an epistemology of physics. Cognition & Instruction, 10(2–3) 105–225.Google Scholar

Dunbar, K., Fugelsang, J., & Stein, C. (2007) Do naïve theories ever go away? Using brain and behavior to understand changes in concepts. In Lovett, M. & Shah, P. (Eds.). Thinking with data (pp. 193–206). Lawrence Erlbaum Associates.Google Scholar

Eimer, G. H. T. (1898) On orthogenesis and the importance of natural selection in species formations (McCormack, T. J., Trans.). Open Court.Google Scholar

Evans, E. M., Spiegel, A. N., Gram, W. et al. (2010) A conceptual guide to natural history museum visitors’ understanding of evolution. Journal of Research in Science Teaching, 47(3), 326–353.Google Scholar

Fischbein, E., Stavy, R., & Ma-Naim, H. (1989) The psychological structure of naïve impetus conceptions. International Journal of Science Education, 11(1), 71–81.Google Scholar

Foisy, L. M. B., Potvin, P., Riopel, M., & Masson, S. (2015) Is inhibition involved in overcoming a common physics misconception in mechanics? Trends in Neuroscience and Education, 4 (1–2) 26–36.Google Scholar

Galileo, G. (1632) Dialogue concerning the two chief world systems, Ptolemaic & Copernican. University of California Press.Google Scholar

Gopnik, A. & Wellman, H. M. (2012) Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory. Psychological Bulletin, 138(6), 1085–1108.Google Scholar

Gregory, T. R. (2009) Understanding natural selection: essential concepts and common misconceptions. Evolution: Education and Outreach, 2(2), 156–175.Google Scholar

Halloun, I. A. & Hestenes, D. (1985) Common sense concepts about motion. American Journal of Physics, 53(11), 1056–1065.Google Scholar

Heddy, B. C. & Nadelson, L. S. (2012) A global perspective of the variables associated with acceptance of evolution. Evolution: Education and Outreach, 5(3), 412–418.Google Scholar

Howe, C., Tavares, J. T., & Devine, A. (2012) Everyday conceptions of object fall: explicit and tacit understanding during middle childhood. Journal of Experimental Child Psychology, 111(3), 351–366.Google Scholar

Jee, B. D., Uttal, D. H., Spiegel, A., & Diamond, J. (2015) Expert-novice differences in mental models of viruses, vaccines, and the causes of infectious disease. Public Understanding of Science, 24(2), 241–256.Google Scholar

Kahneman, D. (2011) Thinking, fast and slow. Farrar, Straus & Giroux.Google Scholar

Kaiser, M. K., Jonides, J., & Alexander, J. (1986) Intuitive reasoning about abstract and familiar physics problems. Memory & Cognition, 14(4), 308–312.Google Scholar

Kelemen, D., Rottman, J., & Seston, R. (2013) Professional physical scientists display tenacious teleological tendencies: purpose-based reasoning as a cognitive default. Journal of Experimental Psychology: General, 142(4), 1074–1083.Google Scholar

Kim, E. & Pak, S. J. (2002) Students do not overcome conceptual difficulties after solving 1000 traditional problems. American Journal of Physics, 70(7), 759–765.Google Scholar

Kim, I. K. & Spelke, E. S. (1999) Perception and understanding of effects of gravity and inertia on object motion. Developmental Science, 2(3), 339–362.Google Scholar

Krist, H. (2010) Development of intuitions about support beyond infancy. Developmental Psychology, 46(1), 266–278.Google Scholar

Lamarck, J. B. (1809) Philosophie zoologique (Elliot, H., Trans.). Haffner.Google Scholar

Legare, C. H. & Gelman, S. A. (2008) Bewitchment, biology, or both: the co-existence of natural and supernatural explanatory frameworks across development. Cognitive Science, 32(4), 607–642.Google Scholar

Legare, C. H., Opfer, J., Busch, J. T. A., & Shtulman, A. (2018) A field guide for teaching evolution in the social sciences. Evolution and Human Behavior, 39(3), 257–263.Google Scholar

Legare, C. H. & Shtulman, A. (2018) Explanatory pluralism across cultures and development. In Proust, J. & Fortier, M. (Eds.). Interdisciplinary approaches to metacognitive diversity (pp. 415–432). Oxford University Press.Google Scholar

Masson, M. E., Bub, D. N., & Lalonde, C. E. (2011) Video-game training and naïve reasoning about object motion. Applied Cognitive Psychology, 25(1), 166–173.Google Scholar

Mayr, E. (1982) The growth of biological thought: diversity, evolution, and inheritance. Harvard University Press.Google Scholar

McCauley, R. N. (2011) Why religion is natural and science is not. Oxford University Press.Google Scholar

McCloskey, M. (1983a) Intuitive physics. Scientific American, 248(4), 122–130.Google Scholar

McCloskey, M. (1983b) Naïve theories of motion. In Gentner, D. & Stevens, A. L. (Eds.). Mental models (pp. 299–324). Erlbaum.Google Scholar

National Academies of Sciences, Engineering, and Medicine. (2016) Science literacy: concepts, contexts, and consequences. The National Academies Press.Google Scholar

National Science Board (2020) Science and engineering indicators. National Science Foundation.Google Scholar

Nersessian, N. J. (1989). Conceptual change in science and in science education. Synthese, 80(1), 163–183.Google Scholar

Novick, L. R., Shade, C. K., & Catley, K. M. (2011) Linear versus branching depictions of evolutionary history: implications for diagram design. Topics in Cognitive Science, 3(3), 536–559.Google Scholar

Pobiner, B. (2016) Accepting, understanding, teaching, and learning (human) evolution: obstacles and opportunities. American Journal of Physical Anthropology, 159(S61), 232–274.Google Scholar

Reiner, M., Slotta, J. D., Chi, M. T. H., & Resnick, L. B. (2000) Naïve physics reasoning: a commitment to substance-based conceptions. Cognition and Instruction, 18 (1), 1–34.Google Scholar

Renken, M. D. & Nunez, N. (2010) Evidence for improved conclusion accuracy after reading about rather than conducting a belief-inconsistent simple physics experiment. Applied Cognitive Psychology, 24(6), 792–811.Google Scholar

Rutjens, B. T., van der Linden, S., & van der Lee, R. (2021) Science skepticism in times of COVID-19. Group Processes & Intergroup Relations, 24(2), 276–283.Google Scholar

Shtulman, A. (2006) Qualitative differences between naïve and scientific theories of evolution. Cognitive Psychology, 52(2), 170–194.Google Scholar

Shtulman, A. (2017) Scienceblind: why our intuitive theories about the world are so often wrong. Basic Books.Google Scholar

Shtulman, A. (2019) Doubly counterintuitive: cognitive obstacles to the discovery and the learning of scientific ideas and why they often differ. In Samuels, R. & Wilkenfeld, D. (Eds.). Advances in experimental philosophy of science (pp. 97–121). Bloomsbury.Google Scholar

Shtulman, A. & Calabi, P. (2012) Cognitive constraints on the understanding and acceptance of evolution. In Rosengren, K. S., Brem, S., Evans, E. M., & Sinatra, G. (Eds.). Evolution challenges: Integrating research and practice in teaching and learning about evolution (pp. 47–65). Oxford University Press.Google Scholar

Shtulman, A. & Calabi, P. (2013) Tuition vs. intuition: effects of instruction on naïve theories of evolution. Merrill-Palmer Quarterly, 59(2), 141–167.Google Scholar

Shtulman, A. & Harrington, K. (2016) Tensions between science and intuition across the lifespan. Topics in Cognitive Science, 8(1), 118–137.Google Scholar

Shtulman, A. & Legare, C. H. (2020) Competing explanations of competing explanations: accounting for conflict between scientific and folk explanations. Topics in Cognitive Science, 12(4), 1337–1362.Google Scholar

Shtulman, A., Neal, C., & Lindquist, G. (2016) Children’s ability to learn evolutionary explanations for biological adaptation. Early Education and Development, 27(8), 1222–1236.Google Scholar

Shtulman, A. & Lombrozo, T. (2016) Bundles of contradiction: a coexistence view of conceptual change. In Barner, D. & Baron, A. (Eds.). Core knowledge and conceptual change (pp. 49–67). Oxford University Press.Google Scholar

Shtulman, A. & Schulz, L. (2008). The relation between essentialist beliefs and evolutionary reasoning. Cognitive Science, 32(6), 1049–1062.Google Scholar

Shtulman, A., Villalobos, A., & Ziel, D. (2021) Whitewashing nature: sanitized depictions of biology in children’s books and parent–child conversation. Child Development, 92(6), 2356–2374.Google Scholar

Shtulman, A. & Valcarcel, J. (2012) Scientific knowledge suppresses but does not supplant earlier intuitions. Cognition, 124(2), 209–215.Google Scholar

Spelke, E. S. (1994) Initial knowledge: six suggestions. Cognition, 50(1–3), 431–445.Google Scholar

Spelke, E. S., Breinlinger, K., Macomber, J., & Jacobson, K. (1992) Origins of knowledge. Psychological Review, 99(4), 605–632.Google Scholar

Steinberg, M. S., Brown, D. E., & Clement, J. (1990) Genius is not immune to persistent misconceptions: conceptual difficulties impeding Isaac Newton and contemporary physics students. International Journal of Science Education, 12(3), 265–273.Google Scholar

Swift, A. (2017) In US, belief in creationist view of humans at new low. Gallup.Google Scholar

Trundle, K. C., Atwood, R. K., & Christopher, J. E. (2007) A longitudinal study of conceptual change: preservice elementary teachers’ conceptions of moon phases. Journal of Research in Science Teaching, 44(2), 303–326.Google Scholar

Villegas, P. (2020). South Dakota nurse says many patients deny the coronavirus exists right up until death. The Washington Post, November 6.Google Scholar

Vosniadou, S. (1994) Capturing and modeling the process of conceptual change. Learning and Instruction, 4(1), 45–69.Google Scholar

Vosniadou, S., Ioannides, C., Dimitrakopoulou, A., & Papademetriou, E. (2001) Designing learning environments to promote conceptual change in science. Learning and Instruction, 11(4–5), 381–419.Google Scholar

Ware, E. A. & Gelman, S. A. (2014) You get what you need: an examination of purpose-based inheritance reasoning in undergraduates, preschoolers, and biological experts. Cognitive Science, 38(2), 197–243.Google Scholar

Weisberg, D. S., Landrum, A. R., Metz, S. E., & Weisberg, M. (2018) No missing link: knowledge predicts acceptance of evolution in the United States. BioScience, 68(3), 212–222.Google Scholar

Young, A. G. & Shtulman, A. (2020) How children’s cognitive reflection shapes their science understanding. Frontiers in Psychology, 11, 1247.Google Scholar

Alwan, N. A., Burgess, R. A., Ashworth, S. et al. (2020) Scientific consensus on the COVID-19 pandemic: we need to act now. The Lancet, 396(10260), e71–e72. https://doi.org/10.1016/S0140-6736(20)32153-XGoogle Scholar

AVAAZ (2020) Facebook’s algorithm: a major threat to public health. Retrieved from https://secure.avaaz.org/campaign/en/facebook_threat_health/Google Scholar

Balliet, D. (2010) Communication and cooperation in social dilemmas: a meta-analytic review. Journal of Conflict Resolution, 54(1), 39–57. https://doi.org/10.1177/0022002709352443Google Scholar

Banas, J. A. & Miller, G. (2013) Inducing resistance to conspiracy theory propaganda: testing inoculation and metainoculation strategies. Human Communication Research, 39(2), 184–207. https://doi.org/10.1111/hcre.12000Google Scholar

Barnett, M. D., Hale, T. M., & Sligar, K. B. (2017) Masculinity, femininity, sexual dysfunctional beliefs, and rape myth acceptance among heterosexual college men and women. Sexuality & Culture, 21(3), 741–753. https://doi.org/10.1007/s12119-017-9420-3Google Scholar

Bénabou, R. & Tirole, J. (2016) Mindful economics: the production, consumption, and value of beliefs. Journal of Economic Perspectives, 30(3), 141–164. https://doi.org/10.1257/jep.30.3.141Google Scholar

Berger, E. & Reupert, A. (2020) The COVID-19 pandemic in Australia: lessons learnt. Psychological Trauma: Theory, Research, Practice, and Policy, 12(5), 494–496. https://doi.org/10.1037/tra0000722Google Scholar

Bowles, S. (2008) Policies designed for self-interested citizens may undermine “the moral sentiments”: evidence from economic experiments. Science, 320(5883), 1605–1609. https://doi.org/10.1126/science.1152110Google Scholar

Brubaker, R. (2020) Paradoxes of populism during the pandemic. Thesis Eleven, 164(1) https://doi.org/10.1177/0725513620970804Google Scholar

Brulle, R. J. (2013) Institutionalizing delay: foundation funding and the creation of US climate change counter-movement organizations. Climatic Change, 122(4), 681–694. https://doi.org/10.1007/s10584-013-1018-7Google Scholar

Bruns, A., Harrington, S., & Hurcombe, E. (2020) “Corona? 5G? or both?”: the dynamics of COVID-19/5G conspiracy theories on Facebook. Media International Australia, 177(1), 12–29. https://doi.org/10.1177/1329878x20946113Google Scholar

Budescu, D. V., Por, H.-H., & Broomell, S. B. (2012) Effective communication of uncertainty in the IPCC reports. Climatic Change, 113(2), 181–200. https://doi.org/10.1007/s10584-011-0330-3Google Scholar

Bukuluki, P., Mwenyango, H., Katongole, S. P., Sidhva, D., & Palattiyil, G. (2020) The socio-economic and psychosocial impact of Covid-19 pandemic on urban refugees in Uganda. Social Sciences & Humanities Open, 2(1). https://doi.org/10.1016/j.ssaho.2020.100045Google Scholar

Campbell, T. H. & Kay, A. C. (2014) Solution aversion: on the relation between ideology and motivated disbelief. Journal of Personality and Social Psychology, 107(5), 809–824. https://doi.org/10.1037/a0037963Google Scholar

Cheng, Y., Ma, N., Witt, C. et al. (2021) Face masks effectively limit the probability of SARS-CoV-2 transmission. Science, 372(6549), 1439–1443. https://doi.org/10.1126/science.abg6296Google Scholar

Chu, D. K., Akl, E. A., Duda, S. et al. (2020) Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. The Lancet, 395(10242), 1973–1987. https://doi.org/10.1016/S0140-6736(20)31142-9Google Scholar

Coates, M. (2020) Covid-19 and the rise of racism. BMJ, 369, m1384. https://doi.org/10.1136/bmj.m1384Google Scholar

Cook, J. (2020a) Deconstructing climate science denial. In Holmes, D. & Richardson, L. M. (Eds.). Research handbook on communicating climate change. Edward Elgar Publishing.Google Scholar

Cook, J. (2020b) Using humor and games to counter science misinformation. Skeptical Inquirer, 44(3), 38–41.Google Scholar

Cook, J., & Lewandowsky, S. (2016) Rational irrationality: modeling climate change belief polarization using Bayesian networks. Topics in Cognitive Science, 8(1), 160–179. https://doi.org/10.1111/tops.12186Google Scholar

Cook, J., Lewandowsky, S., & Ecker, U. K. H. (2017) Neutralizing misinformation through inoculation: exposing misleading argumentation techniques reduces their influence. PLoS ONE, 12(5), e0175799. https://doi.org/10.1371/journal.pone.0175799Google Scholar

Cook, J., van der Linden, S., Maibach, E., & Lewandowsky, S. (2018) The consensus handbook. www.climatechangecommunication.org/all/consensus-handbook/ https://doi.org/10.13021/G8MM6PGoogle Scholar

Crockett, M. J., Kurth-Nelson, Z., Siegel, J. Z., Dayan, P., & Dolan, R. J. (2014) Harm to others outweighs harm to self in moral decision making. Proceedings of the National Academy of Sciences, 111(48), 17320–17325. https://doi.org/10.1073/pnas.1408988111Google Scholar

Daly, M. & Robinson, E. (2021) Willingness to Vaccinate against COVID-19 in the U.S.: Representative Longitudinal Evidence from April to October 2020. American Journal of Preventive Medicine, 60(6), 766–773. https://doi.org/10.1016/j.amepre.2021.01.008Google Scholar

Danielson, R. W., Sinatra, G. M., & Kendeou, P. (2016) Augmenting the refutation text effect with analogies and graphics. Discourse Processes, 53(5–6), 392–414. https://doi.org/10.1080/0163853x.2016.1166334Google Scholar

Dawes, R. M. (1980). Social dilemmas. Annual Review of Psychology, 31, 169–193. https://doi.org/10.1146/annurev.ps.31.020180.001125Google Scholar

DeVerna, M. R., Pierri, F., Truong, B. et al. (2021) CoVaxxy: a global collection of English-language Twitter posts about COVID-19 vaccines. arXiv.org preprint. https://doi.org/10.48550/arXiv.2101.07694Google Scholar

Dickson, E. J. (2020) Anti-vax doctor promotes conspiracy theory that death certificates falsely cite COVID-19. www.rollingstone.com/culture/culture-features/anti-vax-doctor-covid-19-death-certificates-984407/Google Scholar

Diederich, J. & Goeschl, T. (2014) Willingness to pay for voluntary climate action and its determinants: field-experimental evidence. Environmental and Resource Economics, 57, 405–429. https://doi.org/10.1007/s10640-013-9686-3Google Scholar

Diethelm, P. & McKee, M. (2009) Denialism: what is it and how should scientists respond? European Journal of Public Health, 19(1), 2–4. https://doi.org/10.1093/eurpub/ckn139Google Scholar

Dunbar, A. & Jones, N. E. (2021) Race, police, and the pandemic: considering the role of race in public health policing. Ethnic and Racial Studies, 44(5), 773–782. https://doi.org/10.1080/01419870.2020.1851381Google Scholar

Enders, A. M., Uscinski, J. E., Klofstad, C., & Stoler, J. (2020) The different forms of COVID-19 misinformation and their consequences. Harvard Kennedy School Misinformation Review, 1(8). https://doi.org/10.37016/mr-2020-48Google Scholar

Evanega, S., Lynas, M., Adams, J., Smolenyak, K., & Insights, C. G. (2020) Coronavirus misinformation: quantifying sources and themes in the COVID-19 “infodemic” (Tech. Rep.). Cornell University.Google Scholar

Every-Palmer, S., Jenkins, M., Gendall, P. et al. (2020). Psychological distress, anxiety, family violence, suicidality, and wellbeing in New Zealand during the COVID-19 lockdown: a cross-sectional study. PLoS ONE, 15(11), e0241658. https://doi.org/10.1371/journal.pone.0241658Google Scholar

Farrell, J. (2015) Network structure and influence of the climate change counter-movement. Nature Climate Change, 6(4), 370–374. https://doi.org/10.1038/nclimate2875Google Scholar

Fleerackers, A., Riedlinger, M., Moorhead, L., Ahmed, R., & Alperin, J. P. (2021) Communicating scientific uncertainty in an age of COVID-19: an investigation into the use of preprints by digital media outlets. Health Communication, 37(6), 726–738. https://doi.org/10.1080/10410236.2020.1864892Google Scholar

Golman, R., Hagmann, D., & Loewenstein, G. (2017) Information avoidance. Journal of Economic Literature, 55(1), 96–135. https://doi.org/10.1257/jel.20151245Google Scholar

Greenaway, C., Hargreaves, S., Barkati, S., Coyle, C. M., Gobbi, F., Veizis, A., & Douglas, P. (2020) COVID-19: Exposing and addressing health disparities among ethnic minorities and migrants. Journal of Travel Medicine, 27(7). https://doi.org/10.1093/jtm/taaa113Google Scholar

Hahn, U. (2020) Argument quality in real world argumentation. Trends in Cognitive Sciences, 24(5), 363–374. https://doi.org/10.1016/j.tics.2020.01.004Google Scholar

Hahn, U. & Harris, A. J. (2014) What does it mean to be biased: motivated reasoning and rationality. In Ross, B. H. (Ed.), The psychology of learning and motivation, Vol. 61 (pp. 41–102). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-800283-4.00002-2Google Scholar

Hamilton, L. C., Hartter, J., & Saito, K. (2015) Trust in scientists on climate change and vaccines. SAGE Open, 5(3), 1–13. https://doi.org/10.1177/2158244015602752Google Scholar

Hansson, S. O. (2017) Science denial as a form of pseudoscience. Studies in History and Philosophy of Science, 63, 39–47. https://doi.org/10.1016/j.shpsa.2017.05.002CrossRefGoogle ScholarPubMed

Hardin, G. (1968). The tragedy of the commons. Science, 162(3859), 1243–1248. https://doi.org/10.1126/science.162.3859.1243Google Scholar

Haug, N., Geyrhofer, L., Londei, A. et al. (2020) Ranking the effectiveness of worldwide COVID-19 government interventions. Nature Human Behaviour, 4(12), 1303–1312. https://doi.org/10.1038/s41562-020-01009-0Google Scholar

Havey, N. F. (2020) Partisan public health: how does political ideology influence support for COVID-19 related misinformation? Journal of Computational Social Science, 3(2), 319–342. https://doi.org/10.1007/s42001-020-00089-2Google Scholar

Hertwig, R. & Engel, C. (2016) Homo ignorans. Perspectives on Psychological Science, 11(3), 359–372. https://doi.org/10.1177/1745691616635594Google Scholar

Hornsey, M. J., Harris, E., & Fielding, K. S. (2018) The psychological roots of anti-vaccination attitudes: a 24-nation investigation. Health Psychology, 37(4), 307–315. https://doi.org/10.1037/hea0000586Google Scholar

Howard, J., Huang, A., Li, Z. et al. (2021) An evidence review of face masks against COVID-19. Proceedings of the National Academy of Sciences, 118(4), e2014564118. https://doi.org/10.1073/pnas.2014564118Google Scholar

Ivanov, B., Parker, K. A., & Dillingham, L. (2020) Inoculation theory as a strategic tool. In The handbook of applied communication research (pp. 11–28). Wiley Online Library.Google Scholar

Jamison, A. M., Quinn, S. C., & Freimuth, V. S. (2019) “You don’t trust a government vaccine”: narratives of institutional trust and influenza vaccination among African American and white adults. Social Science & Medicine, 221, 87–94. https://doi.org/10.1016/j.socscimed.2018.12.020Google Scholar

Jern, A., Chang, K.-M. K., & Kemp, A. C. (2014) Belief polarization is not always irrational. Psychological Review, 121(2), 206–224. https://doi.org/10.1037/a0035941Google Scholar

Johnson, T., Dawes, C., Fowler, J., & Smirnov, O. (2020) Slowing COVID-19 transmission as a social dilemma: lessons for government officials from interdisciplinary research on cooperation. Journal of Behavioral Public Administration, 3(1), 1–13. https://doi.org/10.30636/jbpa.31.150Google Scholar

Jolley, D. & Paterson, J. L. (2020) Pylons ablaze: examining the role of 5G COVID-19 conspiracy beliefs and support for violence. British Journal of Social Psychology, 59(3), 628–640. https://doi.org/10.1111/bjso.12394Google Scholar

Juanchich, M., Sirota, M., Jolles, D., & Whiley, L. A. (2021) Are COVID-19 conspiracies a threat to public health? Psychological characteristics and health protective behaviours of believers. European Journal of Social Psychology, 51(6), 969–989. https://doi.org/10.1002/ejsp.2796Google Scholar

Koessler, A.-K., Ortiz-Riomalo, J., Janke, M., & Engel, S. (2020) Structuring communication effectively for environmental cooperation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3533910Google Scholar

Kramer, A. & Kramer, K. Z. (2020) The potential impact of the Covid-19 pandemic on occupational status, work from home, and occupational mobility. Journal of Vocational Behavior, 119, 103442. https://doi.org/10.1016/j.jvb.2020.103442Google Scholar

Lewandowsky, S. (2021a) Climate change, disinformation, and how to combat it. Annual Review of Public Health, 42(1), 1–21. https://doi.org/10.1146/annurev-publhealth-090419-102409Google Scholar

Lewandowsky, S. (2021b) Conspiracist cognition: chaos, convenience, and cause for concern. Journal for Cultural Research, 25(1), 12–35. https://doi.org/10.1080/14797585.2021.1886423Google Scholar

Lewandowsky, S., Ballard, T., Oberauer, K., & Benestad, R. (2016) A blind expert test of contrarian claims about climate data. Global Environmental Change, 39, 91–97. https://doi.org/10.1016/j.gloenvcha.2016.04.013Google Scholar

Lewandowsky, S., Cook, J., Ecker, U. et al. (2020) The debunking handbook 2020. https://sks.to/db2020Google Scholar

Lewandowsky, S., Cook, J., & Lloyd, E. (2016) The “Alice in Wonderland” mechanics of the rejection of (climate) science: simulating coherence by conspiracism. Synthese, 195(1), 175–196. https://doi.org/10.1007/s11229-016-1198-6Google Scholar

Lewandowsky, S., Cook, J., Oberauer, K., Brophy, S., Lloyd, E. A., & Marriott, M. (2015) Recurrent fury: conspiratorial discourse in the blogosphere triggered by research on the role of conspiracist ideation in climate denial. Journal of Social and Political Psychology, 3(1), 142–178. https://doi.org/10.5964/jspp.v3i1.443Google Scholar

Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017) Beyond misinformation: Understanding and coping with the post-truth era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369. https://doi.org/10.1016/j.jarmac.2017.07.008Google Scholar

Lewandowsky, S., Gignac, G. E., & Oberauer, K. (2013) The role of conspiracist ideation and worldviews in predicting rejection of science. PLoS ONE, 8(10), e75637. https://doi.org/10.1371/journal.pone.0075637Google Scholar

Lewandowsky, S., Mann, M. E., Brown, N. J. L., & Friedman, H. (2016) Science and the public: debate, denial, and skepticism. Journal of Social and Political Psychology, 4(2), 537–553. https://doi.org/10.5964/jspp.v4i2.604Google Scholar

Lewandowsky, S. & Oberauer, K. (2016) Motivated rejection of science. Current Directions in Psychological Science, 25(4), 217–222. https://doi.org/10.1177/0963721416654436Google Scholar

Lewandowsky, S., Oberauer, K., & Gignac, G. E. (2013) NASA faked the moon landing—therefore (climate) science is a hoax: an anatomy of the motivated rejection of science. Psychological Science, 24(5), 622–633. https://doi.org/10.1177/0956797612457686Google Scholar

Lewandowsky, S. & van der Linden, S. (2021) Countering misinformation and fake news through inoculation and prebunking. European Review of Social Psychology, 32(2) 348–384. https://doi.org/10.1080/10463283.2021.1876983Google Scholar

Lewandowsky, S., Woike, J. K., & Oberauer, K. (2020) Genesis or evolution of gender differences? Worldview-based dilemmas in the processing of scientific information. Journal of Cognition, 3(1), 1–25. https://doi.org/10.5334/joc.99Google Scholar

Loomba, S., de Figueiredo, A., Piatek, S. J., de Graaf, K., & Larson, H. J. (2021) Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nature Human Behaviour, 5(3), 337–348. https://doi.org/10.1038/s41562-021-01056-1Google Scholar

Lowes, S. R. & Montero, E. (2018) The legacy of colonial medicine in Central Africa. https://ssrn.com/abstract=3138813Google Scholar

Mamié, R., Ribeiro, M. H., & West, R. (2021). Are anti-feminist communities gateways to the far right? Evidence from Reddit and YouTube. 13th ACM Web Science Conference 2021, Association for Computing Machinery, pp. 139–147. https://dx.doi.org/10.1145/3447535.3462504Google Scholar

Mastrandrea, M. D., Mach, K. J., Plattner, G.-K. et al. (2011) The ipcc ar5 guidance note on consistent treatment of uncertainties: a common approach across the working groups. Climatic Change, 108(4), 675–691. https://doi.org/10.1007/s10584-011-0178-6Google Scholar

McKee, M. & Diethelm, P. (2010) How the growth of denialism undermines public health. BMJ, 341(7786), 1309–1311. https://doi.org/10.1136/bmj.c6950Google Scholar

McKee, M. & Stuckler, D. (2020) Scientific divisions on COVID-19: not what they might seem. BMJ, 371(8265), m4024. https://doi.org/10.1136/bmj.m4024Google Scholar

Milinski, M., Semmann, D., & Krambeck, H. J. (2002). Reputation helps solve the “tragedy of the commons.” Nature, 415(6870), 424–426. https://doi.org/10.1038/415424aGoogle Scholar

Momplaisir, F., Haynes, N., Nkwihoreze, H., Nelson, M., Werner, R. M., & Jemmott, J. (2021) Understanding drivers of COVID-19 vaccine hesitancy among Blacks. Clinical Infectious Diseases, 73(10), 1784–1789. https://doi.org/10.1093/cid/ciab102Google Scholar

Oppenheimer, D. M. (2006) Consequences of erudite vernacular utilized irrespective of necessity: problems with using long words needlessly. Applied Cognitive Psychology, 20(2), 139–156. https://doi.org/10.1002/acp.1178Google Scholar

Oreskes, N. & Conway, E. M. (2010) Merchants of doubt. Bloomsbury Publishing.Google Scholar

Ostrom, E. (1993) Governing the commons: the evolutions of institutions for collective action. Cambridge University Press.Google Scholar

O’Sullivan, D., Rahamathulla, M., & Pawar, M. (2020) The impact and implications of COVID-19: an Australian perspective. The International Journal of Community and Social Development, 2(2), 134–151. https://doi.org/10.1177/2516602620937922Google Scholar

Patel, S. S., Kalma, J., & Bluman, E. M. (2020) Understanding COVID-19 vaccines and their development. Journal of Bone, 102(20), 1759–1769. https://doi.org/10.2106/JBJS.20.01191Google Scholar

Pei, X. & Mehta, D. (2020) #Coronavirus or #Chinese virus?! Understanding the negative sentiment reflected in Tweets with racist hashtags across the development of covid-19. arXiv.org preprint. https://doi.org/10.48550/arXiv.2005.08224Google Scholar

Perry, H. B. (2020) Is access enough? Interrogating the influence of money and power in shaping information. Open Information Science, 4(1), 29–38. https://doi.org/10.1515/opis-2020-0003Google Scholar

Petersen, E., Koopmans, M., Go, U. et al. (2020). Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics. The Lancet Infectious Diseases, 20(9), e238–e244. https://doi.org/10.1016/s1473-3099(20)30484-9Google Scholar

Readfearn, G. (2016) Revealed: most popular climate story on social media told half a million people the science was a hoax. www.desmogblog.com/2016/11/29/revealed-most-popular-climate-story-social-media-told-half-million-people-science-was-hoaxGoogle Scholar

Reardon, S. (2011) Decrying CIA vaccination sham, Health Workers Brace for Backlash. Science, 333(6041), 395–395. https://doi.org/10.1126/science.333.6041.395Google Scholar

Risbey, J. S., Lewandowsky, S., Hunter, J. R., & Monselesan, D. P. (2015) Betting strategies on fluctuations in the transient response of greenhouse warming. Philosophical Transactions of the Royal Society (A), 373(2055), 20140463. https://doi.org/10.1098/rsta.2014.0463Google Scholar

Robinson, L. A., Sullivan, R., & Shogren, J. F. (2020) Do the benefits of COVID-19 policies exceed the costs? exploring uncertainties in the age–VSL relationship. Risk Analysis, 41(5), 761–770. https://doi.org/10.1111/risa.13561Google Scholar

Roozenbeek, J., Schneider, C. R., Dryhurst, S. et al. (2020) Susceptibility to misinformation about COVID-19 around the world. Royal Society Open Science, 7(10), 201199. https://doi.org/10.1098/rsos.201199Google Scholar

Rutjens, B. T., van der Linden, S., & van der Lee, R. (2021) Science skepticism in times of COVID-19. Group Processes & Intergroup Relations, 24(2), 276–283. https://doi.org/10.1177/1368430220981415Google Scholar

Sakalh-Ugurlu, N. & Glick, P. (2003) Ambivalent sexism and attitudes toward women who engage in premarital sex in Turkey. The Journal of Sex Research, 40(3), 296–302. https://doi.org/10.1080/00224490309552194Google Scholar

Schimmenti, A., Billieux, J., & Starcevic, V. (2020) The four horsemen of fear: an integrated model of understanding fear experiences during the COVID-19 pandemic. Clinical Neuropsychiatry, 17(2), 41–45. https://doi.org/10.36131/CN20200202.Google Scholar

Schmid, P. & Betsch, C. (2019) Effective strategies for rebutting science denialism in public discussions. Nature Human Behavior, 3(9), 931–939. https://doi.org/10.1038/s41562-019-0632-4Google Scholar

Seifert, C. M. (2002) The continued influence of misinformation in memory: what makes a correction effective? In Ross, B. H. (Ed.), The psychology of learning and motivation: advances in research and theory, Vol. 41 (pp. 265–292). Academic Press. https://doi.org/10.1016/S0079-7421(02)80009-3Google Scholar

Serafini, G., Parmigiani, B., Amerio, A., Aguglia, A., Sher, L., & Amore, M. (2020) The psychological impact of COVID-19 on the mental health in the general population. QJM: An International Journal of Medicine, 113(8), 531–537. https://doi.org/10.1093/qjmed/hcaa201Google Scholar

Smirnov, O. (2019) Collective risk social dilemma and the consequences of the US withdrawal from international climate negotiations. Journal of Theoretical Politics, 31(4), 660–676. https://doi.org/10.1177/0951629819875511Google Scholar

Sutton, R. M. & Douglas, K. M. (2020) Agreeing to disagree: reports of the popularity of Covid-19 conspiracy theories are greatly exaggerated. Psychological Medicine, 52(4), 791–793. https://doi.org/10.1017/S0033291720002780Google Scholar

The Lancet (2020) The plight of essential workers during the COVID-19 pandemic. The Lancet, 395(10237), 1587. https://doi.org/10.1016/S0140-6736(20)31200-9Google Scholar

Thomson, S. & Ip, E. C. (2020) COVID-19 emergency measures and the impending authoritarian pandemic. Journal of Law and the Biosciences, 7(1), 1–33. https://doi.org/10.1093/jlb/lsaa064Google Scholar

Uscinski, J. E., Douglas, K., & Lewandowsky, S. (2017) Climate change conspiracy theories. In Oxford research encyclopedia of climate science. https://doi.org/10.1093/acrefore/9780190228620.013.328Google Scholar

Uscinski, J. E., Enders, A. M., Klofstad, C. et al. (2020) Why do people believe COVID-19 conspiracy theories? Harvard Kennedy School Misinformation Review, 1(3). https://doi.org/10.37016/mr-2020-015Google Scholar

van Barneveld, K., Quinlan, M., Kriesler, P. et al. (2020) The COVID-19 pandemic: lessons on building more equal and sustainable societies. The Economic and Labour Relations Review, 31(2), 133–157. https://doi.org/10.1177/1035304620927107Google Scholar

van Basshuysen, P., & White, L. (2021) Bad data and flawed models? Fact-checking Winsberg et al.’s case against lockdowns. www.lse.ac.uk/philosophy/blog/2021/01/26/bad-data-and-flawed-models/Google Scholar

van der Linden, S. (2021) Some recommendations for doing high-impact research in social psychological science. Asian Journal of Social Psychology, 24(1), 37–41. https://doi.org/10.1111/ajsp.12463Google Scholar

van der Linden, S., Leiserowitz, A., Rosenthal, S., & Maibach, E. (2017) Inoculating the public against misinformation about climate change. Global Challenges, 1(2), 1600008. https://doi.org/10.1002/gch2.201600008Google Scholar

Vorms, M. & Hahn, U. (2019) In the space of reasonable doubt. Synthese, 198(15), 3609–3633. https://doi.org/10.1007/s11229-019-02488-zGoogle Scholar

Vraga, E. K. & Bode, L. (2020) Defining misinformation and understanding its bounded nature: using expertise and evidence for describing misinformation. Political Communication, 37(1), 136–144. https://doi.org/10.1080/10584609.2020.1716500Google Scholar

Ward, B. (2020) Organisers of anti-lockdown declaration have track record of promoting denial of health and environmental risks. www.lse.ac.uk/granthaminstitute/news/organisers-of-anti-lockdown-declaration-have-track-record-of-promoting-denial-of-health-and-environmental-risks/Google Scholar

Wenham, C., Smith, J., & Morgan, R. (2020) COVID-19: the gendered impacts of the outbreak. The Lancet, 395(10227), 846–848. https://doi.org/10.1016/s0140-6736(20)30526-2Google Scholar

Wondreys, J. & Mudde, C. (2020) Victims of the pandemic? European far-right parties and COVID-19. Nationalities Papers, 50(1), 86–103. https://doi.org/10.1017/nps.2020.93Google Scholar

Xiong, J., Lipsitz, O., Nasri, F. et al. (2020) Impact of COVID-19 pandemic on mental health in the general population: a systematic review. Journal of Affective Disorders, 277, 55–64. https://doi.org/10.1016/j.jad.2020.08.001Google Scholar

Alland, A. (2002) Race in mind: race, IQ and other racisms. Palgrave.Google Scholar

American Anthropological Association (AAA)(1998) AAA statement on race. https://bit.ly/2VmQfiNGoogle Scholar

American Association of Physical Anthropologists (1996) AAPA statement on race and racism. https://bit.ly/3iz9DDiGoogle Scholar

American College of Physicians (2010) “Racial and Ethnic Disparities In Health Care.” Position paper. https://bit.ly/31M4P7LGoogle Scholar

American Journal of Human Genetics (2018) The American Society of Human Genetics denounces attempts to link genetics and racial supremacy. American Journal of Human Genetics, 103(5), 636–673. https://doi.org/10.1016/j.ajhg.2018.10.011Google Scholar

American Sociological Association (2005) Race, ethnicity and the health of Americans. www.asanet.org/sites/default/files/savvy/images/research/docs/pdf/race_ethnicity_health.pdfGoogle Scholar

Anderson, K. O., Green, C. R., & Payne, R. (2009) Racial and ethnic disparities in pain: causes and consequences of unequal care. Critical Review, 10(12), 1187–1204.Google Scholar

Aroke, E. N., Joseph, P. V., Roy, A., et al. (2019) Could epigenetics help explain racial disparities in chronic pain? Journal of Pain Research, 12, 701–710.Google Scholar

Bamshad, M. & Guthery, S. L. (2007) Race, genetics and medicine: does the color of a leopard’s spots matter? Current Opinion in Pediatrics, 19(6), 613–618.Google Scholar

Bartholomew, D. J. (2004) Measuring intelligence: facts and fallacies. Cambridge University Press.Google Scholar

Bird, K. A. (2021) No support for the hereditarian hypothesis of the black–white achievement gap using polygenic scores and tests for divergent selection. American Journal of Physical Anthropology, 175(2), 1–12. https://doi.org/10.1002/ajpa.24216.Google Scholar

Bliss, C. (2012) Race decoded. Stanford University Press.Google Scholar

Brooks, J. D. & King, M. L. (2008) Geneticizing disease: implications for racial health disparities. Center for American Progress. www.americanprogress.org/issues/healthcare/reports/2008/01/15/3832/geneticizing-disease-implications-for-racial-health-disparities/Google Scholar

Bryc, K., Auton, A., Nelson, M. R. et al. (2010) Genome-wide patterns of population structure and admixture in West Africans and African Americans. Proceedings of the National Academy of Sciences. 107(2), 786–791. https://doi.org/10.1073/pnas.0909559107Google Scholar

Buckles, J. (2001) The success story of gene tests. Genome News Network. www.genomenewsnetwork.org/articles/08_01/Tay_Sachs_gene_tests.shtmlGoogle Scholar

Burris, H., Bacaraelli, A., Wright, R. et al. (2016) Epigenetics: linking social and environmental exposures to preterm birth. Journal of Pediatric Research, 79(1-2), 136–140.Google Scholar

Campbell, M. C. & Tishkoff, S. A. (2008) African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annual Review of Genomics and Human Genetics, 9, 403–433.Google Scholar

Cerdeña, J. P., & Plaisime, M.V., & Tsai, J. (2020) From race-based to race-conscious medicine: how anti-racist uprisings call us to act. Lancet, 396(10257) pp. 1125–1128.Google Scholar

Chen, F. et al. (2002) Larger genetic differences within Africans than between Africans and Eurasians. Genetics, 161(1), pp. 269–274.Google Scholar

Cobbinah, S. & Lewis, J. (2018) Racism & health: a public health perspective on racial discrimination. Journal of Evaluation in Clinical Practice, 24, 995–998.Google Scholar

Collins, J., David, R., Symmons, R. et al. (2000) Low-income African-American mothers’ perception of exposure to racial discrimination and infant birth weight. Epidemiology, 11(3), 337–339.Google Scholar

Davis, James F. (1991) Who is black? One nation’s definition. Penn State University Press.Google Scholar

Desalle, R. & Tattersall, I. (2018) Troublesome science: the misuse of genetics and genomics in understanding race. Columbia University Press.Google Scholar

Dickens, W. T. & Flynn, J. R. (2006) Black Americans reduce the racial IQ gap: evidence from standardization samples. Psychological Science, 17 (10), 913–920.Google Scholar

Dolan, C., Wicherts, J., van der Maas, H. et al. (2010) The dangers of unsystematic selection methods and the representativeness of 46 samples of African test-takers. Intelligence, 38(1), 30–37.Google Scholar

Fagan, J. & Holland, C. (2002) Equal opportunity and racial differences in IQ. Intelligence, 30(4), 361–387.Google Scholar

Fairbanks, D. J. (2015) Everyone is African: how science explodes the myth of race. Prometheus.Google Scholar

Fish, J. M., ed. (2002) Race and intelligence: separating science from myth. Lawrence Erlbaum Publishers.Google Scholar

Fish, J. M. (2012) The Myth of Race. N.p.Google Scholar

Fuentes, A. (2012) The myth of race. In race, monogamy, and other lies: busting myths about human nature (pp. 70–113). University of California Press.Google Scholar

Gibson, A. R., Ojiambo, R., Konstabel, K. et al. (2013) Aerobic capacity, activity levels and daily energy expenditure in male and female adolescents of the Kenyan Nandi sub-group. PLoS One, 8(6), e66552.Google Scholar

Gomez, F., Hirbo, J., & Tishkoff, S. A. (2014) Genetic variation and adaptation in Africa: implications for human evolution and disease. Cold Spring Harbor Perspectives in Biology, 6(7). https://doi.org/10.1101/cshperspect.a008524Google Scholar

Goodman, A. H. (1997) Bred in the bone? The Sciences, 37, 20–25. https://doi.org/10.1002/j.2326-1951.1997.tb03296.xGoogle Scholar

Goodman, A. H., Moses, Y., Jones, J. L. et al. (2012) Race: are we so different? Wiley.Google Scholar

Graves, J. L. (2001) The emperor’s new clothes: biological theories of race at the millennium. Rutgers University Press.Google Scholar

Graves, J. L. (2004) The race myth: why we pretend race exists in America. Dutton.Google Scholar

Guillaumin, Colette. (1995) Racism, sexism, power and ideology. Routledge.Google Scholar

Hamilton, B. (2000) East African running dominance: what is behind it? British Journal of Sports Medicine, 34, 393–394.Google Scholar

Harrison, G. P. (2010) Race and reality: what everyone should know about our biological diversity. Prometheus Books.Google Scholar

Harrison, G. P. (2015) Good thinking: what you need to know to be smarter, safer, wealthier, and wiser. Prometheus Books.Google Scholar

Harrison, G. P. (2018) At least know this: essential science to enhance your life. Prometheus Books.Google Scholar

Hefner, J. T. (2009) Cranial nonmetric variation and estimating ancestry*. Journal of Forensic Sciences, 54 (5). doi: 10.1111/j.1556-4029.2009.01118.xGoogle Scholar

Hoberman, J. (1997) Darwin’s athletes. Mariner.Google Scholar

Hoffman, K. M., Trawalter, S., Axt, J. et al. (2016) Racial bias in pain assessment. Proceedings of the National Academy of Sciences, 113(16), 4296–4301.Google Scholar

Hoffman, S. (2006) “Racially-Tailored” medicine unraveled. American University Law Review, 55(395), 397–398.Google Scholar

Hughey, M. W. & Goss, D. R. (2015) A level playing field? Media constructions of athletics, genetics, and race. The ANNALS of the American Academy of Political and Social Science, 661(1), 182–211. https://doi.org/10.1177/0002716215588067Google Scholar

Jencks, C. & Phillips, M. (1998) The black-white test score gap: why it persists and what can be done. Brookings, https://bit.ly/3gJ3yThGoogle Scholar

Kelly, T. E., Chase, G., Kaback, M. et al. (1975) Tay-Sachs disease: high gene frequency in a non-Jewish population. American Journal of Human Genetics, 27(3), 287–291.Google Scholar

Kerr, Ian B. (2010) The myth of racial superiority in sports. The Hilltop Review, 4(1), 19–27.Google Scholar

Lange, A. (2015) “Bones” has been making the same mistake for 10 seasons. Buzzfeed News. www.buzzfeednews.com/article/arianelange/bones-race-forensic-anthropologyGoogle Scholar

Lanz, P. (2000) The concept of intelligence in psychology and philosophy. In Cruse, H., Dean, J., Ritter, H. (Eds.). Prerational intelligence: adaptive behavior and intelligent systems without symbols and logic, Vols 1 and 2 (pp. 19–31). Springer. https://doi.org/10.1007/978-94-010-0870-9_3Google Scholar

Lee, S. S., Mountain, J., Koenig, B. et al. (2008) The ethics of characterizing difference: guiding principles on using racial categories in human genetics. Genome Biology, 9(7), 404. https://doi.org/10%2010.1186/gb-2008-9-7-404Google Scholar

Lewontin, R. (2005) The fallacy of racial medicine: confusions about human races. GeneWatch, 18(4), 5–7.Google Scholar

Marks, D. F. (2010) IQ variations across time, race, and nationality: an artifact of differences in literacy skills. Psychological Reports, 106(3), 643–664. https://doi.org/10.2466/PR0.106.3.643-664. PMID: 20712152Google Scholar

Marks, J. (1995) Human biodiversity: genes, race and history. Aldine de Gruyter.Google Scholar

Merlino, D. (2011) Magic Johnson and Larry Bird: the rivalry that transformed the NBA. Bleacher Report. https://bit.ly/3fgosZeGoogle Scholar

Mersha, T. B. & Abebe, T. (2015) Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities. Human Genomics, 9(1), 1–15.Google Scholar

Morning, A. (2011) The nature of race. University of California Press. Kindle Edition.Google Scholar

Murdoch, S. (2007) IQ: A smart history of a failed idea. Wiley and Sons.Google Scholar

National Genome Research Institute (2018) Frequently asked questions about genetic and genomic science. https://bit.ly/384l9BOGoogle Scholar

National Oceanic and Atmospheric Administration (NOAA) (2021) How many oceans are there? https://oceanservice.noaa.gov/facts/howmanyoceans.htmlGoogle Scholar

Nisbett, R. E. (2005) Heredity, environment, and race differences in IQ: a commentary on Rushton and Jensen. Psychology, Public Policy, and Law, 11(2), 302–310.Google Scholar

Nisbett, R. E. (2009) Intelligence and how to get it. W. W. Norton.Google Scholar

Olson, S. (2002) Mapping human history. Houghton Mifflin.Google Scholar

Omi, M. & Winant, H. (2014) Racial formation in the United States. Routledge.Google Scholar

Panofsky, A., Dasgupta, K., & Iturriaga, N. (2021) How white nationalists mobilize genetics: from genetic ancestry and human biodiversity to counterscience and metapolitics. American Journal of Physical Anthropology, 75, 387–398. https://doi.org/10.1002/ajpa.24150Google Scholar

Roberts, D. (2011) Fatal invention. The New Press.Google Scholar

Romualdi, C., Balding, D., Nasidze, I. et al. (2002) Patterns of human diversity, within and among continents, inferred from biallelic DNA polymorphisms. Genome Research, 12(4), 602–612. DOI: 10.1101/gr.214902Google Scholar

Rotimi, C. N. (2004) Are medical and nonmedical uses of large-scale genomic markers conflating genetics and “race”? Nature Genetics, 36, S43–S47. https://doi.org/10.1038/ng1439Google Scholar

Rutherford, A. (2017) A brief history of everyone who ever lived: the human story retold through our genes. Experiment.Google Scholar

Rutherford, A. (2020) How to argue with a racist: what our genes do (and don’t) say about human difference. Weidenfeld and Nicolson.Google Scholar

Schuster, S., Miller, W., Ratan, A. et al. (2010) Complete Khoisan and Bantu genomes from southern Africa. Nature, 463, 943–947. https://doi.org/10.1038/nature08795Google Scholar

Shenk, David (2010) The genius in all of us. Doubleday.Google Scholar

Smedley, A. & Smedley, B. D. (2005) Race as biology is fiction, racism as a social problem is real: anthropological and historical perspectives on the social construction of race. American Psychologist, 60(1), 16–26.Google Scholar

Sternberg, R. J. (2021) Rethinking intelligence. New Scientist, 249(3317), 39. www.newscientist.com/article/mg24933174-700-weve-got-intelligence-all-wrong-and-thats-endangering-our-future/Google Scholar

Sternberg, R. J., Grigorenko, E. L., & Kidd, K. K. (2005) Intelligence, race, and genetics. American Psychologist, 60(1), 46–59.Google Scholar

Sussman, R. (2014) The myth of race: the troubling persistence of an unscientific idea. Harvard University Press.Google Scholar

Suzuki, L. & Aronson, J. (2005) The cultural malleability of intelligence and its impact on the racial/ethnic hierarchy. Psychology, Public Policy and Law, 11(2), 320–327.Google Scholar

Tattersall, I. & DeSalle, R. (2011) Race? Debunking a scientific myth. Texas A&M Press.Google Scholar

Templeton, A. R. (1998) Human races: a genetic and evolutionary perspective. American Anthropologist, 100(3), 632–650. https://doi.org/10.1525/aa.1998.100.3.632Google Scholar

Templeton, A. R. (2013) Biological races in humans. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 44(3), 262–271.Google Scholar

Tishkoff, S. & Kidd, K. (2004) Implications of biogeography of human populations for “race” and medicine. Nature Genetics, 36, S21–S27. https://bit.ly/3guqup1Google Scholar

Track and Field News (n.d.) History of Olympic results: high jump – men https://trackandfieldnews.com/olympic-results/history-of-olympic-results-high-jump-men/Google Scholar

Trahan, L. H. & Stuebing, K. K. (2014) The Flynn effect: a meta-analysis. Psychological Bulletin, 140(5), 1332–1360. https://doi.org/10.1037/a0037173Google Scholar

Vick, A. D. & Burris, H. H. (2017) Epigenetics and health disparities. Current Epidemiology Reports, 4(1), 31–37.Google Scholar

Wagner, J. K., Yu, J.-H., Ifekwunigwe, T. M. et al. (2017) Anthropologists’ views on race, ancestry, and genetics. American Journal of Physical Anthropology, 162 (2), 318–327.Google Scholar

Wells, S. 2002. The journey of man. Princeton University Press.Google Scholar

Wicherts, J. M., Borsboom, D., & Dolan, C. V. (2010) Why national IQs do not support evolutionary theories of intelligence. Personality and Individual Differences, 48 (2), 91–96.Google Scholar

Williams, D. R., Lawrence, J. A., & Davis, B. A. (2019) Racism and health: evidence and needed research. Annual Review of Public Health, 40(1), 105–125.Google Scholar

Williams, D. R. & Sternthal, M. (2010) Understanding racial-ethnic disparities in health: sociological contributions. Journal of Health and Social Behavior, 51 (S1), s15–s27. https://doi.org/10.1177/0022146510383838Google Scholar

Williams, J. E. (2016) Decoding racial ideology in genomics. Lexington Books.Google Scholar

Witzig, R. (1996) The medicalization of race: scientific legitimization of a flawed social construct. Annals of Internal Medicine, 125 (8) 675–679.Google Scholar

World Health Organization (WHO) (2006) Sickle-cell anemia: report by the secretariat. https://bit.ly/3gtLNHlGoogle Scholar

Wrigley-Field, E. (2020) U.S. racial inequality may be as deadly as COVID-19. Proceedings of the National Academies of Sciences, 117(36), 21854–21856.Google Scholar

Yearby, R. (2018) Racial disparities in health status and access to healthcare: the continuation of inequality in the united states due to structural racism. American Journal of Economics and Sociology, 77, 1113–1152. https://doi.org/10.1111/ajes.12230Google Scholar

Yearby, R. (2021) Race based medicine, colorblind disease: how racism in medicine harms us all. The American Journal of Bioethics, 21(2), 19-27– https://doi.org/10.1080/15265161.2020.1851811Google Scholar

Yudell, M., Roberts, D., DeSalle, R. et al. (2016) Taking race out of human genetics. Science, 351(6273), 564–565. https://bit.ly/2O2bdzGGoogle Scholar