Correction is an important element of scientific progress. In the history of scientific investigations, it has been common for widely-accepted ideas to be overturned. Literature contains many instances of such self-correction, though the corrections are sometimes not as widely known as the original findings. Here, we catalog some corrections, all of which are instances science can be proud of. Investigators are invited to submit to us more such examples to be listed here and to illustrate more instances in which science was successfully self-correcting.
Shooter Video Games and Effect on Firing Aim and Accuracy:
Whitaker and Bushman argue that playing violent video games with a pistol-shaped control can increase firing accuracies. This paper has been retracted by Communication Research due to irregularities in some variables in the data set. A replication of the study by Dr. Bushman is in review.
Whitaker, J.L. & Bushman, B.J. (2012). “Boom, Headshot!” Effect of Video Game Play and Controller Type on Firing Aim and Accuracy Communication Research, 41(7), 879-891.
(2016). Dispute over shooter video games may kill recent paper
Attitude Importance and Attitude Accessibility:
Roese and Olson argue that attitude importance and accessibility are intrinsically linked and that accessibility indicates importance; if an attitude is easily accessible to an individual then it is also important to him or her. Bizer and Krosnick take issue with that assertion, demonstrating that, with regard to a particular attitude, either accessibility or importance can exist without the other. They also found that attitude importance does influence accessibility, but accessibility does not necessarily determine importance.
Roese, N.J., & Olson, J.M. (1994). Attitude importance as a function of repeated attitude expression. Journal of Experimental Social Psychology, 30, 39-51.
Bizer, G.Y., & Krosnick, J. A. (2001). Exploring the structure of strength-related attitude features: Between attitude importance and attitude accessibility. Journal of Personality and Social Psychology, 81, 566-586.
In 1964, after the brutal murder of Catherine “Kitty” Genovese, the New York Times published an article reporting that thirty-seven of Genovese’s neighbors witnessed the attack and did nothing, failing to either intervene or call the police. In response, many researchers published articles on the Bystander Effect, claiming that the presence of multiple observers of a situation leads to a diffusion of responsibility, making each person less likely to involve him or herself in that situation, even if it means helping someone who needs it. In recent years, however, scholars have questioned the Bystander Effect as well the veracity of the Kitty Genovese story itself. In reality, very few neighbors witnessed her murder, and several people who were witnesses did call the police or attempt to help Genovese. Research has shown that in dangerous or life-threatening situations, bystanders are willing to help a victim even if they are part of a large group.
Darley, J.M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 8(4), 377-383.
Gansberg, M. (1964, March 27). 37 who saw murder didn’t call the police. The New York Times, pp. 1, 38.
Latané, B., & Darley, J.M. (1968). Group inhibition of bystander intervention in emergencies. Journal of Personality and Social Psychology,10(3), 215-221.
Latané, B., & Darley, J.M. (1969). Bystander “apathy.” American Scientist, 57(2), 244-268.
Latané, B., & Nida, S. (1981). Ten years of research on group size and helping. Psychological Bulletin, 89(2), 308-324.
Rosenthal, A.M. (1964, May 3). Study of the sickness called apathy. The New York Times, pp. 24, 66, 69, 70, 72).
Rosenthal, A.M. (1999). Thirty-eight witnesses: The Kitty Genovese case. Brooklyn, NY: Melville House Publishing.
Cook, K. (2014). Kitty Genovese: The murder, the bystanders, the crime that changed America. New York, NY: W. W. Norton & Company.
Fischer, P., Krueger, J.I, Greitemeyer, T., Vogrincic, C., Kastenmüller, A., Frey, D., … Kainbacher, M. (2011). The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. Psychological Bulletin, 137(4), 517-537.
Lemann, N. (2014, March 10). A call for help: What the Kitty Genovese story really means. The New Yorker, 73-77.
Manning, R., Levine, M., & Collins, A. (2007). The Kitty Genovese murder and the social psychology of helping: The parable of the 38 witnesses. American Psychologist, 62(6), 555-562.
The Name-Order Effect refers to the theory that political candidates whose names are listed first on the ballot are given an unfair advantage, as they receive more votes than they would have if they were not listed first. Ho and Imai argue that the Name-Order effect is largely insignificant, mostly holding true only for minor party candidates and in nonpartisan elections. Alvarez et al also emphasize that the Name-Order Effect is small where it exists. In some cases, they find that there is actually a negative effect on candidates’ vote shares if they are listed first or last on the ballot. Pasek et al, however, reaffirm the significance of the Name-Order Effect, arguing that it is sizable enough to impact elections.
Ho, D.E., & Imai K. (2008). Estimating causal effects of ballot order from a randomized natural experiment: The California Alphabet Lottery, 178-2002. Public Opinion Quarterly, 72 (2), 216-240.
Ho, D.E., & Imai K. (2006). Randomization inference with natural experiments: An analysis of ballot effects in the 2003 California recall election. Journal of the American Statistical Association, 101 (475), 888-900.
Alvarez, R.M., Sinclair, B., & Hasen R.L. (2006). How much is enough? The “Ballot Order Effect” and the use of social science research in election law disputes. Election Law Journal, 5 (1), 40-56.
Pasek, J., Schneider, D., Krosnick, J.A., Tahk, A., Ophir, E., & Milligan, C. (2014). Prevalence and moderators of the candidate Name-Order Effect: Evidence from statewide general elections in California. Public Opinion Quarterly, 78 (2), 416-439.
Gateway Belief Model:
The Gateway Belief Model (GBM) describes a process of attitudinal change where a shift in people’s perception of the scientific consensus on an issue leads to subsequent changes in their attitudes which in turn predict changes in support for public action. According to the original study called,”The Scientific Consensus on Climate Change as a Gateway Belief: Experimental Evidence,” by van der Linden and others, advising study subjects that “97% of climate scientists have concluded that human-caused climate change is happening” induces subjects to revise upward their own estimate of the proportion of scientists who subscribe to this position.
The GBM has been contested by many other researchers since the original study’s publication. One of the most prominent contesters is by Kahan in his work, “The ‘Gateway Belief’ Illusion: Reanalyzing the Results of a Scientific Consensus Messaging Study.” Kahan insists that “the point of [his] paper was not to determine which position is correct on the use of consensus messaging. It was only to assure that scholars would have access to all the data collected” in regards to the work by van der Linden and his colleagues.
Another study by Kerr and Wilson also contests the original study supporting the GBM. In “Perceptions of Scientific Consensus Do Not Predict Later Beliefs about the Reality of Climate Change: A Test of the Gateway Belief Model Using Cross-lagged Panel Analysis,” Kerr and Wilson find the opposite results then the original study, positing “results suggest that individuals’ perceptions of a consensus among scientists do not have a strong influence on their personal beliefs about climate change.”
While van der Linden and his colleagues have subsequently done large scale replications of the original study in “The gateway belief model: A large-scale replication,” many researchers continue to disconfirm the GBM and view it as an ‘illusion.’
van der Linden, S.L., Leiserowitz, A.A., Feinberg, G.D., & Maibach, E.W. (2015). “The Scientific Consensus on Climate Change as a Gateway Belief: Experimental Evidence.” PLOS One.
Kahan, D.M. (2017). “The ‘Gateway Belief’ Illusion: Reanalyzing the Results of a Scientific consensus Messaging Study.” Journal of Science Communication 16(5): 1—20.
Kerr, J.R. & Wilson, M.S. (2018). “Perceptions of Scientific Consensus Do Not Predict Later Beliefs about the Reality of Climate Change: A Test of the Gateway Belief Model Using Cross-lagged Panel Analysis.” Journal of Environmental Psychology 59: 107-110.
van der Linden, S.L., Leiserowitz, A.A., Feinberg, G.D., & Maibach, E.W. (2019). “The gateway belief model: A large-scale replication.” Journal of Environmental Psychology 62.
van der Linden, S.L., Leiserowitz, A.A., Feinberg, G.D., & Maibach, E.W. (2017). “Gateway Illusion or Cultural Cognition Confusion?” Journal of Science Communication 16(5).
Leber, R. (2015). “Meet the 97 Percent Climate Truthers.” The New Republic.
Mooney, C. (2019). “Researchers Think They’ve Found a ‘Gateway Belief’ That Leads to Greater Science Acceptance.” The Washington Post, WP Company.
van der Linden, S. (2015). “How to Combat Distrust of Science.” Scientific American, Scientific American.