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Grossmann I, Rotella A, Hutcherson CA, Sharpinskyi K, Varnum MEW, Achter S, Dhami MK, Guo XE, Kara-Yakoubian M, Mandel DR, Raes L, Tay L, Vie A, Wagner L, Adamkovic M, Arami A, Arriaga P, Bandara K, Baník G, Bartoš F, Baskin E, Bergmeir C, Białek M, Børsting CK, Browne DT, Caruso EM, Chen R, Chie BT, Chopik WJ, Collins RN, Cong CW, Conway LG, Davis M, Day MV, Dhaliwal NA, Durham JD, Dziekan M, Elbaek CT, Shuman E, Fabrykant M, Firat M, Fong GT, Frimer JA, Gallegos JM, Goldberg SB, Gollwitzer A, Goyal J, Graf-Vlachy L, Gronlund SD, Hafenbrädl S, Hartanto A, Hirshberg MJ, Hornsey MJ, Howe PDL, Izadi A, Jaeger B, Kačmár P, Kim YJ, Krenzler R, Lannin DG, Lin HW, Lou NM, Lua VYQ, Lukaszewski AW, Ly AL, Madan CR, Maier M, Majeed NM, March DS, Marsh AA, Misiak M, Myrseth KOR, Napan JM, Nicholas J, Nikolopoulos K, O J, Otterbring T, Paruzel-Czachura M, Pauer S, Protzko J, Raffaelli Q, Ropovik I, Ross RM, Roth Y, Røysamb E, Schnabel L, Schütz A, Seifert M, Sevincer AT, Sherman GT, Simonsson O, Sung MC, Tai CC, Talhelm T, Teachman BA, Tetlock PE, Thomakos D, Tse DCK, Twardus OJ, Tybur JM, Ungar L, Vandermeulen D, Vaughan Williams L, Vosgerichian HA, Wang Q, Wang K, Whiting ME, Wollbrant CE, Yang T, Yogeeswaran K, Yoon S, Alves VR, Andrews-Hanna JR, Bloom PA, Boyles A, Charis L, Choi M, Darling-Hammond S, Ferguson ZE, Kaiser CR, Karg ST, Ortega AL, Mahoney L, Marsh MS, Martinie MFRC, Michaels EK, Millroth P, Naqvi JB, Ng W, Rutledge RB, Slattery P, Smiley AH, Strijbis O, Sznycer D, Tsukayama E, van Loon A, Voelkel JG, Wienk MNA, Wilkening T. Insights into the accuracy of social scientists' forecasts of societal change. Nat Hum Behav 2023; 7:484-501. [PMID: 36759585 PMCID: PMC10192018 DOI: 10.1038/s41562-022-01517-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 12/19/2022] [Indexed: 02/11/2023]
Abstract
How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data.
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Kurdoglu RS, Jekel M, Ateş NY. Eristic reasoning: Adaptation to extreme uncertainty. Front Psychol 2023; 14:1004031. [PMID: 36844329 PMCID: PMC9947153 DOI: 10.3389/fpsyg.2023.1004031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 01/23/2023] [Indexed: 02/11/2023] Open
Abstract
Heuristics (shortcut solution rules) can help adaptation to uncertainty by leading to sufficiently accurate decisions with little information. However, heuristics would fail under extreme uncertainty where information is so scarce that any heuristic would be highly misleading for accuracy-seeking. Thus, under very high levels of uncertainty, decision-makers rely on heuristics to no avail. We posit that eristic reasoning (i.e., self-serving inferences for hedonic pursuits), rather than heuristic reasoning, is adaptive when uncertainty is extreme, as eristic reasoning produces instant hedonic gratifications helpful for coping. Eristic reasoning aims at hedonic gains (e.g., relief from the anxiety of uncertainty) that can be pursued by self-serving inferences. As such, eristic reasoning does not require any information about the environment as it instead gets cues introspectively from bodily signals informing what the organism hedonically needs as shaped by individual differences. We explain how decision-makers can benefit from heuristic vs. eristic reasoning under different levels of uncertainty. As a result, by integrating the outputs of formerly published empirical research and our conceptual discussions pertaining to eristic reasoning, we conceptually criticize the fast-and-frugal heuristics approach, which implies that heuristics are the only means of adapting to uncertainty.
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Affiliation(s)
- Rasim Serdar Kurdoglu
- Faculty of Business Administration, Bilkent University, Ankara, Turkey,*Correspondence: Rasim Serdar Kurdoglu,
| | - Marc Jekel
- Faculty of Human Sciences, University of Cologne, Cologne, Germany,Marc Jekel,
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Stelter M, Essien I, Sander C, Degner J. Racial Bias in Police Traffic Stops: White Residents' County-Level Prejudice and Stereotypes Are Related to Disproportionate Stopping of Black Drivers. Psychol Sci 2022; 33:483-496. [PMID: 35319309 DOI: 10.1177/09567976211051272] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Racial disparities in policing are well documented, but the reasons for such disparities are often debated. In the current research, we weighed in on this debate using a regional-level bias framework: We investigated the link between racial disparities in police traffic stops and regional-level racial bias, employing data from more than 130 million police traffic stops in 1,413 U.S. counties and county-level measures of racial bias from more than 2 million online respondents. Compared with their population share in county demographics, Black drivers were stopped at disproportionate rates in the majority of counties. Crucially, disproportionate stopping of Black drivers was higher in counties with higher levels of racial prejudice by White residents (rs = .07-.36). Furthermore, county-level aggregates of White people's threat-related stereotypes were less consistent in predicting disproportionate stopping (rs = .00-.19). These observed relationships between regional-level bias and racial disparities in policing highlight the importance of the context in which police operate.
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Affiliation(s)
- Marleen Stelter
- Social Psychology Department, Universität Hamburg.,Institute of Psychology, FernUniversität in Hagen
| | - Iniobong Essien
- Institute of Psychology, FernUniversität in Hagen.,Department of Social and Organisational Psychology of Social Work, Leuphana Universität Lüneburg
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Abstract
It is often claimed that only experiments can support strong causal inferences and therefore they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments results in their overuse both by researchers and decision makers and in an underappreciation of their shortcomings. Neglect of other methods often follows. Experiments can suggest whether X causes Y in a specific experimental setting; however, they often fail to elucidate either the mechanisms responsible for an effect or the strength of an effect in everyday natural settings. In this article, we consider two overarching issues. First, experiments have important limitations. We highlight problems with external, construct, statistical-conclusion, and internal validity; replicability; and conceptual issues associated with simple X causes Y thinking. Second, quasi-experimental and nonexperimental methods are absolutely essential. As well as themselves estimating causal effects, these other methods can provide information and understanding that goes beyond that provided by experiments. A research program progresses best when experiments are not treated as privileged but instead are combined with these other methods.
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Affiliation(s)
- Ed Diener
- Department of Psychology, University of Utah.,Department of Psychology, University of Virginia.,Gallup, Washington, D.C
| | - Robert Northcott
- Department of Philosophy, Birkbeck College, University of London
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