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How race affects evidence accumulation during the decision to shoot

Overview of attention for article published in Psychonomic Bulletin & Review, October 2017
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Title
How race affects evidence accumulation during the decision to shoot
Published in
Psychonomic Bulletin & Review, October 2017
DOI 10.3758/s13423-017-1369-6
Pubmed ID
Authors

Timothy J. Pleskac, Joseph Cesario, David J. Johnson

Abstract

The biasing role of stereotypes is a central theme in social cognition research. For example, to understand the role of race in police officers' decisions to shoot, participants have been shown images of Black and White males and instructed to shoot only if the target is holding a gun. Findings show that Black targets are shot more frequently and more quickly than Whites. The decision to shoot has typically been modeled and understood as a signal detection process in which a sample of information is compared against a criterion, with the criterion set for Black targets being lower. We take a different approach, modeling the decision to shoot as a dynamic process in which evidence is accumulated over time until a threshold is reached. The model accounts for both the choice and response time data for both correct and incorrect decisions using a single set of parameters. Across four studies, this dynamic perspective revealed that the target's race did not create an initial bias to shoot Black targets. Instead, race impacted the rate of evidence accumulation with evidence accumulating faster to shoot for Black targets. Some participants also tended to be more cautious with Black targets, setting higher decision thresholds. Besides providing a more cohesive and richer account of the decision to shoot or not, the dynamic model suggests interventions that may address the use of race information in decisions to shoot and a means to measure their effectiveness.

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The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 20%
Student > Bachelor 13 13%
Researcher 12 12%
Student > Doctoral Student 10 10%
Student > Master 9 9%
Other 17 17%
Unknown 19 19%
Readers by discipline Count As %
Psychology 44 44%
Medicine and Dentistry 5 5%
Social Sciences 5 5%
Computer Science 4 4%
Decision Sciences 4 4%
Other 18 18%
Unknown 20 20%