| Literature DB >> 34928473 |
Vincenzo J Olivett1, David S March2.
Abstract
The role of implicit processes during police-civilian encounters is well studied from the perspective of the police. Decades of research on the "shooter bias" suggests that implicit Black-danger associations potentiate the perception of threat of Black individuals, leading to a racial bias in the decision to use lethal force. Left understudied are civilians' possible associations of police with danger and how such associations pervade behavior and explicit views of the police. The current work begins to address this gap. In two within-subjects studies, we separately assess police-threat (i.e., safety/danger) and police-valence (i.e., good/bad) associations as well as their relative influences on explicit perceptions of police. Study 1 revealed that implicit threat evaluations (police-danger associations) more strongly predicted negative explicit views of the police compared to implicit valence evaluations (police-negative associations). Study 2 replicated these findings and suggests that individuals evaluate the police as more dangerous versus negative when each response is pitted against each other within single misattribution procedure trials. The possible implications for explicit attitudes toward police reform and behavior during police-civilian encounters are discussed.Entities:
Keywords: Civilian; Danger; Police; Threat; Valence
Mesh:
Year: 2021 PMID: 34928473 PMCID: PMC8688646 DOI: 10.1186/s41235-021-00343-9
Source DB: PubMed Journal: Cogn Res Princ Implic ISSN: 2365-7464
Fig. 1Depiction of a single misattribution procedure trial
Fig. 2Mean dangerous versus safe and good versus bad evaluations by prime type
Results of regression analyses in Study 1 predicting POPS
| Predictor | Model 1 | Model 2 | Model 3 | |||
|---|---|---|---|---|---|---|
| Good/bad | − .85 | − 4.89, < .001 | – | – | − .27 | − 1.22, .224 |
| Safe/dangerous | – | – | − 1.02 | − 6.40, < .0001 | − .85 | − 3.98, < .001 |
b represents unstandardized regression coefficients
Fig. 3Mean danger versus negative evaluations by prime type