“The Public Doesn’t Understand”: The Self-reinforcing Interplay of Image Discrepancies and Political Ideologies in Law Enforcement

Drawing on information processing theory, I revisit prior assumptions that not being understood raises challenges for employees, examining how political ideologies powerfully affect how employees who serve the public react to a perceived lack of understanding of the difficulties of their jobs. Using...

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Bibliographic Details
Main Author: Patil, S.V (Author)
Format: Article
Language:English
Published: SAGE Publications Ltd 2019
Subjects:
Online Access:View Fulltext in Publisher
Description
Summary:Drawing on information processing theory, I revisit prior assumptions that not being understood raises challenges for employees, examining how political ideologies powerfully affect how employees who serve the public react to a perceived lack of understanding of the difficulties of their jobs. Using independent expert ratings of 794 body camera videos of 164 police officers across two agencies, I show that a lack of perceived public understanding decreases task performance for liberal-leaning officers but not for conservative-leaning officers. Because liberal-leaning officers seek to form more communal relationships with the public, a perceived lack of public understanding violates their sense of social order, but it merely reaffirms conservative-leaning officers’ beliefs in maintaining an authoritarian distance given the responsibilities and duties they shoulder. I replicate these results using supervisors’ ratings of 82 officers across four agencies and then demonstrate in a time-lagged survey of 184 officers in a single agency that those with stronger conservative beliefs are more likely to believe the public fails to appreciate the difficulties of their jobs. These studies highlight the importance of accounting for people’s beliefs in whether image conflicts should and do arise—and provide insights into the self-reinforcing forces that sustain divides between employees and those they serve. © The Author(s) 2018.
ISBN:00018392 (ISSN)
DOI:10.1177/0001839218783988