2,976
Views
2
CrossRef citations to date
0
Altmetric
Articles

‘Looking back, i wouldn’t join up again’: the lived experiences of police officers as victims of bias and prejudice perpetrated by fellow staff within an english police force

Pages 33-48 | Received 11 Nov 2017, Accepted 03 Aug 2018, Published online: 25 Sep 2018
 

ABSTRACT

Women, ethnic minority and LGB police officers often experience prejudice, disadvantage and exclusion within police forces because of their perceived ‘otherness’ in a predominantly white, heterosexual, male organisation. In the context of an increasingly diverse service, the paper argues that the concept of intersectionality is important in order to understand the experiences of police officers who encounter bias and prejudice because of their multiple, intersecting identities. Drawing on data from qualitative interviews with 20 individuals based in an English police force, the paper examines their occupational experiences of bias, discrimination and exclusion perpetrated by their colleagues and supervisors. Utilising the ‘exit, voice and loyalty’ model, the paper analyses how police officers are affected by, and respond to these experiences. Taken together, these arguments lay the foundation for future work to further understand the experiences of police officers as victims of bias and prejudice due to their multiple, intersecting identities.

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Irene Zempi

Dr Irene Zempi biography is a Lecturer in Criminology, Department of Sociology, Nottingham Trent University.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 241.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.