Show simple item record

dc.contributor.authorPaolillo, Christine M.
dc.description.abstractGender bias—giving preferences to men over women—is a societal issue that affects the day-to-day lives of individuals in the workforce. This is especially true in the police force, where gender bias influences the recruitment of officers, interpersonal relations in the workplace, wage levels, and career trajectories. The objective of this study was to further explore the perception of bias that retired women who work in the police force feel had been levied against them by the organization and/or colleagues. In this qualitative, phenomenological study, women of all ranks on the force, including both uniform and civilian employees, in an urban police department in the Northeast were interviewed through purposeful sampling. Using thematic analysis, key themes from the interviews were identified that showed women on the force often experience gender bias in the form of: (a) gendered liabilities, (b) inequalities despite rank, and (c) gender-based strategies. Moreover, other themes are related to leadership, discrimination, and future needs to address gender bias in police departments were found and include: (a) discrimination longevity, (b) leadership issues, (c) women vs. women, and (d) gender mentoring and networking. The findings of this study can help generate new perspectives on how gender bias affects women in urban police departments and possibly provide a template to help these organizations redesign their culture to be more gender inclusive.en_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.subjectGender biasen_US
dc.subjectWomen in policingen_US
dc.titleGender Bias Against Women in Policing: Is It Perception or a Reality?en_US
dc.typeDissertationen_US University of Seattleen_US of Educationen_US
cityu.schoolSchool of Education and Leadershipen_US
cityu.siteSeattleen_US Statesen_US

Files in this item


This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States