Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Sociology

Supervisor

Adams, Tracey L.

2nd Supervisor

Livingstone, David W.

Affiliation

University of Toronto

Joint Supervisor

Abstract

Individuals do not always follow the rules at work, yet it is not entirely clear what conditions generally contribute to higher rates of misbehaviour. Much of the research on organizational misbehaviour is ethnographic or based on limited sample populations (single organization, single industry, etc.), so there remains a gap in the literature for findings representative of a wider population and comparison across occupational classes. Additionally, there has been an over-emphasis on the study of misbehaviour by employees, while employer misbehaviour remains relatively unexplored within the literature. Organizational misbehaviour is also often treated as an objective act with little recognition for how individual attitudes and structural position shape perceptions of what constitutes ‘proper’ behavior and, in turn, misbehaviour. This dissertation reconnects the study of organizational misbehaviour with Marxist class analysis and examines the connection between the structural conditions of work and employee and employer misbehaviour, also incorporating a study of how individual reporting of misbehaviour frequency is influenced by respondent class consciousness. Each integrated chapter uses nationally representative data for Canada from the 2016 Changing Workplaces in a Knowledge Economy (CWKE) survey (N=3007). Methods utilized include chi-square, gamma and ordinary least squares (OLS) regression. Findings contribute to a growing section of the literature focused on identifying the structural determinants of organizational misbehaviour, examine the link between individual subjectivity and perceptions of misbehaviour frequency and provide unique initial exploratory research into the phenomenon of employer misbehaviour.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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