Police culture, discourse, and the construction of Canadian police officers’ identity
Bibliographic record
Abstract
Canadian police officers work within a deeply rooted and unique police culture that remains anchored to traditional occupational norms and values often resistant to change. Yet, policing is under pressure from elected officials and the public to meet changing social realities and public expectations. Inevitably, officers experience an identity crisis when they feel the strong and persistent pull of their tradition-bound culture while their services attempt to be more inclusive and progressive. Utilizing critical discourse analysis (CDA) and specifically Fairclough’s dialectical-relations approach, this study explores how identity is constructed and reinforced through discourse within and by police culture to create the idea of what it means to be a cop. Using data from an analysis of semi-structured interviews with 30 currently serving police officers in four Canadian police services, it considers how the language of policing (verbal, written, visual) is used to construct police identity. The data show that through the use of police-specific discourse prior to, during, and after recruitment, police culture retains an all-powerful hold on officers’ identity construction before and during recruitment and throughout their careers. It also represents a barrier to more equitable and inclusive police organizations. Finally, this study explores areas such as training, recruitment, and warrior/guardian debate where change should be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".