The Language of Authority: Swearing, Prisonization, and Words Behind the Wall for the Correctional Officer
Bibliographic record
Abstract
Words are integral to human communication across social interactions. In the current study, we examine how the language of swearing is used in Canadian federal prisons to understand how correctional officers (COs) socialize and deliver human service. We seek to add to the body of literature suggesting COs experience the effects of prisonization, as we find nuance in how prison swearing for COs is a unique aspect of their work environment, integral to the norms of prison society, but concurrently, socially and professionally purposeful. We highlight how swearing – often dismissed as deviant – functions as an intentional, context-dependent communication strategy embedded within CO relationships in prison. Findings suggest swearing serves to manage stress, signal belonging, assert authority, and express masculinities, while also producing unintended disruptive effects on Canada’s national correctional officer workforce. We argue that swearing, as a normalized yet misunderstood form of profanity, plays a critical role in rapport building and human service delivery in correctional environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".