“The Top Cop”: Understanding Correctional Officer Recruits’ Motivations Towards Correctional Emergency Response Team Membership
Bibliographic record
Abstract
Correctional officer recruits (CORs) must complete the correctional training program (CTP) mandated by Correctional Service Canada (CSC), in preparation for the plethora of occupational responsibilities they will be tasked with in their occupational role of correctional officer (CO). During training, recruits continue to conceive ideas about their career trajectories. Previous research exploring CO or COR motivations has focused largely on occupational entry and their underlying intrinsic and extrinsic motivations. Little empirical evidence examines the general occupational directions or desires of CORs exiting CTP, particularly their interest in future Correctional Emergency Response Team (CERT) membership. The current study relies on data from interviews with 36 CORs who expressed interest in CERT membership before employment at a federal penitentiary. Findings suggest that these CORs are drawn to CERT membership due to previous occupational interests, media representations of CERT/ERT, but also experience challenges in acquiring membership related to CERT culture, social relationships, and gender. We conclude the article with considerations for recruitment and retention of COs as it relates to CERT membership for Canadian federal correctional services.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".