Article 4: Correctional Work, Wellbeing, And Mental Health Disorders
Bibliographic record
Abstract
Correctional Services Canada (CSC) employees include those working in institutional corrections (e.g., correctional officers in prisons), community corrections (e.g., community parole officers), and administrative corrections (e.g., employees in regional or national headquarters). Correctional workers appear at elevated risk for mental disorders, due in part to exposures to potentially traumatic events and chronic occupational stress. Correctional worker experiences appear linked to mental health disorders including depression, posttraumatic stress disorder (PTSD), and anxiety. Data were gathered in 2016 from 1,115 correctional service workers across diverse occupation categories as part of a larger study. Previous results with the full dataset that included provincial, territorial, and federal correctional workers, indicated that correctional workers’ mental health were compromised; however, all correctional workers were analyzed collectively, despite potentially critical occupational differences. Here we provide a more nuanced examination of wellbeing across different CSC worker categories, a subset of the full dataset, by assessing self-reported prevalence of mental health disorder diagnoses, positive screenings consistent with mental health disorders, and mental health disorder correlates. The current results indicated no statistically significant differences between CSC categories, though workers in operational community positions reported fewer difficulties with mental health than those in other categories, and comparable screening percentages relative to other correctional workers. Being married or common law was associated with a lower probability of a mental health disorder; whereas working for 16+ years was associated with a higher probability. The results indicate high mental health disorder prevalence rates among all correctional worker categories, emphasizing a critical need for empirically-based interventions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".