If it didn’t screw me up, I’d be screwed up: Moral injury and moral labour in Canadian federal parole
Bibliographic record
Abstract
The aim of this article is to develop knowledge on how moral challenges affect officers’ well-being and professional performance. Building on existing research on adverse work experiences and the developing literature on moral injury, we examine 150 Canadian federal parole officers’ experiences of moral distress at work as distinct from traumatic stress and emotional stress. We unpack the process of how officers experience and manage moral distress and its aftermath in interaction with their social, organizational, and professional context. Our findings are crucial for addressing PPOs’ adverse work experiences, and for recognizing barriers to supporting clients’ rehabilitation and reintegration in penal settings. Therefore, we suggest a conceptualization specific to the moral aspects of challenges at work – moral labour – to further theorize and examine the relationship between moral distress at work, contextual conditions for managing the distress, and adverse work outcomes such as moral injury, burnout, and compassion fatigue.
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".