‘Against everything that got you into the job’: experiences of potentially morally injurious events among Canadian public safety personnel
Bibliographic record
Abstract
Background: Moral injury (MI) has become a research and organizational priority as frontline personnel have, both during and in the years preceding the COVID-19 pandemic, raised concerns about repeated expectations to make choices that transgress their deeply held morals, values, and beliefs. As awareness of MI grows, so, too, does attention on its presence and impacts in related occupations such as those in public safety, given that codes of conduct, morally and ethically complex decisions, and high-stakes situations are inherent features of such occupations.Objective: This paper shares the results of a study of the presence of potentially morally injurious events (PMIEs) in the lived experiences of 38 public safety personnel (PSP) in Ontario, Canada.Method: Through qualitative interviews, this study explored the types of events PSP identify as PMIEs, how PSP make sense of these events, and the psychological, professional, and interpersonal impacts of these events. Thematic analysis supported the interpretation of PSP descriptions of events and experiences.Results: PMIEs do arise in the context of PSP work, namely during the performance of role-specific responsibilities, within the organizational climate, and because of inadequacies in the broader healthcare system. PMIEs are as such because they violate core beliefs commonly held by PSP and compromise their ability to act in accordance with the principles that motivate them in their work. PSP associate PMIEs, in combination with traumatic experiences and routine stress, with adverse psychological, professional and personal outcomes.Conclusion: The findings provide additional empirical evidence to the growing literature on MI in PSP, offering insight into the contextual dimensions that contribute to the sources and effects of PMIEs in diverse frontline populations as well as support for the continued application and exploration of MI in the PSP context.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.020 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".