Meat in a Seat: A Grounded Theory Study Exploring Moral Injury in Canadian Public Safety Communicators, Firefighters, and Paramedics
Bibliographic record
Abstract
The work of public safety personnel (PSP) is inherently moral; however, the ability of PSP to do what is good and right can be impeded and frustrated, leading to moral suffering. Left unresolved, moral suffering may develop into moral injury (MI) and potential psychological harm. The current study was designed to examine if MI is relevant to frontline public safety communicators, firefighters, and paramedics. Semi-structured interviews (n = 3) and focus groups (n = 3) were conducted with 19 participants (public safety communicators (n = 2); paramedics (n = 7); and firefighters (n = 10)). Interviews and focus groups were audio-recorded, transcribed, coded, and constantly compared in accordance with the grounded theory method. A conceptual theory of “frustrating moral expectations” emerged, with participants identifying three interrelated properties as being potentially morally injurious: chronic societal problems, impaired systems, and organizational quagmires. Participants navigated their moral frustrations through both integrative and disintegrative pathways, resulting in either needing to escape their moral suffering or transforming ontologically. The current study results support MI as a relevant concept for frontline PSP. Given the seriousness of PSP leaving their profession or committing suicide to escape moral suffering, the importance of the impact of MI on PSP and public safety organizations cannot be ignored or underestimated. Understanding the similarities and differences of morally injurious exposures of frontline PSP may be critical for determining mental health and resilience strategies that effectively protect PSP.
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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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.037 | 0.022 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".