Conceptualization of moral injury: A socio-cognitive perspective
Bibliographic record
Abstract
LAY SUMMARY This article looks at how moral injury (MI) may develop by considering what event features may be especially salient and cause MI and what experiences an individual may have after an event that might lead to the occurrence of a MI. It proposes that the beliefs someone has about themselves, others, and the world can be shaped by experiences in childhood and early life. Once an individual has experienced a potentially morally injurious event (PMIE) — for example, witnessing something that violates deeply held moral or ethical codes but being unable to stop it, doing something that violates these ethical codes, or experiencing a significant betrayal — they may try to make sense of it by changing the way they see the world, themselves, and others. This can lead to problems in the individual’s relationship with themselves and others, leading to feelings of shame and guilt and withdrawal from other people. Finally, for an event to be a PMIE, it must significantly challenge strongly held moral beliefs and a sense of right and wrong.
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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 | 0.001 | 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".