Moral injury and the need to carry out ethically responsible research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The need for research to advance scientific understanding must be balanced with ensuring the rights and wellbeing of participants are safeguarded, with some research topics posing more ethical quandaries for researchers than others. Moral injury is one such topic. Exposure to potentially morally injurious experiences can lead to significant distress, including post-traumatic stress disorder (PTSD), depression, and selfinjury. In this article, we discuss how the rapid expansion of research in the field of moral injury could threaten the wellbeing, dignity and integrity of participants. We also examine key guidance for carrying out ethically responsible research with participants’ rights to self-determination, confidentiality, non-maleficence and beneficence discussed in relation to the study of moral injury. We describe how investigations of moral injury are likely to pose several challenges for researchers including managing disclosures of potentially illegal acts, the risk of harm that repeated questioning about guilt and shame may pose to participant wellbeing in longitudinal studies, as well as the possible negative impact of exposure to vicarious trauma on researchers themselves. Finally, we offer several practical recommendations that researchers, research ethics committees and other regulatory bodies can take to protect participant rights, maximise the potential benefits of research outputs and ensure the field continues to expand in an ethically responsible way.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.018 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 it