Conducting research on nonsuicidal self-injury in schools: Ethical considerations and recommendations
Bibliographic record
Abstract
Research on nonsuicidal self-injury (NSSI) has grown significantly over the last 15 years, with much of this work focused on factors that initiate and maintain NSSI among school-aged youth. Although this work is important, it does raise several ethical concerns. In this article we outline key ethical issues underlying NSSI research in schools and offer recommendations for conducting ethically sound and productive research in this area. Ethical concerns addressed include: 1) recruitment of minors to research; 2) disclosure and confidentiality; 3) the risk of iatrogenic effects; 4) duty of care; 5) engaging schools in research; and 6) safety of the researchers. In each area, we offer recommendations to assist researchers, ethics committees, and schools in working together to conduct ethical NSSI research, further our understanding of NSSI, and address and respond to these behaviors in schools.
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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 | 0.498 | 0.626 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.018 | 0.029 |
| Open science | 0.009 | 0.013 |
| Research integrity | 0.035 | 0.040 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".