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Record W2913357982 · doi:10.1177/0143034319827056

Conducting research on nonsuicidal self-injury in schools: Ethical considerations and recommendations

2019· article· en· W2913357982 on OpenAlex
Penelope Hasking, Stephen P. Lewis, Kealagh Robinson, Nancy L. Heath, Marc Wilson

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSchool Psychology International · 2019
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill UniversityUniversity of Guelph
Fundersnot available
KeywordsConfidentialityPsychologyDutyWork (physics)Research ethicsHuman factors and ergonomicsEthical issuesSuicide preventionPoison controlOccupational safety and healthEngineering ethicsMedical educationMedicinePolitical sciencePsychiatryMedical emergencyEngineering

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0130.005

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.

Opus teacher head0.213
GPT teacher head0.510
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it