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Record W2070642882 · doi:10.1111/sltb.12058

Risk‐<scp>R</scp>elated and <scp>P</scp>rotective <scp>C</scp>orrelates of <scp>N</scp>onsuicidal <scp>S</scp>elf‐<scp>I</scp>njury and <scp>C</scp>o‐<scp>O</scp>ccurring <scp>S</scp>uicide <scp>A</scp>ttempts among <scp>I</scp>ncarcerated <scp>W</scp>omen

2013· article· en· W2070642882 on OpenAlexaff
Alexander L. Chapman, Kim L. Gratz, Brianna J. Turner

Bibliographic record

VenueSuicide and Life-Threatening Behavior · 2013
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCoping (psychology)Clinical psychologySexual abusePsychologyPhysical abuseSuicide preventionPoison controlMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Individual and environmental correlates of nonsuicidal self-injury (NSSI) and co-occurring suicide attempts (SA) among incarcerated women (N = 104) were examined. Participants completed measures of putative risk and protective factors, including coping styles, childhood maltreatment, and hopelessness. Results indicated that active coping was uniquely, negatively associated with the presence and frequency of NSSI, whereas avoidant coping and childhood physical/emotional abuse were positively associated with NSSI frequency. Conversely, among women with a history of NSSI, hopelessness was uniquely, positively associated with the presence and frequency of SA. Further, childhood sexual abuse was associated with the presence of SA, while physical/emotional abuse was associated with SA frequency. Hopelessness was more strongly related to SA frequency than NSSI frequency. These findings help disentangle the unique risk and protective factors for NSSI and co-occurring SA in incarcerated samples.

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.

How this classification was reachedexpand

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)0.015
metaresearch head score (Gemma)0.103
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.103
Meta-epidemiology (narrow)0.0210.023
Meta-epidemiology (broad)0.0230.008
Bibliometrics0.0140.017
Science and technology studies0.0130.012
Scholarly communication0.0090.011
Open science0.0130.011
Research integrity0.0170.024
Insufficient payload (model declined to judge)0.0000.006

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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2013
Admission routes1
Has abstractyes

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