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Record W2320730110 · doi:10.1177/0093854812474427

Prevalence and Incidence of Nonsuicidal Self-Injury Among Federally Sentenced Women in Canada

2013· article· en· W2320730110 on OpenAlexaffabout
Jenelle Power, Shelley L. Brown, Amelia M. Usher

Bibliographic record

VenueCriminal Justice and Behavior · 2013
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMinistry of Community Safety and Correctional ServicesCarleton University
Fundersnot available
KeywordsIncidence (geometry)Injury preventionPoison controlSuicide preventionOccupational safety and healthMedicineHuman factors and ergonomicsPopulationDemographyPsychiatryPsychologyClinical psychologyMedical emergencyEnvironmental health

Abstract

fetched live from OpenAlex

Nonsuicidal self-injury (NSSI) is a complex behavior that is not uncommon in the general population, yet little is known about the prevalence of this behavior among incarcerated women. Two studies were conducted to determine the prevalence and incidence of NSSI in federally sentenced Canadian women. In Study 1, a mixed-methods design that included a qualitative interview and a written questionnaire with a sample of 150 incarcerated women was used. In Study 2, archival data were analyzed for a random sample of 400 incarcerated women. Results indicated lifetime prevalence rates of NSSI ranging from 24% to 38%. Incidence of self-injury in a federal institution over a 1-year period was found to be 3.6 per 27.4 person-years (i.e., number of years incarcerated). Both studies indicated that for the majority of women in both samples, NSSI was first initiated in the community, prior to incarceration in a federal correctional institution.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.021
GPT teacher head0.290
Teacher spread0.269 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2013
Admission routes2
Has abstractyes

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