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Record W2586789876 · doi:10.1017/s0003445200000040

Medication Use, Substance Use, and Psychological Conditions of Female Inmates in Canadian Federal Prisons

2013· article· en· W2586789876 on OpenAlexaffabout
Chantal Plourde, Natasha Dufour, Serge Brochu, Annie Gendron

Bibliographic record

VenueInternational Annals of Criminology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversité de MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsMedical prescriptionPsychiatryPrisonSubstance useSubstance abuseMental healthAddictionMedicinePsychology

Abstract

fetched live from OpenAlex

Summary This study provides data on substance use patterns, including medications, among female inmates in Canadian federal prisons. The participants were interviewed regarding their substance use and their psychological condition before and during incarceration. Their medication cards were also analyzed. The results show that a large proportion (66.9 %) of these incarcerated women reported substance abuse prior to incarceration and exhibited psychological disorders. In prison, if the illicit substance use remained low, most subjects had prescriptions for more than one medication. Furthermore, women with psychotropic medication prescriptions in their file had, on average, prescriptions for two different psychotropic medications. Significant relationships were found between substance misuse before incarceration and illicit substance use or and psychotropic medication use during incarceration. These results support the need to develop integrated services for both addiction and mental health for female offenders during incarceration.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.237
GPT teacher head0.417
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2013
Admission routes2
Has abstractyes

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