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Record W2017914359 · doi:10.1300/j013v40n04_04

Harm Reduction and Women in the Canadian National Prison System: Policy or Practice?

2005· article· en· W2017914359 on OpenAlexaffabout
Laurene Rehman, Jacqueline Gahagan, Anne Marie DiCenso, Giselle Dias

Bibliographic record

VenueWomen & Health · 2005
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPrisonHarm reductionReduction (mathematics)HarmPolitical scienceCriminologyPsychologyMedicineNursingPublic healthLaw

Abstract

fetched live from OpenAlex

Applying the principles of harm reduction within the context of incarcerated populations raises a number of challenges. Although some access to harm reduction strategies has been promoted in general society, a divide between what is available and what is advocated continues to exist within the prison system. This paper explores the perceptions and lived experiences of a sample of nationally incarcerated women in Canada regarding their perceptions and experiences in accessing HIV and Hepatitis C prevention, care, treatment and support. In-depth interviews were conducted with 156 women in Canadian national prisons. Q.S.R. Nudist was used to assist with data management. A constant comparison method was used to derive categories, patterns, and themes. Emergent themes highlighted a gap between access to harm reduction in policy and in practice. Despite the implementation of some harm reduction techniques, women in Canadian prisons reported variable access to both education and methods of reducing HIV/HCV transmission. Concerns were also raised about pre-and post-test counseling for HIV/HCV testing. Best practices are suggested for implementing harm reduction strategies within prisons for women in Canada.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.398
Teacher spread0.344 · 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 designQualitative
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

Citations17
Published2005
Admission routes2
Has abstractyes

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