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Record W1997960028 · doi:10.1080/17449200601043663

Model law to address HIV/AIDS in prison

2006· article· en· W1997960028 on OpenAlexaff
Richard Pearshouse, Joanne Csete

Bibliographic record

VenueInternational Journal of Prisoner Health · 2006
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsHIV Legal Network
Fundersnot available
KeywordsPrisonLegislatureLawPolitical scienceHarmLaw reformCriminal lawHuman immunodeficiency virus (HIV)CriminologySociologyMedicine

Abstract

fetched live from OpenAlex

This paper makes the case for, and describes an effort to develop and promote the use of, model law to address HIV/AIDS in prisons. First, it outlines the concept of model law and what model law can bring to advocacy around law reform. Second, it describes why model law is particularly important to safeguard the rights of prisoners and people who use drugs. Third, it relates the methodology involved in developing model law. Three important areas of prison law and regulation related to HIV/AIDS are then described: provisions on the likelihood and duration of incarceration, including periods in pretrial detention; the legal foundation for HIV/AIDS care in prison; and the legal framework for comprehensive harm reduction services in prisons. A legislative framework to address rape and sexual violence in prison is also outlined. The paper sets out broad principles of how prison laws and regulations should be reformed to accord with human rights principles, and provides a number of examples of the specific wording of certain provisions.

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)0.014
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0050.006
Open science0.0020.005
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.057
GPT teacher head0.403
Teacher spread0.346 · 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 designTheoretical or conceptual
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
Published2006
Admission routes1
Has abstractyes

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