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Record W1987885367 · doi:10.1097/ans.0b013e31824fe6f9

Governing Bodies and Spaces

2012· article· en· W1987885367 on OpenAlexaff
Marilou Gagnon, Luc Cormier

Bibliographic record

VenueAdvances in Nursing Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Human rightsPoliticsState (computer science)Software deploymentNursingPolitical scienceMedicineSociologyLawFamily medicineEngineeringComputer science

Abstract

fetched live from OpenAlex

As it currently stands, mandatory human immunodeficiency virus (HIV) testing of prisoners is performed by nurses in more than 24 states and throughout the federal correctional system. The aim of this article was to bring to the attention of the nursing community the inner workings of mandatory HIV testing and its implications for HIV-positive prisoners. Building on a recent report published by Human Rights Watch, we critically examine the deployment of mandatory HIV testing in state correctional facilities located in Alabama and South Carolina. We, therefore, intend to situate this practice within a bio-political logic and explore its human rights consequence.

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)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.024
Scholarly communication0.0110.006
Open science0.0010.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.013
GPT teacher head0.377
Teacher spread0.364 · 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 designNot applicable
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

Citations5
Published2012
Admission routes1
Has abstractyes

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