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Record W4389612500 · doi:10.17269/s41997-023-00843-9

Criminal Code reform of HIV non-disclosure is urgently needed: Social science perspectives on the harms of HIV criminalization in Canada

2023· review· en· W4389612500 on OpenAlexaffvenueabout
Colin Hastings, Martin French, Alexander McClelland, Eric Mykhalovskiy, Barry D. Adam, Laura Bisaillon, Katarina Bogosavljević, Marilou Gagnon, Saara Greene, Adrian Guţă, Suzanne Hindmarch, Angela Kaida, Jennifer M. Kilty, Notisha Massaquoi, Viviane Namaste, Patrick O’Byrne, Michael Orsini, Sophie Patterson, Chris Sanders, Alison Symington, Ciann Wilson

Bibliographic record

VenueCanadian Journal of Public Health · 2023
Typereview
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsWomen's and Gender Studies et Recherches FéministesConcordia UniversityMcMaster UniversityUniversity of VictoriaUniversity of New BrunswickUniversity of TorontoSimon Fraser UniversityUniversity of OttawaHIV Legal NetworkUniversity of WindsorOntario HIV Treatment NetworkLakehead UniversityRegional Municipality of WaterlooYork UniversityCarleton UniversityWilfrid Laurier UniversityUniversity of Waterloo
FundersNational Institute for Health and Care Research
KeywordsCriminalizationCriminal codeHuman immunodeficiency virus (HIV)Political scienceCriminologyPublic healthCriminal lawHumanitiesSociologyLawMedicineVirologyNursing

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006
metaresearch head score (Gemma)0.015
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: Review · Consensus signal: Review
Teacher disagreement score0.086
Threshold uncertainty score0.350

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.008
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.215
GPT teacher head0.412
Teacher spread0.197 · 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
GenreReview

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

Citations3
Published2023
Admission routes3
Has abstractno

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Same venueCanadian Journal of Public HealthSame topicHIV, Drug Use, Sexual RiskFrench-language works237,207