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Record W2484805982

Gendering HIV/AIDS prevention: situating Canadian youth in a transitional world

2004· article· en· W2484805982 on OpenAlexaboutno aff
June Larkin, Claudia Mitchell

Bibliographic record

VenueTSpace (University of Toronto) · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesHuman sexualityMasculinitySociologyTransnationalityVulnerability (computing)EthnographySex workCriminologyHuman immunodeficiency virus (HIV)
DOInot available

Abstract

fetched live from OpenAlex

In this research note we bring the work of transnational feminist scholars to our study of gender, risk and HIV prevention and we make the case for situating prevention work with Canadian youth in a larger global context. Drawing on HIV work in both Canada and South Africa and preliminary data from our focus groups with Canadian youth, we consider the value of a transnational analytic for furthering our understanding of the complexities of gendered risks both within and across two countries: South Africa with HIV infection rates around 20% and Canada where infections rates are low but with worrying signs about the potential for the spread of the disease. In an increasingly globalized world, we argue that the problem of first world/third world binaries, the transnational circulation of racist representations of AIDS, and the restructuring of gender systems are important considerations for HIV research and education with youth.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.578

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0650.019
Scholarly communication0.0100.003
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.024
GPT teacher head0.260
Teacher spread0.236 · 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 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

Citations4
Published2004
Admission routes1
Has abstractyes

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