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Record W2060101604 · doi:10.1080/15574090902922975

Sexual Identity and Its Contribution to MSM Risk Behavior in Bangaluru (Bangalore), India: The Results of a Two-Stage Cluster Sampling Survey

2008· article· en· W2060101604 on OpenAlexaff
Anna E. Phillips, Marie‐Claude Boily, Catherine M Lowndes, G Garnett, Kaveri Gurav, Banadakoppa M Ramesh, John Anthony, Richard E. Watts, Stephen Moses, Michel Alary

Bibliographic record

VenueJournal of LGBT Health Research · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of ManitobaUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsAnal intercourseMen who have sex with menContext (archaeology)Sexual identitySexual orientationDemographyPsychologyHomosexualitySocial psychologyGender studiesSociologyGeographyHuman immunodeficiency virus (HIV)Human sexualityMedicine

Abstract

fetched live from OpenAlex

In India, there are categories of MSM (hijras, kothis, double-deckers, panthis and bisexuals), which are generally associated with different HIV-risk behaviors. Our objective was to quantify differences across MSM identities (n = 357) and assess the extent they conform to typecasts that prevail in policy-orientated discourse. More feminine kothis (26%) and hijras (13%) mostly reported receptive sex, and masculine panthis (15%) and bisexuals (23%) insertive anal sex. However, behavior did not always conform to expectation, with 25% and 16% of the sample reporting both insertive and receptive anal intercourse with known and unknown noncommercial partners, respectively (p < 0.000). Although behavior often complied with stereotyped role and identity, male-with-male sexual practices were fluid. Reification of these categories in an intervention context may hinder our understanding of the differential HIV risk among MSM.

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)0.044
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.290
GPT teacher head0.527
Teacher spread0.237 · 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.

Study designObservational
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

Citations37
Published2008
Admission routes1
Has abstractyes

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