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Record W2346614401 · doi:10.1080/17441692.2016.1180701

‘Men who use the Internet to seek sex with men’: Rethinking sexuality in the transnational context of HIV prevention

2016· review· en· W2346614401 on OpenAlexaff
Rusty Souleymanov, Yu Huang

Bibliographic record

VenueGlobal Public Health · 2016
Typereview
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman sexualityScholarshipEthnocentrismSociologyGender studiesNormativeEssentialismPopulationPublic healthContext (archaeology)Social psychologyPsychologyPolitical scienceMedicineAnthropology

Abstract

fetched live from OpenAlex

MISM (i.e. men who use the Internet to seek sex with men) has emerged in public health literature as a population in need of HIV prevention. In this paper, we argue for the importance of rethinking the dominant notions of the MISM category to uncover its ethnocentric and heteronormative bias. To accomplish this, we conducted a historical, epistemological and transnational analysis of social sciences and health research literature (n = 146) published on MISM between 2000 and 2014. We critically unravel the normative underpinnings of 'westernised' knowledge upon which the MISM category is based. We argue that the essentialist approach of Western scholarship can homogenise MISM by narrowly referring to behavioural aspects of sexuality, thereby rendering multiple sexualities/desires invisible. Furthermore, we argue that a Eurocentric bias, which underlies the MISM category, may hinder our awareness of the transnational dynamics of sexual minority communities, identities, histories and cultures. We propose the conceptualisation of MISM as hybrid cultural subjects that go beyond transnational and social boundaries, and generate conclusions about the future of the MISM category for HIV prevention and health promotion.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.950
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.102
GPT teacher head0.408
Teacher spread0.306 · 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.

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

Citations6
Published2016
Admission routes1
Has abstractyes

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