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Record W2399913108 · doi:10.1080/13691058.2016.1180855

Introduction to the <i>Culture, Health &amp; Sexuality</i> Virtual Special Issue on sex, sexuality and sex work

2016· article· en· W2399913108 on OpenAlexaff
Dan Allman, Melissa Ditmore

Bibliographic record

VenueCulture Health & Sexuality · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsHuman sexualityContext (archaeology)Agency (philosophy)Gender studiesScholarshipReproductive healthSex workSociologyScope (computer science)Power (physics)Political scienceSocial scienceHuman immunodeficiency virus (HIV)MedicineHistoryPopulationLaw

Abstract

fetched live from OpenAlex

This article provides an editorial introduction to a virtual special issue on sex work and prostitution. It offers a brief history of sex work studies as published in the journal Culture, Health & Sexuality; reflects on the breadth and scope of papers the journal has published; considers the contribution of the journal's papers to the wellbeing and sexuality of people who sell sex; and envisions future areas of inquiry for sex work studies. As authors, we identify major themes within the journal's archive, including activism, agency, context, discourse, hazard, health, legalisation, love, place, power, race, relationships, stigma and vulnerabilities. In particular, we reflect on how HIV has created an environment in which issues of culture, health and sexuality have come to be disentangled from the moral agendas of earlier years. As a venue for the dissemination of a reinvigorated scholarship, Culture, Health & Sexuality provides a platform for a community of often like-minded, rigorous thinkers, to provide new and established perspectives, methods and voices and to present important developments in studies of sex, sexuality and sex work.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.032
GPT teacher head0.363
Teacher spread0.332 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations14
Published2016
Admission routes1
Has abstractyes

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