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Record W2605097442 · doi:10.3390/socsci6020039

A Sex Work Research Symposium: Examining Positionality in Documenting Sex Work and Sex Workers’ Rights

2017· article· en· W2605097442 on OpenAlexaff
Megan Lowthers, Magdalena Sabat, Elya M. Durisin, Kamala Kempadoo

Bibliographic record

VenueSocial Sciences · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsGeorge Brown CollegeYork University
Fundersnot available
KeywordsSex workSex workersScholarshipPoliticsGender studiesWork (physics)SociologySex segregationPolitical scienceLawMedicine

Abstract

fetched live from OpenAlex

Historically, academic literature on sex work has documented the changing debates, policies, and cultural discourse surrounding the sex industry, and their impact on the rights of sex workers worldwide. As sex work scholars look to the future of sex workers’ rights, however, we are also in a critical moment of self-reflection on how sex work scholarship engages with sex worker communities, produces knowledge surrounding sex work, and represents the lived experiences of sex workers’ rights, organizing, and activism. In this short Communication, proceedings from a recent sex work research symposium entitled, Sexual Economies, Politics, and Positionality in Sex Work Research are presented. Held at the Centre for Refugee Studies at York University, this symposium is a response to the need for sex work researchers, sex workers, and sex worker-led organizations to come together and critically examine the future of research on sex work and the politics of documenting sex workers’ rights.

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)0.025
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0320.019
Scholarly communication0.0170.014
Open science0.0020.015
Research integrity0.0090.018
Insufficient payload (model declined to judge)0.0070.001

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 head0.113
GPT teacher head0.433
Teacher spread0.320 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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