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Record W1948367062 · doi:10.1080/13691058.2015.1072875

Taint: an examination of the lived experiences of stigma and its lingering effects for eight sex industry experts

2015· article· en· W1948367062 on OpenAlexafffund
Raven Bowen, Vicky Bungay

Bibliographic record

VenueCulture Health & Sexuality · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of British Columbia Hospital
FundersCanadian Institutes of Health Research
KeywordsStigma (botany)Sex workNarrativeSocial workPsychologySex workersSocial psychologyMedicinePolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

As part of a larger study examining the effects of the design of the off-street sex industry on sex worker's health and safety practices, eight sex work experts who had experience as sex workers and as advocates and service providers were interviewed to garner their community engagement expertise in shaping the research. During narrative interviews, these experts discussed how stigma influenced their personal lives and their social justice work among sex workers. Their insights into stigma are unique to the literature because our experts simultaneously confronted direct instances of stigma that were a part of their personal and professional lives, sometimes concealing their sex work histories during the course of their professional support and advocacy work. As a result of this concealment, and because of how sex workers are sometimes mistreated, experts experienced stigma vicariously (indirectly) when their own sex work histories were not apparent. As a result of these experiences, participants became proficient at managing discrediting information about themselves when in the presence of those they mistrusted. They supported sex workers through stigmatising ordeals by using knowledge gained from these intersecting direct and vicarious experiences stigma, continuously building capacity within themselves and among other sex workers to resist stigma.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.083
GPT teacher head0.402
Teacher spread0.319 · 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 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

Citations40
Published2015
Admission routes2
Has abstractyes

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