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Record W4391214378 · doi:10.1080/00224499.2024.2302974

Navigating Stigma in Romantic Relationships Where One or Both Partners Sell Sexual Services

2024· article· en· W4391214378 on OpenAlexafffundabout
Cecilia Benoit, Brett Koenig, Andrea Mellor, Mikael Jansson, Doug Magnuson, Laura Vetrone

Bibliographic record

VenueThe Journal of Sex Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Victoria
FundersInstitute of Gender and HealthCanadian Institutes of Health Research
KeywordsRomancePsychologySocial psychologySex workNegotiationTollGeneral partnershipQualitative researchDevelopmental psychologySociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Romantic relationships are an important part of our social identities and well-being. In this paper, we report on qualitative findings with thirty Canadian couples, interviewed together, where it was known that one or both partners sell sexual services for a living. We asked a series of open-ended questions related to the background of the couple's relationship, their day-to-day interactions and work-related stressors. Participants talked about the ongoing negotiations they engage in as a couple, the benefits of being open to each other about working in the sex industry, and how they manage its emotional toll on their partnership. We conclude that there are various ways that sex workers are able to maintain intimacy in their romantic relationships after sex work has been disclosed. Widespread social stigma attached to sex work, complicated by criminalization in countries such as Canada, nevertheless threatens relationship quality in the long run.

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)0.006
metaresearch head score (Gemma)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.353

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0240.023
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.181
GPT teacher head0.480
Teacher spread0.300 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

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