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“It's the Money, Honey”: The Economy of Sex Work in the Maritimes

2006· article· en· W1968953893 on OpenAlexaff
Leslie Ann Jeffrey, Gayle MacDonald

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSex workersWageWelfare economicsHumanitiesPolitical scienceSociologyEconomyEconomicsLabour economicsDemographyArtResearch methodologyPopulation

Abstract

fetched live from OpenAlex

Cet article se fonde sur une série d'interviews menés auprès de 60 travailleurs du sexe dans trois villes des Provinces maritimes. Nous avons trouvé que ces travailleurs prenaient souvent des décisions prudentes entre les choix économiques, notamment le travail a salaire minimal ou le bien-être social, ou entre le travail sexuel de maison ou de rue. Les interviews révélaient des modèles de résistance à l'endroit des structures économiques dominantes comparables aux modèles d'autres travailleurs des Maritimes. Comprendre les travailleurs du sexe comme travailleurs resistants nous permet de voir que beaucoup de leurs soucis tournent autour du maintien et/ou de l'augmentation de leur indépendance comme travailleurs, de leur capacité de maîtriser le rythme et le prix de leur travail, et de leurs conditions de travail. This paper is based on interviews with 60 sex workers in three Maritime cities. We found that sex workers often made careful decisions between the economic choices–including minimum-wage work or welfare–and between indoor or street-based sex work. Patterns of resistance to dominant economic structures that are comparable to other workers in the Maritimes emerged from the interviews. Understanding sex workers as resistant workers allows us to see that many of their concerns revolve around maintaining and/or increasing their independence as workers, their control over the pace and price of their labour, and the conditions of their 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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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
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

Citations41
Published2006
Admission routes1
Has abstractyes

Explore more

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