“It's the Money, Honey”: The Economy of Sex Work in the Maritimes
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".