“I'll Scratch Your Back If You'll Scratch Mine”: The Role of Reciprocity, Power and Autonomy in the Strip Club
Bibliographic record
Abstract
l'auteure de cet article étudie les jeux de pouvoir dans un club d'ef-feuilleuses. En établissant des parallelès avec l'industrie des services, elle explore les stratégies que les travailleurs des clubs d'effeuilleuses utilisent afin d'augmenter leur autonomie au travail et d'accroitre les ressources qu'ils mobilisent pour favoriser des actes de résistance. l'économie informelle des faveurs” (Bruckert, 2002) qui se crée au sein des communications entre les travailleurs et de leurs activités de coopération sert àétablir un environnement de travail plus soutenant et à diminuer les incertitudes inhérentes à leur emploi. This paper examines the interplay of power relations in the strip club. Through drawing parallels with the service industry, it explores the strategies strip club workers engage in to enhance their autonomy on the job and the resources they use to facilitate acts of resistance. The “informal economy of favours” (Bruckert, 2002) that develops, through interconnections between and co-operative activities engaged in by workers, serves to create a more supportive work environment and to decrease the inherent uncertainties of the job.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".