The social dynamics of safe sex practices among Canadian sex industry clients
Bibliographic record
Abstract
Much of what we know about the safe sex practices of people who pay for sexual services (clients) remains firmly grounded in empirical and interpretive tendencies to overemphasise the causal link between social, cultural or individual characteristics and sexual decision-making. In this study we apply Adam Green's Bourdieu-inspired sexual fields theory to examine the ways in which safe sex practices are interdependently shaped by social, personal and interpersonal forces. Using data from 697 questionnaires and 24 semi-structured interviews with Canadian clients, we implemented a series of six additive logistic regression models and contextualised the results with the interview data to reveal the relational interdependencies of intra-psychic, macro, meso and micro-level factors related to safe sex practices. The questionnaire responses and interview data used in the study were gathered from a diverse sample of clients who were over the age of 19, had paid money for sexual services on one or more occasions during their lifetime and who resided in Canada at the time of participation. Our results illustrate the ways in which factors related to the venue where sexual acts take place, clients' relationships with commercial and non-commercial partners and personal choices related to substance use interdependently inform safe sex practices.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".