Radical Sex Between Men : Assembling Desiring-Machines
Bibliographic record
Abstract
Introduction In response to the HIV/AIDS epidemic, many jurisdictions in North America (especially in the United States) have cracked down on most of the sex-on-thepremises venues such as gay bathhouses, parks, and adult theaters in order to “control” and “contain” the epidemic. This has prompted men who have sex with men (MSM) to find alternative venues for sex, especially group sex (Meunier, 2014). This chapter presents the results of ethnographic (excluding observation) fieldwork involving MSM who engage in group sex, which we define as any planned or unplanned event with three or more men who engage in sexual activities together. Our research included MSM who gathered together for group sex either at their own home(s), at another private location, or at gay hotels/resorts. Despite increasing research on MSM who are involved in group sex sessions (Grov et al., 2013; Meunier, 2014; Philipps II et al., 2013; Solomon et al., 2011), to date little has looked at risky sexual practices (including attendees’ definition of risk) specifically in a context that is gaining in popularity. The broad research objective was to understand the sexual practices of men who engage in group sex, where verbal communication is often minimal. Aligned with this main objective, we explored two research questions: (1) what are the representations of STI/ HIV risk among MSM who engage in group sex, and (2) what “risk reduction” strategies did group sex participants employ? We approached the study from a critical theoretical standpoint, and structured data analysis using poststructuralist scholarship.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".