Undoing and redoing an at-risk group: The objectivation and prevention of AIDS among male homosexuals in the antiretroviral era
Bibliographic record
Abstract
Au cours des années 1990, la lutte contre le VIH est devenue une cause nationale dont les actes de prévention s’adressent à l’ensemble de la population afin de prévenir toute stigmatisation. Dans les années 2000, la reconnaissance de l’existence de « groupes à risque » n’a plus posé problème et a déterminé des actions plus ciblées. Constatant la recrudescence des prises de risques, ces acteurs se sont donnés les moyens de saisir les groupes au plus près de leurs comportements. À partir du cas des homosexuels masculins, l’article analyse deux innovations récentes qui incarnent cette tendance : la démédicalisation du dépistage et la prophylaxie préexposition. Celles-ci permettent de montrer que l’évolution observée ne se résume pas à l’explicitation de ce qui devait être passé sous silence, mais suppose un travail d’objectivation renouvelé, de mobilisation d’individus appartenant à la population ciblée et d’une certaine conception de l’individu preneur de risques. Le repérage des comportements à risque permet aussi de délimiter les populations sur lesquelles il est possible d’intervenir et la mise en place d’outils pour y parvenir.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".