Bisexualities and AIDS: International Perspectives
Bibliographic record
Abstract
Bisexual men in Britain, Mary Boulton and Ray Fitzpatrick bisexuality and HIV/AIDS in Canada, Ted Myers and Dan Allman not gay, not bisexual, but polymorphously sexually active - male bisexuality and AIDS in Australia, June Crawford et al bisexuality and AIDS - results from French quantitative studies, Antione Messiah bisexuality and HIV/AIDS in Mexico, Ana Luisa Liguori et al bisexual communities and culture in Costa Rica, Jacobo Shifter et al AIDS and the enigma of bisexuality in the Domincan Republic, E. Antonio de Moya and Rafael Garcia male bisexuality in Peru and the prevention of AIDS, Carlos F. Caceres bisexuality and HIV/AIDS in Brazil, Richard G. Parker under the blanket - bisexualities and AIDS in India, Shivananda Khan and Peter Aggleton male homosexual behviour and HIV-related risk in China, Suiming Pan and Peter Aggleton the homosexual xontext of heterosexual practice in Papua New Guinea, Carol L. Jenkins silahis - looking for the missing Filipino bisexual male, Michael L. Tan.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.040 | 0.007 |
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".