Bibliographic record
Abstract
This chapter explores what is known about bisexuality and HIV/AIDS in Canada.It will focus primarily on research definitions, behavioural manifestations, and the political movement and organization of bisexuals in relation to HIV/AIDS.Published research, largely epidemiological, relating to the sexual behaviour of various populations since the beginning of the AIDS epidemic will be the predominant source of information.This documentation is critical because it is the only Canadian information currently available on bisexuality.While these data shed some light on the national picture as well as on regional variation, they ultimately raise more questions than answers.Scholarly reflection on sexuality in Canada and the placement of bisexuality along the continuum of human sexual relations is a discourse in its infancy.Our consideration of bisexuality in the arena of HIV/AIDS has had to take this into account.We will first provide an overview of the sources of information on male bisexualities found in Canadian HIV/AIDS research.This will be followed by an examination of what is known from these sources regarding the proportion, distribution, social and ethnocultural characteristics, risk behaviour and the incidence of HIV infection among bisexual men.To illuminate the organization, social environment and societal responses to bisexuality, specific examples will be presented.Though many of the issues that influence the experiences of bisexuals can apply to both men and women, indeed, many of the issues may be the same, this chapter will focus exclusively on the bisexualities of men.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".