Missing Links: Women, Mental Health, and the Need for a New Model of HIV Prevention and Sexual Health Promotion
Bibliographic record
Abstract
Although women constitute over half the general population and almost two-thirds of the psychiatric patient population many studies of mental illness do not report women’s data separately and many do not include women (Penfold and Walker; Brunette and Drake). Similarly information about or pertinent to women at risk of HIV infection has been concealed within study data or neglected all together. Although the lack of information about the sexual and drug-using behaviours of people with serious mental illness at first impeded the development of appropriate AIDS prevention efforts it is now widely assumed that people living with mental illness may engage in “sexual risk behaviour” because of “their inability to evaluate appropriately their HIV risk” (McKinnon 25). In spite of this knowledge and the knowledge that women are more biologically at risk for HIV infection than men the HIV prevention needs of women have gone largely unconsidered. There is a great need to develop comprehensive and appropriate HIV prevention and sexual health promotions strategies and programs with and for women living with mental illness. If the HIV prevention needs of women living with mental illness are addressed at all the emphasis of most service planners is on strict HIV infection prevention education with very little attention paid to the larger aspects of healthy sexuality. Within such programs specific ways in which issues such as gender class ethnicity and “mentalism” intersect to influence the lives of women are ignored and the social problems that affect women’s lives are often blamed on the individual. (excerpt)
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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.011 | 0.024 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".