Stacked Against Us: HIV / AIDS Statistics and Women
Bibliographic record
Abstract
According to Health Canada at the end of 2000 women in Canada accounted for 13.8 percent of cumulative positive HIV tests and 7.6 percent of AIDS cases among adults (Health Canada). Statistics such as these which describe the incidence and prevalence of HIV and AIDS among women in Canada have been available for well over a decade. Unfortunately these statistics do not always accurately or adequately describe the reality of women’s experience; rather they simply reflect the way we choose to conceptualize and subsequently measure risk in order to facilitate the categorization and labeling of certain individuals and groups (Gorna). Behind the epidemiology of HIV/AIDS is a story that women are “dying to tell.” The story begins with two universal truths. The first is that women have been relegated to positions of social political and economic subordination that are mediated by race and class. The second is that these constraints inhibit women’s capacity to protect themselves from exposure to HIV (Doyal; Gorna; O’Hea Sytsman Copeland and Brantley; Rao Gupta). Within most HIV/AIDS literature high-risk behaviours are conceptualized within rather myopic social historical economic cultural and political contexts. The process by which this conceptualization occurs is particularly important because it often determines the extent to which we assign responsibility to individuals. Originating in the minds of researchers and policy makers concepts of risk dictate the degree to which HIV/AIDS and women is given priority in society and the manner in which related issues of power and patriarchy are understood investigated and ameliorated. Consequently a discussion of women and HIV/AIDS cannot occur in isolation of their socio-economic and political position which is characterized by diminished social and sexual autonomy (Arber and Cooper; Rao Gupta). (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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".