Who? What? Where? When? And with What Consequences? An Analysis of Criminal Cases of HIV Non-disclosure in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The use of criminal-law powers to respond to people with HIV who place others at risk of HIV infection has emerged as a focal point of AIDS advocacy at global, national, and local levels. In the Canadian context, reform efforts that address the criminalization of HIV non-disclosure have been hampered by the absence of data on the contours, scale, and outcomes of criminalization. This article responds to that gap in knowledge with the first comprehensive analysis of the temporal trends, demographic patterns, and aggregate outcomes of Canadian criminal cases of HIV non-disclosure. The authors draw on insights into the role that rendering social phenomena in numerical terms plays for the governance of social life in order to make criminalization “visible” in ways that might contribute to activist responses. The article examines temporal trends, demographic patterns, and outcomes separately. In each instance, the pattern or trend identified is described, potential explanations for findings are offered, and an account is given of how the data have informed efforts to reform criminal law. Particular attention is paid to the following key findings: a sharp increase in criminal cases that began in 2004; the large proportion of recent criminal cases involving defendants who are heterosexual Black, African, and Caribbean men; and the high proportion of criminal cases resulting in conviction. The article closes with suggestions for future research.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it