Toward a Critical Response to HIV Criminalization: Remarks on Advocacy and Social Justice
Bibliographic record
Abstract
In recent years, criminal laws have been increasingly applied in matters related to HIV nondisclosure, HIV exposure, and/or HIV transmission (Joint United Nations Programme on HIV/AIDS [UNAIDS], 2008). In North America, there has been a dramatic increase in the number of people charged for allegedly failing to disclose their serologic status before engaging in sexual activities, exposing others to HIV (via bodily fluids), and/or sexually transmitting HIV infection (Bernard, 2010). In Canada, charges have been laid against persons living with HIV (PLWH) in numerous cases. As of February 2011, there have been a total of 115 prosecutions in which a PLWH wasalleged tohave transmittedHIVorexposeda sexual partner to the risk of infection without disclosing HIVinfection status (Canadian HIV/AIDS Legal Network, 2011). Of this number, more than 56% (65/115) were convicted of an offense under the Criminal Code of Canada (Canadian HIV/AIDS Legal Network, 2011). See Figure 1 for a review of some of these cases. A similar situation has been documented in the United States, although at present, it remains difficult to determine exactly how many cases have been brought before the courts. As it currently stands, a growing number of PLWH are being prosecuted in North America, which is consistent with the fact that criminal laws are increasingly applied to punish certain conducts and prevent HIV transmission, although it has been clearly argued that criminalization hinders prevention efforts and may, in fact, dissuade some people from getting tested or accessing care (O’Byrne, 2011).
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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 | 0.058 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.031 | 0.074 |
| Scholarly communication | 0.031 | 0.038 |
| Open science | 0.009 | 0.028 |
| Research integrity | 0.088 | 0.083 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".