The harms of HIV criminalization
Notice bibliographique
Résumé
As academics, advocates, including people living with HIV, we are writing to welcome the findings, recently published in this journal, suggesting the ineffectiveness of invoking the criminal law as a tool of HIV prevention [1]. Using the American Centers for Disease Control and Prevention data, Sweeney et al.[1] searched for correlations between rates of diagnosis of HIV (2001–2010) and AIDS (1994–2010) and the presence of state laws that criminalize so-called ‘HIV exposure’. In 30 states that had such laws, Sweeney et al.[1] found ‘no association between HIV or AIDS diagnosis rates and criminal exposure laws across states over time’. We strongly encourage developing new knowledge about the implications of criminal laws for HIV prevention. We also recognize that Sweeney et al.[1] published a ‘concise communication’ format article, which undoubtedly limited what could be said. Despite this, we feel it imperative to highlight some omissions and assumptions in the work that precluded this article from making a stronger statement about the harms of HIV criminalization. First, this research does not sufficiently address the myriad negative impacts that HIV laws have had on the lives of people living with HIV. Sweeney et al.[1] seem unaware of the growing body of social science work that has theorized and documented, in empirical terms, these harmful effects [2]. If this evidence of harmful effects had been considered, we think Sweeney et al.[1] might have actually come to a less qualified conclusion. They are careful to note the limitations of their ecological analysis, but they could go further to underscore that, although they detected no association, there is research that has documented how such laws interfere with the work of HIV prevention [3]. Second, the quantitative approach employed relies on a form of logic that reinforces assumptions about the criminal law's rationality and neutrality in a way that is potentially troubling, as it fails to recognize two important factors that have been explored by social science researchers: the ways in which criminal laws and courts can be highly irrational and contingent; [4] and historically how criminal laws have been organized around the regulation, control, and incapacitation of populations (e.g., people of color, people with disabilities, people who live in poverty, gay, lesbian, and trans people, and people who live with forms of communicable disease, among others) [5]. Research organized with the underpinning assumptions that HIV criminal laws are rationally intended to prevent transmission of the virus, and that legislators will simply uptake scientific or public health knowledge to promote the goals of science and public health may be unintentionally misguided. Third, Sweeney et al. [1] noted that ‘state governments have been encouraged to review criminal laws to ensure they reflect current science on transmission risk as well as further public interest and public health’ (p. 11). To strengthen this observation, they might have also acknowledged law reform efforts, now underway in many jurisdictions, led by those living with, and most affected by, HIV (see, among others, HIV Justice Network, and the Global Commission on HIV and the Law). A lack of engagement with these efforts seems disconnected from the growing expectation that social science research be made meaningful in the real world. Although the study by Sweeny et al.[1] may have productive possibilities for advocacy, it was unfortunately too silent on the harms of exposure laws. Acknowledgements Conflicts of interest There are no conflicts of interest.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».