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Record W2092315164 · doi:10.7202/038659ar

Rethinking Risk: The Relevance of Condoms and Viral Load in HIV Nondisclosure Prosecutions

2009· article· en· W2092315164 on OpenAlexaffvenueabout
Isabel Grant

Bibliographic record

VenueMcGill Law Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCondomHarmPlaintiffCriminologyContext (archaeology)Relevance (law)CulpabilityPsychologySexual assaultSocial psychologyPolitical scienceLawHuman immunodeficiency virus (HIV)MedicinePoison controlSuicide preventionFamily medicineEnvironmental health

Abstract

fetched live from OpenAlex

An HIV-positive individual who fails to disclose his or her status to a sexual partner may face charges ranging from nuisance to murder for such behaviour, with the most common charges being aggravated assault and aggravated sexual assault. The number of prosecutions in Canada against individuals who fail to disclose their HIV-positive status to their sexual partners has risen over the last ten years. At the same time, scientific advancements in treatment options and our understanding of transmission, condom usage, and viral load are constantly influencing the assessment of the risk that nondisclosure poses to the complainant in any given case. The author reviews the recent case of R. v. Mabior , the first judgment in Canada to criminalize nondisclosure in the context of protected sex. She argues that encouraging condom use is so important, and that the use of condoms reduces the risk of transmission so significantly, that the criminal law should distinguish between protected and unprotected sex in cases of nondisclosure. The author proceeds to critique the trial judge's reliance on viral load as a factor in determining whether nondisclosure poses a significant risk of serious bodily harm under the test established in Cuerrier . The author argues that the accused's viral load, unlike condom use, is not a manageable standard on which to base culpability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.288
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2009
Admission routes3
Has abstractyes

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