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Record W3134469893 · doi:10.22215/etd/2016-11251

Vanquishing the Victim: The Criminalization of HIV non-disclosure and transmission in Canada

2016· dissertation· en· W3134469893 on OpenAlexaffabout
Noreen Charge

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsHIV Legal NetworkCarleton UniversityYork University
Fundersnot available
KeywordsCriminalizationCriminologyMoral panicHuman immunodeficiency virus (HIV)Criminal codeCriminal lawPolitical scienceNarrativeLawPsychologyMedicineVirology

Abstract

fetched live from OpenAlex

This thesis examines the legal complexities surrounding the criminalization of HIV non-disclosure and transmission in Canada, where, by law, an HIV-positive person (PHA) is required to disclose his or her HIV status before engaging in sexual activities where a potential risk of exposure to the virus exists.In analyzing how HIV/AIDS is treated under the Criminal Code, the thesis will focus on the HIV narrative over the past three decades; the rationale behind HIV criminalization; how media coverage of HIV has incited bouts of moral panic in society; the historical legal framework; the evolution of HIV non-disclosure laws; how past precedents have affected cases heard to date; and, importantly, the role of public health and the consideration of human rights in relation to HIV criminalization.The criminalization of HIV non-disclosure and transmission is a complicated issue.Using the law as a HIV prevention tool is a blunt instrument that places the sole responsibility of disclosure on the PHA, and increases stigma and discrimination around people living with and affected by the virus.Although using criminal law to prosecute PHAs for non-disclosure may be necessary in situations where a person is blameworthy and the intent to harm another person can be proved, creating a policy framework would allow for clarity, protection of individual rights, public education and consistency in the application of the law.This thesis would not have been possible without the guidance of my academic advisor, Professor Kirsten Kozolanka.Her critiques on each chapter were thoughtful and provocative, and her interest in the topic was a motivating force that kept me on track.It was an honour to be under her supervision.I would like to thank my partner, Tamara Fetters, who listened ad nauseam to my musings on HIV, public health quandaries, legal fiascos, moral panic and medical advancements.She took time from her own work to encourage me in person, on Skype and via email to continue writing when my mind went blank.I would like to thank the many experts I interviewed, who shared their opinions on the legal, political and health ramifications of the criminalization of HIV nondisclosure.I would like to thank Steven Boone who was generous in sharing his personal experiences of being HIV-positive with me.Although the interviews were, at times, difficult, I appreciate Steven's willingness to share his story with me.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.951

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0400.013
Scholarly communication0.0090.002
Open science0.0030.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.273
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2016
Admission routes2
Has abstractyes

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