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Record W1985285784 · doi:10.1016/j.jana.2011.02.002

HIV, Nursing Practice, and the Law: What Does HIV Criminalization Mean for Practicing Nurses

2011· article· en· W1985285784 on OpenAlexaboutno aff
Patrick O’Byrne

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationCriminalizationAgency (philosophy)Human immunodeficiency virus (HIV)Notifiable diseasePublic healthMedicinePolitical scienceFamily medicineNursingCriminologyLawPsychologySociology

Abstract

fetched live from OpenAlex

HIV infection is not a legally notifiable disease at the national level in Canada; however, provincial and territorial officials voluntarily undertake notification to the Public Health Agency of Canada. A case study involving four community-based sites in Newfoundland and Labrador found that the absence of clear legislation concerning HIV testing presented challenges for nurses who had to interpret and comply with provincial legislation and agency policy while meeting the needs of test-seekers. This ambiguous messaging is part of other conflicting information about the availability of anonymous HIV testing that, along with other factors, may contribute to under-testing and under-diagnosis in the province. From a social justice perspective, developing a national HIV strategy and amending legislation to facilitate anonymous HIV testing might provide clearer direction to nurses and agencies, and promote public health by improving service delivery and increasing testing in under-tested, higher-risk-taking populations.

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)0.012
metaresearch head score (Gemma)0.061
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: none
Teacher disagreement score0.284
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.061
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0140.031
Scholarly communication0.0150.024
Open science0.0030.006
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.366
Teacher spread0.331 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Association of Nurses in AIDS CareSame topicHIV, Drug Use, Sexual RiskFrench-language works237,207