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Record W2531188923 · doi:10.1177/0840470416660569

The ethical case for providing cost-free access to lifesaving HIV medications in Canada

2016· review· en· W2531188923 on OpenAlexaffabout
Chris Kaposy, Nicole Greenspan, Zack Marshall, Jill Allison, Shelley Marshall, Cynthia Kitson

Bibliographic record

VenueHealthcare Management Forum · 2016
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of OttawaDalhousie UniversityWinnipeg Regional Health AuthoritySt. Michael's HospitalMemorial University of Newfoundland
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Expanded accessAntiretroviral therapyVariety (cybernetics)Ethical issuesMedical prescriptionMedicineBusinessFamily medicineNursingViral loadEngineering ethicsComputer science

Abstract

fetched live from OpenAlex

Antiretroviral therapy for HIV can be expensive if paid for out of pocket. In Canada, there are a variety of federal, provincial, and private prescription drug plans that lower the cost of these lifesaving medications for people living with HIV, and in some cases, these plans result in cost-free access. However, many people living with HIV must contend with high deductibles for their antiretroviral therapies, and many experience difficulty managing the administrative requirements of their drug plans. This article comments on some of the results of a qualitative study into ethical issues in HIV care. Access to antiretrovirals was a theme that emerged in this study. We argue on ethical grounds that provincial drug plans should guarantee cost-free access to antiretroviral therapies for people living with HIV with minimal administrative requirements.

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)0.008
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.287
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0070.014
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.471
Teacher spread0.360 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2016
Admission routes2
Has abstractyes

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