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Record W2135253099 · doi:10.1111/nin.12114

Health prevention in the era of biosocieties: a critical analysis of the ‘Seek‐and‐Treat’ paradigm in<scp>HIV</scp>/<scp>AIDS</scp>prevention

2015· article· en· W2135253099 on OpenAlexaff
Thomas Foth, Patrick O’Byrne, Dave Holmes

Bibliographic record

VenueNursing Inquiry · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)MedicinePsychologyVirology

Abstract

fetched live from OpenAlex

On 18 November 2014, the United Nations launched an urgent new campaign to end AIDS as a global health threat by 2030. With its proposed strategy, the UN follows leading scientists who had declared the failure of former prevention strategies and now were promoting a 'Seek and Treat for Optimal Prevention' (STOP) approach as the most cost-effective response to the pandemic to meet the goal of 'an AIDS-free generation'. STOP combines antiretroviral therapy and routine HIV screening to find persons unaware that they are HIV-positive, because research has shown that people consistently change their behaviour (i.e. increase condom use, have fewer partners) after an HIV diagnosis. AIDS activists have broadly criticized this strategy on different levels. In this article, we go beyond these criticisms and try to analyse the political rationalities behind this 'new' strategy. We believe that it is necessary to put the rationale underpinning the STOP programme into the context of broader societal transformations that can best be captured as the development of advanced liberal societies and the new emphasis on self-controlling or self-responsibility rather than on disciplining behaviour.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.419
Teacher spread0.340 · 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.

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

Citations6
Published2015
Admission routes1
Has abstractyes

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