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Record W2795541401 · doi:10.1017/s1743923x18000016

She's Married, She's Faithful, She's Dying: Politicizing the President's Emergency Plan for AIDS Relief

2018· article· en· W2795541401 on OpenAlexaff
Christina Doonan

Bibliographic record

VenuePolitics & Gender · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPledgePolitical scienceMandatePublic administrationLawPoliticsIdeology

Abstract

fetched live from OpenAlex

Conservative Christians played a significant role in pioneering the United States’ groundbreaking anti-HIV funding initiative, the President's Emergency Plan for AIDS Relief (PEPFAR). Consequently, PEPFAR is widely regarded as George W. Bush's crowning achievement. The same political forces that ushered in PEPFAR under President Bush were also the architects of strict ideological restraints around the otherwise straightforward public health goal of curbing the spread of HIV/AIDS. In recent years, some of these restrictions have been rolled back or struck down by the U.S. Supreme Court, and PEPFAR has continued to serve a crucial role in global health and security. PEPFAR's future success in achieving its health mandate (to create an AIDS-free generation) will be influenced by lessons from its past. This article illuminates how, in its first decade, PEPFAR was directed toward the fulfillment of socially conservative goals that ran counter to its official agenda. This was accomplished in large part through two controversial provisions: the “anti-prostitution pledge” (2003–2013) and the “conscience clause” (2003–present). Working in tandem, these policies sought to secure funding for organizations that favored abstinence and fidelity rather than a multisectoral approach to AIDS prevention.

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)0.004
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0200.011
Scholarly communication0.0070.003
Open science0.0000.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.064
GPT teacher head0.353
Teacher spread0.289 · 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
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
Published2018
Admission routes1
Has abstractyes

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