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Record W2063295934 · doi:10.1097/qai.0b013e3181bbcb56

Civil Society, Political Mobilization, and the Impact of HIV Scale-Up on Health Systems in Brazil

2009· review· en· W2063295934 on OpenAlexaboutno aff
Richard Parker

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2009
Typereview
Languageen
FieldSocial Sciences
TopicHistorical and modern epidemiology studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsCivil societySocial movementPublic healthPoliticsContext (archaeology)LegislationPolitical scienceEconomic growthPublic administrationResource mobilizationHealth policyRight to healthSociologyHealth careMedicineLawEconomics

Abstract

fetched live from OpenAlex

This article examines the role of civil society in shaping HIV and AIDS policies and programs in Brazil. It focuses on the historical context of the redemocratization of Brazilian society during the 1980s, when the initial response to the epidemic took shape, and emphasizes the role of social movements linked to the progressive Catholic Church, the sanitary reform movement in public health, and the emerging gay rights movement in the early response to the epidemic in Brazil. It highlights the broad-based civil society coalition that took shape over the course of the 1990s and the political alliances that were built up shortly after the 1996 International AIDS Conference in Vancouver, Canada, to pass legislation guaranteeing the right to access to antiretroviral treatment. It emphasizes the continued importance of civil society organizations-in particular, AIDS-related nongovernmental organizations-and leading AIDS activists in exerting continued pressure to guarantee the sustainability of treatment access and the impact that action focused on HIV and AIDS has had on the Brazilian public health system more broadly, particularly through strengthening health infrastructures and providing a model for health-related social mobilization.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.755
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.060
GPT teacher head0.403
Teacher spread0.343 · 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 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

Citations85
Published2009
Admission routes1
Has abstractyes

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