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Evaluation of STD/HIV/AIDS peer-education and danger: a local perspective

2008· article· en· W2034657291 on OpenAlexaff
Hélène Laperrière

Bibliographic record

VenueCiência & Saúde Coletiva · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPeer educationConceptualizationContext (archaeology)NegotiationPublic relationsCollective actionParticipatory action researchCitizen journalismSociologyPolitical sciencePsychologyPoliticsHealth educationMedicinePublic healthNursingSocial scienceGeography

Abstract

fetched live from OpenAlex

An evaluation of peer-education projects with sex workers, men who have sex with men and marginalized adolescents, was introduced in a remote region of Brazil. The context of varied limits of predictability made it difficult to conduct inquiry. To go beyond available epidemiological surveys and questionnaires on sexual behavior, a self-evaluation aimed at increasing pragmatic knowledge about prevention in a challenging socio-political context. During five-months, a participatory-action research explored participant observation; individual and collective exchanges with users, peer-educators, coordinators, administrators, politicians and regional health professionals. Collective understanding of peer-education in prostitution zones underlines the reality of unforeseen social repercussions and confluence/divergence of multiple actors' perspectives. It identifies meaningful dimensions at a community-level, such as the collective history and dangerous working conditions. Nurses face complex struggles and negotiations over multiple actors in their practice. This study suggests that nurses have a role to play in the conceptualization of participatory evaluation. It also underlines the threats to their physical and social safety, which they might share with peer-educators.

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)0.026
metaresearch head score (Gemma)0.023
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: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0040.002
Open science0.0020.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.030
GPT teacher head0.337
Teacher spread0.307 · 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

Citations11
Published2008
Admission routes1
Has abstractyes

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