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Record W2136752115 · doi:10.1093/her/cyn023

Effectiveness of community health agents' actions in situations of social vulnerability

2008· article· en· W2136752115 on OpenAlex
Margareth Santos Zanchetta, Susan M V Voet, Wilson Galhego-Garcia, V. M. N. Smolentzov, Yves Talbot, Marielle Riutort, A. M. M. F. Galhego, T. J. de Souza, Rodrigo S Caldas, E. Costa, M. M. Kamikihara, S. Smolentzov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Education Research · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsVulnerability (computing)PsychologySocial psychologyEnvironmental healthMedicineComputer scienceComputer security

Abstract

fetched live from OpenAlex

Evaluation is purposeful activity examining multiple, diverse realities [1] that affect the implementation of social interventions and their management [2]. As political activity, evaluation involves partnerships among managers, stakeholders and internal and external evaluators. These partners review common interests and concerns to modify policies and modi operandi, and ultimately, to influence human life [3]. Evaluation is particularly sensitive to social problems and expectations; it documents their features, incidence and prevalence [2]. This article reports the quanti-qualitative results of an in-service effectiveness evaluation of interventions to reduce health risks for socially vulnerable people by community health agents (CHAs) (Agentes Comunitarios de Saude) in Brazil. CHAs are key personnel within the nationwide community health agent program (CHAP), created in 1991, that operates within Brazil’s Family Health Strategy (FHS). CHAP considers social inclusion through health education and promotion, a cornerstone of collective health. Most CHAs are from the communities they serve. This article documents some crucial features of CHAs’ work in dangerous neighborhoods previously inaccessible to health professionals (HPs). Knowledge about these residents’ health needs, challenges and difficulties due to their social vulnerability may not have reached health care providers.

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.

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)0.026
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.489
GPT teacher head0.658
Teacher spread0.169 · 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