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Record W2166564529 · doi:10.1177/2158244014556632

Enhancing Critical Reflection of Brazilian Community Health Agents’ Awareness of Social Determinants of Health

2014· article· en· W2166564529 on OpenAlexaff
Margareth Santos Zanchetta, Bukola Salami, Annette Bailey, Sepali Guruge, Ann Ohama, Lise Rénaud, Jacques Rhéaume, Roger Côté, Michel Perreault, Zeilma da Cunha, Alia Maulgue, Jonathan Tel, Marlene Marques Avila, Rita Narrimam Boery

Bibliographic record

VenueSAGE Open · 2014
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité du Québec à MontréalWilliam Osler Health SystemUniversity of AlbertaUniversité de MontréalSt. Michael's HospitalToronto Metropolitan University
Fundersnot available
KeywordsSocial determinants of healthHealth equityPsychologyReflection (computer programming)Environmental healthPublic healthSocial psychologyMedicineNursingComputer science

Abstract

fetched live from OpenAlex

This project aims to assess how Brazilian community health agents’ critical awareness of the social determinants of health was enhanced and led to a greater understanding of the major structural changes necessary to sustain health promotion initiatives. Educational workshops inspired by Paulo Freire’s ideas on critical pedagogy were delivered to 82 community health agents in three Brazilian cities. The workshops utilized evocative objects to link and develop participants’ conceptual and experiential knowledge. The participants exchanged connections and experiences and created hypothetical action plans to be implemented in collaboration with community members. The discussions were audio recorded, transcribed verbatim, and submitted to content analysis. The connections provoked by evocative objects were related to required assets for the development of a healthy community. As social advocates, they are already committed to a social movement for health equity to catalyze a more equitable distribution of social goods, promote social inclusion, and liberate communities.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.217
GPT teacher head0.560
Teacher spread0.344 · 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.

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

Citations8
Published2014
Admission routes1
Has abstractyes

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