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Record W7044025889

Using health committees to promote community participation as a social determinant of the right to health : lessons from Uuganda and South Africa

2018· article· en· W7044025889 on OpenAlexfundno aff

Bibliographic record

VenueGhent University Academic Bibliography (Ghent University) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsnot available
FundersEuropean CommissionInternational Development Research Centre
KeywordsDeliberationCorporate governanceCommunity participationCitizen journalismSocial determinants of healthParticipatory developmentCommunity healthPoliticsRight to healthSocial engagementHuman rights
DOInot available

Abstract

fetched live from OpenAlex

Community participation is not only a human right in itself but an essential underlying determinant for realizing the right to health, since it enables communities to be active and informed participants in the creation of a responsive health system that serves them efficiently. As acknowledged by the Rio Political Declaration on Social Determinants of Health, participatory processes are important in policymaking and in the implementation of laws relating to health. Collective deliberation improves both community development and health system governance, resulting in more reasoned, informed, and public-oriented decisions. 1 More recently, attention has focused on the elements of health system governance that enable greater responsiveness to community needs. However, there is relatively little by way of interventions linking human rights approaches to governance in ways that recognize participation as a critical social determinant of the right to health. This paper provides perspectives from a three-year intervention whose general objective was to develop and test models of good practice for health committees in South Africa and Uganda. It describes the aspects that we found critical for enhancing the potential of such committees in driving community participation as a social determinant of the right to health.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.011
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.102
GPT teacher head0.346
Teacher spread0.243 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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