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Record W4394631138 · doi:10.17118/11143/20541

The local dialogue workshop : a method for knowledge sharing in health promotion

2023· article· en· W4394631138 on OpenAlexaff
Obrillant Damus

Bibliographic record

VenueAnthropologie des savoirs des Suds · 2023
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsKnowledge sharingPromotion (chess)Knowledge managementComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Abstract : In Haiti, holders of local and indigenous knowledge living in rural areas are excluded from speaking
\nout about health promotion. We invited them to break the culture of silence by asking them to participate in a
\ndialogue workshop, held over several days, related to the role of their knowledge in promoting health in their
\ncommunities. Unlike some of us may believe, these people are not “cultural idiots”, but are, for the most part,
\nilliterate scholars who have developed knowledge through multiple dimensions in order to manage their own
\nhealth and that of others (including strangers as well as members of their biological family and their community).
\nThrough their participation in the dialogue workshop, they became more aware that they are actually living
\nhuman treasures and traditional health promoters, who each play an important role in both human (community
\nresilience) and environmental sustainability. Our trusting relationship and our close cultural proximity to the
\nparticipants contributed to the success of the dialogue workshop, a success that shattered the myth of the
\nmandatory link between the rural dwellers’ situation and absolute ignorance. The objective of this article is to
\npresent our methodological approach.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
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 head0.373
GPT teacher head0.557
Teacher spread0.184 · 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 designOther design
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
Published2023
Admission routes1
Has abstractyes

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