The local dialogue workshop : a method for knowledge sharing in health promotion
Bibliographic record
Abstract
In Haiti, holders of local and indigenous knowledge living in rural areas are excluded from speaking out about health promotion.We invited them to break the culture of silence by asking them to participate in a dialogue workshop, held over several days, related to the role of their knowledge in promoting health in their communities.Unlike some of us may believe, these people are not "cultural idiots", but are, for the most part, illiterate scholars who have developed knowledge through multiple dimensions in order to manage their own health and that of others (including strangers as well as members of their biological family and their community).Through their participation in the dialogue workshop, they became more aware that they are actually living human treasures and traditional health promoters, who each play an important role in both human (community resilience) and environmental sustainability.Our trusting relationship and our close cultural proximity to the participants contributed to the success of the dialogue workshop, a success that shattered the myth of the mandatory link between the rural dwellers' situation and absolute ignorance.The objective of this article is to present our methodological approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.088 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.006 | 0.030 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".