Places of Tradition, Places of Research: The Evaluation of Traditional Medicine Workshops Using Culturally and Locally Relevant Methods
Bibliographic record
Abstract
This thesis examines how traditional medicine workshops offered by an Aboriginal health centre contribute to capacity re-building through self-care in two local communities in Manitoulin Island, Ontario. Health disparities that exist between Aboriginal people and the rest of the population have prompted a need to better understand health determinants that are of relevance in these communities including the importance of culture, tradition, and self-determination. A variety of qualitative methods were employed in this work including in-depth interviews, focus groups and “art voice.” The use of art voice on Manitoulin Island advances decolonizing methodologies by emphasizing how the incorporation of locally and culturally relevant methods or “methods-in-place,” is an effective way to engage communities in the research process. Results show the need to approach traditional teachings, health programs, and research from an Aboriginal worldview and indicate that more frequent workshops are required to empower youth and adults to practice and share traditional knowledge. Furthermore, a continuum exists in which the interest in language, culture, and tradition increases with age. Capacity can therefore be re-built over time within communities promoting autonomy and self-determination through self-care. Findings can be expected to further inform the traditional programming in participating communities, enhance existing Aboriginal determinants of health models by including traditional medicine as an element of self-care, and can act as a springboard for the inclusion of unique place-based methods into community-based research projects in the future.
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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 | 0.066 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".