iixsatimutilh - We Are Medicine For Eachother: A Traditional Medicines Program
Bibliographic record
Abstract
Traditional medicines hold profound significance within numerous Indigenous communities, serving as integral components of cultural identity and holistic wellness practices. Traditional medicine assumes a central role in fostering the physician, mental, spiritual and emotional health and vitality of its members. An esteemed healer within the community, has devoted decades sharing her profound knowledge regarding the medicine that comes from the land, witnessing firsthand the transformative impact on individuals. She defines traditional medicine as a culmination of plants, healing, song, and dance. She emphasizes that traditional medicine and healing is about “the energy, the working and the sharing that all community members partake in to rid themselves of illness.” Much of this knowledge is passed down within the community by word-of-mouth, and thus a program is needed so that this wealth of knowledge can be taught and shared accurately and in a structured manner. She is dedicated to guiding learners on how to use traditional medicines and to understand when these medicines are the right option. Through her teachings, individuals are empowered to recognize the appropriateness of these remedies and engage in healing practices that resonate authentically with their cultural heritage and community traditions.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.077 | 0.044 |
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".