Learning New Medicines: Exchanging Medicinal Plant Knowledge amongst Northwestern North American Indigenous and Settler Communities
Bibliographic record
Abstract
Virtually every human society holds a rich body of knowledge regarding herbal medicines. Through a study of medicinal plants used by Indigenous peoples in Northwestern North America, as well as plant names and medicinal applications, I investigate the ways in which such knowledge is acquired and shared across cultural and geographic space. Not only are there many similarities in medicinal plant traditions among the region’s Indigenous cultures, there is also evidence of exchanging medicinal plant knowledge – and even the medicines and plants themselves – between newcomer Europeans and Asians and Indigenous peoples. As well as introducing their own herbal medicines from their homelands, the newcomers acquired herbal medicinal knowledge from First Nation practitioners, adapted this knowledge to their own needs, and incorporated it into their official pharmacopoeias. This process of medicinal knowledge transmission can enrich our lives and increase our resilience in the face of ongoing change. Key words: Herbal medicine - Exchanging knowledge - North American Indigenous peoples
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".