Engaged Palaeoethnobotany on the Northern Plains: A Compelling Future for Medicinal Plant Research
Bibliographic record
Abstract
The University of Saskatchewan Department of Archaeology & Anthropology became the first academic Department in Canada to publicly offer a Statement on Reconciliation. Most archaeologists recognize our colonial past and agree we need to expand our focus to incorporate better the thoughts, actions, and desires of the descendant communities of those who produced the material and nonmaterial remains we study. As a subdiscipline of archaeology, palaeoethnobotany with its emphasis on traditional plant use is well-positioned to engage fully with descendant communities. The Northern Plains would seem an ideal candidate for such research, given the rarity of existing palaeoethnobotanical research and the apparent absence of engaged research on medicinal plants. Current literature on the Northern Plains does include various ethnobotanical accounts, including discussion of plants with medicinal purposes. Though rare, there are also a few palaeoethnobotanical studies, which typically incorporate ethnobotanical data to aid interpretations. But what is lacking are clear attempts to bridge these sources of information; to conduct studies specifically designed through the coordinated efforts of Indigenous Knowledge Keepers and Healers with palaeoethnobotanists. We discuss how community-engaged scholarship of medicinal plants research on the Northern Plains may benefit both palaeoethnobotany and descendant communities.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".