Mucz, Michael. Baba’s Kitchen Medicines: Folk Remedies of Ukrainian Settlers in Western Canada
Bibliographic record
Abstract
Although the folklife of Ukrainians in Canada has been the topic of a number of valuable studies, some traditions or memories of traditions were passed on only orally until now.Michael Mucz, a professor of biology with interests in ethnobotany and herbal medicine who teaches in the University of Alberta system, offers a well-rounded and fascinating study of the folk healing practices of Ukrainian communities in Canada in Baba's Kitchen Medicines: Folk Remedies of Ukrainian Settlers in Western Canada.Mucz briefly but effectively outlines the historical context of Ukrainian settlements in Canada, noting that compact settlements in isolated areas meant both a need for mutual aid and a greater likelihood of preserving traditions, whereas consulting scientific medicine and trained doctors involved both distance (difficulty) and expense.A chapter on ancient healing practices reaches back to Classical Greece, while another outlines the specialized kinds of healers who could be found in the Ukrainian communities: bonesetters, mostly men who had learned the skill while serving in the Austro-Hungarian Army; midwives who helped women in childbirth; herbalists, found much less often than the bearers of "kitchen" herbal medicine; and spiritual healers, who would crack eggs into water or use other folk methods to advance psychological wellbeing.Mucz's informants come from a variety of religions and places of origin, but the data is based on extensive interviews with children and grandchildren of the original settlers.(There is also just a glimpse of aboriginal healing practices, as picked up by the Ukrainian communities.)The best part of the book offers tables with lists of medicinal preparations, often providing quotations from individual informants and other kinds of context for the healing practices cited.The book is richly illustrated with maps and black-andwhite photographs, which include both historical photographs of
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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 | 0.000 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".