It's in Our Blood: Indigenous women's knowledge as a critical path to women's well-being
Bibliographic record
Abstract
The research reported in this article sought to shed light on the North, Central and South American indigenous moon time teachings related to the menstrual cycle of women. The historical institutionalization, medicalization and colonization of indigenous women's practices have devalued and almost destroyed this knowledge. This study explored the question of whether or not lost indigenous knowledge of women's power can be reclaimed for women's health and well-being. A qualitative participatory research methodology was adopted, based on an indigenous paradigm and scholarly rigour and including protocols acceptable to an Ojibwe grandmother, Isabelle Meawasige, who shared her knowledge and experience. The experiential knowledge gained and the meanings expressed by female participants in a circle sharing facilitated by the principal author are presented and discussed. The results of this research reveal optimistic possibilities to co-create health and well-being for the participants, grounded in what is both visible and invisible within indigenous women's culture.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.030 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".