Bibliographic record
Abstract
Daughters of Aataentsic highlights and connects the unique lives of seven Weⁿdat/Waⁿdat women whose legacies are still felt today. Spanning the continent and the colonial borders of New France, British North America, Canada, and the United States, this book shows how Wendat people and place came together in Ontario, Quebec, Michigan, Ohio, Kansas, and Oklahoma, and how generations of activism became intimately tied with notions of family, community, motherwork, and legacy from the seventeenth to the twenty-first century. The lives of the seven women tell a story of individual and community triumph despite difficulties and great loss. Kathryn Magee Labelle aims to decolonize the historical discipline by researching with Indigenous people rather than researching on them. It is a collaborative effort, guided by an advisory council of eight Weⁿdat/Waⁿdat women, reflecting the needs and desires of community members. Daughters of Aataentsic challenges colonial interpretations by demonstrating the centrality of women, past and present, to Weⁿdat/Waⁿdat culture and history. Labelle draws from institutional archives and published works, as well as from oral histories and private collections. Breaking new ground in both historical narratives and community-guided research in North America, Daughters of Aataentsic offers an alternative narrative by considering the ways in which individual Weⁿdat/Waⁿdat women resisted colonialism, preserved their culture, and acted as matriarchs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".