Bibliographic record
Abstract
For centuries, women artists of the Wendat First Nation of Wendake in Quebec have created artworks of intricate design and complex meaning in moosehair and quill embroidery. Their work records and transmits ancestral knowledge across generations of artists and remains a vibrant and important practice today. Breaking new ground in Indigenous art histories, Wendat Women’s Arts is the first book to bring together a full history of the Wendat embroidery art form. Annette de Stecher challenges the historical anonymity of Indigenous women artists by arguing for their central role in community history and ceremony. Through their art, these women played an important part in the diplomatic strategies that advanced the sovereignty of their nation, work that was an extension of their position of authority in their families and clans. Chiefs and community members wore finely embroidered attire as a brilliant focus of ceremonial events, a tradition that continues today. Women artists also supported their community economically as their embroidery was a souvenir of choice for European collectors. In vibrant illustrations, this book reconstructs the rich repertoire of Wendat embroidery now dispersed in collections throughout the world. Wendat Women’s Arts combines a depth of historical understanding with a keen knowledge of contemporary Wendat artists, demonstrating that the story of Wendat women is one of cultural strength, innovation, resilience, and success.
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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 | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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".