Bibliographic record
Abstract
In the borderland between the United States and Canada stand communities of Native American people whose resilience enabled them to survive the ravages of hundreds of years of wars, eugenics, and racism that persists into the present day. These factors contributed to the decline of traditions and a subsequent period of cultural renewal and pride that has led up to several Abenaki tribes petitioning the State of Vermont for tribal Recognition. When the Recognition applications were compared, it became apparent that they had retained many of their agricultural traditions and that their cultural revitalization efforts could be extended not only to their ceremonial dances but also to the creation of ceremonial regalia for both their planting and harvest ceremonies. The complementary nature of regalia would help strengthen their community and restore cultural context to the dances for the first time in generations. As women from different communities prepared for the renewal of the harvest dances, questions arose around cultural identity, design motifs, materials, and the possession of the ceremonial regalia. This paper is a retelling of the process that led to creating the ceremonial garments and a description of outcomes. It sets the stage for a discussion about the essential hidden leadership roles of Native American women in consensus-based society and demonstrates how a team of Abenaki women from different communities played a crucial role in the cultural revitalization process through the creation and usage of regalia for the agricultural ceremony.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".