A History of Language and Revival in the Wendat and Wyandot(te) Nations, 1534-2023
Bibliographic record
Abstract
The Wxndat languages (Wendat, Waⁿdat, Wyandot, Huron) are some of the best documented Indigenous languages in North America. Yet despite the volume of documentation, the languages fell asleep (became dormant) in the twentieth century, and still today there are no fluent speakers. Over the course of nearly five hundred years, from 1534-2023, the Wxndat languages have had champions from various communities: other Indigenous peoples, Europeans, American and Canadian settlers, and most importantly, the modern Wxndat nations and Wxndat individuals themselves. Previous scholarship has covered varying aspects of the languages and their history, but usually focusing on certain eras only, or as a section within a larger study. This thesis examines the longue durée history of the Wxndat languages, efforts to preserve them, and their revival movements, to illustrate the caretaking of the languages from one generation to the next. It features hędí:hšahs nęh hatitsihęstatsih (explorers and missionaries), huⁿdatrižuh nęh hatižatǫʔ (fighting and writing) to preserve the languages, and the uⁿditaʔwahstaʔ nęh uⁿdakye:wat (sleeping and waking) of the languages. Unique sources obtained through fieldwork and the collection of oral history interviews with Elders in Oklahoma, Toronto, and Québec in 2019 inform this work. This meticulously chronological approach contributes a reexamination of Wendat (Huron) and Wyandot (Huron) history through the lens of language and community agency.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".