Methods of Madness: The Tuscarora Language Committee
Bibliographic record
Abstract
The Tuscarora Nation is one of the six nations of the Haudenosaunee (people of the Longhouse) presently situated in western New York. Traditionally, it is believed that the Tuscarora originated near the St. Lawrence Valley along with the other five nations (Hale, 1883; Johnson, 1967), eventually separating and migrating southward into present day North Carolina. In 1722, after devastation of their land base during the Tuscarora War, they journeyed north and were taken into the Iroquois Confederacy, joining the Cayugas and Oneidas as one of the Younger Brothers; the Mohawk, Seneca, and Onondaga were considered the Older Brothers. We have since been relocated to reservation lands about twelve miles southeast of Niagara Falls, New York. At one time, the Tuscarora language, a member of the Iroquoian language family, was spoken as the mother tongue, transmitted across the generations, and used for all informal and formal situations. In the 1800s, owing to the proximity of the non-Native society and the influence of boarding schools, the language began to lose its importance. Today, we have about four or five fluent Elders remaining, all in their seventies and eighties, and the language is in the shadows of extinction. The Tuscarora Language Committee came into existence in the fall of 1995, developed from a final paper I had written for a course taken at the American Indian Language Development Institute (AILDI) at the University of Arizona. A language revitalization program, tailored to our own individual first language communities, was based on our needs and on what stage our language community was in. The Tuscarora language, according to renowned sociolinguist Dr. Joshua A. Fishman’s Graded Intergenerational Disruption Scale, could be classified as being in stage seven, where language users are “socially integrated and ethnolinguistically active populations but beyond child-bearing age ” (Fishman, 1991, p. 89). Our remaining handful of Tuscarora Elder speakers have become involved in our language revitalization efforts and are willing to help promote and restore their first language. At one time, there were also Tuscarora speakers located on the Six Nations Reserve in Ontario, Canada, but, at this time, I am unaware of any fluent speakers remaining, although there may be several residents from one of the other Haudenosaunee communities with some familiarity with
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".