The Role of Intercommunication in Athabascan Revitalization
Bibliographic record
Abstract
The Role of Intercommunication in Athabascan Revitalization. A mini-conference on "The Role of Intercommunication in Athabascan Revitalization" will be held at the Research Institute for Languages & Cultures of Asia & Africa (ILCAA), Tokyo University of Foreign Studies, February 16-18, 2004. The organizers are Jeff Leer and Tokusu Kurebito, and the Guest speaker will be Eric Hamp (U of Chicago), "Distant and Immediate Relations, Linguistic and Non-linguistic Statements." Other presentations will include: Loren Bommelyn (Tolowa, Del Norte High School), "Revitalization of Tolowa language and culture" Tasaku Tsunoda (U of Tokyo), "Language revitalization in Australia" Linda Harvey (S Tutchone, Yukon Native Language Centre), "Language Revitalization in the Yukon Territory" Toshihide Nakayama (ILCAA), "Language Revitalization in Nootka" Bruce Starlight (Sarcee, Tsuut'ina Band), "Language revitalization on the Tsuut'ina Reserve" Gary Donovan (U of Calgary), "Strategies for learner-initiated interactions in language acquisition" Martha Austin (Navajo, Diné College), "Child language acquisition in Navajo" and "Navajo Code Talkers: a Linguistic View" Tokusu Kurebito (ILCAA), "Language revitalization in Chukchi" Eliza Jones (Koyukon, Alaska Native Language Center), "Aspectual dimensions of the seriative verb in Koyukon Athabascan" Nobukatsu Minoura (Tokyo), "Wh-questions in some Athabascan languages" Fibbie Tatti (S Slavey, Language Commissioner of the NWT), "Language maintenance and revitalization in the Northwest Territories" Jeff Leer (Alaska Native Language Center & ILCAA), "Using gesture and sign to teach Athabascan languages." Citation: Research Institute for Languages & Cultures of Asia & Africa (ILCAA), Tokyo University of Foreign Studies, February 16-18, 2004.
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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 | 0.004 |
| 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 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".