Pitch Patterns in Standard Negation in Alaskan Dene and the Development of Grammatical Tone
Bibliographic record
Abstract
We describe a prosodic pattern that is part of standard negation in five Alaskan Dene languages spoken along the Tanana River. In all of these varieties, this “negative high” differs from the tonal distinction originating from historical constriction. We argue that it originates as an emphatic form of negative verb suffixation that is still partially productive in Koyukon. In the other Tanana languages, the negative high occupies different places in the grammar. In Upper Tanana it is a floating tone which associates with the negative verb stem. In Lower Tanana it is a high tone associated with the negative suffix. In Tanacross and Middle Tanana, the negative high is best analyzed as an utterance-level intonational pattern. To our knowledge, this type of intonational source for tone has not been described for other language families. Our study also has implications for typological studies of standard negation and for language teaching.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".