Alternations of classificatory verb stems in Tłıchǫ Yatıì: a cognitive semantic account
Bibliographic record
Abstract
Abstract This paper investigates the phenomenon of ‘classificatory verbs’, i.e. a set of motion and positional verbs that show stem alternations depending on the semantic features of one of their arguments in Tłı̨chǫ Yatıì (Dogrib), based on field notes and documentary sources of the language. The paper shows that Tłı̨chǫ classificatory verbal categories belong to four semantic subclasses which have inconsistent stem inventories caused by the presence or absence of some semantic features. Stem inventories of locative verb systems vary depending on the scalar [ effort ] feature, and those of motion verbs correlate with the scalar [ agentive ] feature. The paper explains why other semantically related verbs do not show stem alternations and proposes contrastive hierarchies to represent variations in stem inventories intra- and cross-linguistically assuming that the selection of a stem for a particular semantic category follows a series of binary choices that characterize the opposition’s active in the language.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".