Bibliographic record
Abstract
The paper discusses the semantics of certain suffixal predicates (bound verbalizers with concrete, root-like semantics) in Amguema Chukchi. I study the semantic oppositions in the system of Chukchi suffixal predicates on the basis of my field data. This study shows that Chukchi suffixal predicates exhibit bleached (as compared to the semantics of the corresponding verbal roots) semantics. Still, this group of suffixes retain some semantic properties which align these predicates with verbal roots and distinguish them from the Chukchi verbalizers in the strict sense. These properties include the specification of the manner of action and of the resultant state to which this action leads. I compare the semantic properties of Chukchi suffixal predicates with the properties of affixal predicates in other languages, including Inuktitut (Eskimo-Aleut) studied by Johns (2007), Bella Coola (Salish) studied by Mithun (1997) and Oneida (Iroquoian) studied by Barrie (2011). This comparison provides an evidence that one of the most probable sources of affixal predication construction in Chukchi is noun incorporation construction. Finally, I highlight some evidence which may serve to distinguish between the two grammaticalization sources of affixal predication in general. Namely, the erosion and bleaching of verbs in noun incorporation construction and the morphologization of light verbs in light verb construction.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".