Juggling arguments: VSVO and other word orders in Hul’q’umi’num’ Salish SVCs
Bibliographic record
Abstract
This paper investigates the word order of serial-verb constructions in Hul’q’umi’num’ Salish. Hul’q’umi’num’ SVCs are monoclausal constructions consisting of two or more verbs that can function as independent lexical verbs, have matching aspect, share one or more arguments, and are not connected by any linking element. Two-verb SVCs may consist of transitive and intransitive verbs. The first question concerns subject and object NP placement. For constructions with two overt NPs, an alternating VSVO pattern is both preferred in elicitation, and the only order occurring in the corpus. Only shared arguments may intervene between the verb components. Hul’q’umi’num’ SVCs exhibit flexible word order in elicitation, but certain grammatical word orders generate ambiguity. Various pragmatic strategies work together to prevent or rescue ambiguous constructions. SVCs are an understudied feature of Central Salish languages; thus investigation of this topic broadens the scope of the current literature.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".