Bibliographic record
Abstract
Based on original fieldwork and data from texts, this paper details applicatives in Hul’q’umi’num’, spoken along the western shores of the Salish Sea in British Columbia, Canada. Hul’q’umi’num’ has four applicative constructions marked by suffixes that allow the expression of objects with such semantic roles as goal, beneficiary, direction, and cause/stimulus. Applicatives are divided into two types: relationals, which are formed on intransitive bases, and redirectives, formed on transitive bases. (Transitivity is easily ascertained in Hul’q’umi’num’ due to transitive morphology and ergative inflection.) Hul’q’umi’num’ is a direct/oblique object language: only two NPs per verb can be direct arguments and other NPs are introduced by oblique marking. In semantically ditransitive constructions, the applied object is always the direct object and thus there are no non-applicative counterparts for redirective applicatives. As a polysynthetic language, Hul’q’umi’num’ exhibits voice and valence marked by suffixes- limited control, passive, causative, reflexive, reciprocal, and antipassive-as well as lexical suffixes with the semantic meaning of nominals. These all co-occur with the applicative suffixes. Applicative constructions are an important device for expressing topic-worthy NPs as direct objects or, if they are also passivized, as subjects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".