Licensing unergative objects in ergative languages: The view from Polynesian
Bibliographic record
Abstract
Abstract Transitive and unergative verbs have long received a uniform syntactic analysis, where they differ in whether an overt object is present (in transitives) or absent (in unergatives). We examine how objects of unergative verbs are case licensed when theyarepresent, focusing on a contrast between two related Polynesian languages: Samoan and Niuean. Both languages have ergative case systems, with subjects of intransitive verbs receiving absolutive case. When unergatives have an overt object, however, a difference emerges. In Samoan, ergative case is absent: the subject of a transitivized unergative is absolutive, and the object receives “middle case.” In Niuean, the resulting transitive exhibits an ergative–absolutive frame. Working within a split‐vP system, we propose that the contrast between Samoan and Niuean results from the interaction of three parametric differences. This comparative analysis highlights the importance of considering unergative constructions when determining the underlying syntax of any given case system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".