Bibliographic record
Abstract
This paper explores word order in Niuean, a Polynesian language with VSO word order, within the context of theories that attempt to constrain the range and limits of possible word orders across languages (in particular Kayne 1994, Cinque 1999, 2005). First it is argued that V-initial order in Niuean is derived via verbal movement, through maximal predicate fronting. Following the predicate in Niuean are a sequence of inversely-ordered particles (Rackowski and Travis 2000). Various analyses are reviewed which attempt to account for the inverse ordering and to tie the V-initial word order to the inverse order of particles. Finally, the position of arguments is discussed. Their non-inverse ordering presents problems for inverse order derivations, assuming traditional theories of theta role assignment. It is proposed that we continue the trend towards separating arguments from their traditional theta role assigners and merge object arguments directly into specifiers of functional projections (as in, for example, Borer 2005). This allows for a comprehensive analysis of word order in Niuean.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".