MétaCan
Menu
Back to cohort
Record W2506002331 · doi:10.1075/la.167.16mas

Deriving inverse order

2010· book-chapter· en· W2506002331 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLinguistik aktuell · 2010
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInverseOrder (exchange)Applied mathematicsMathematicsComputer scienceEconomicsGeometry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.622
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.005

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.

Opus teacher head0.028
GPT teacher head0.226
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it