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Record W2920915806 · doi:10.1353/lan.2019.0012

Prosody, Focus, and Ellipsis in Irish

2019· article· en· W2920915806 on OpenAlexaff
Ryan Bennett, Emily Elfner, James McCloskey

Bibliographic record

VenueLanguage · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsYork University
FundersNational Science Foundation
KeywordsEllipsis (linguistics)Focus (optics)LinguisticsIrishComputer scienceHead (geology)ProsodyPhraseClass (philosophy)Phonological ruleOptimality theoryRelation (database)Natural language processingPhonologyArtificial intelligencePhilosophyPhysics

Abstract

fetched live from OpenAlex

This article analyzes a certain class of misalignments found in contemporary Irish in the relation between syntactic and phonological representations. The mismatches analyzed turn on the phonological requirements of focus (VERUM FOCUS, in particular) and of ellipsis and on how the two sets of requirements interact. It argues that the phonological mechanisms of ellipsis can be overridden when the phonological requirements of F-marking need to be satisfied. The analysis requires a theoretical framework in which the postsyntactic computation is characterized by parallel and simultaneous optimization. In particular, it is argued that certain facets of ellipsis, morphophonology, and prosody are computed in parallel, as in classic optimality theory. The analysis also relies crucially on a kind of head movement (from specifier to a commanding head position) whose existence is predicted by current conceptions of phrase structure but which seems to be little documented.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.229
Teacher spread0.216 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations94
Published2019
Admission routes1
Has abstractyes

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