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Record W2760246646 · doi:10.5334/gjgl.310

Spoken syntax in a comparative perspective: The dative and genitive alternation in varieties of English

2017· article· en· W2760246646 on OpenAlexaffabout
Benedikt Szmrecsanyi, Jason Grafmiller, Joan Bresnan, Anette Rosenbach, Sali A. Tagliamonte, Simon Todd

Bibliographic record

VenueGlossa a journal of general linguistics · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
FundersUniversity of Illinois at Urbana-ChampaignVlaamse regeringUniversitetet i OsloKU LeuvenFonds Wetenschappelijk OnderzoekUniversity of CambridgeNational Science Foundation
KeywordsGenitive caseDative caseLinguisticsVarieties of EnglishVariation (astronomy)SyntaxBritish EnglishComputer sciencePerspective (graphical)Natural language processingArtificial intelligenceNoun

Abstract

fetched live from OpenAlex

This paper introduces a new resource designed to facilitate the quantitative investigation of syntactic variation in spoken language from a comparative perspective. The datasets comprise homogeneously annotated collections of “interchangeable” (i.e. competing) genitive and dative variants in four varieties of English: American English, British English, Canadian English, and New Zealand English. To showcase the empirical potential of the data source, we present a suggestive analysis that investigates the extent to which the probabilistic grammar of genitive and dative variant choice differs across varieties. The statistical analysis reveals that while there are a number of subtle probabilistic contrasts between the regional varieties under study, there is overall a striking degree of cross-varietal homogeneity. We conclude by outlining directions for future research. This article is part of the Special Collection: Probabilistic grammars: Syntactic variation in a comparative perspective

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.004
Scholarly communication0.0020.004
Open science0.0000.002
Research integrity0.0000.001
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 head0.046
GPT teacher head0.380
Teacher spread0.334 · 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 designObservational
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

Citations85
Published2017
Admission routes2
Has abstractyes

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Same venueGlossa a journal of general linguisticsSame topicLinguistic Variation and MorphologyFrench-language works237,207