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Record W2317852315 · doi:10.1215/00031283-2322628

Social and Linguistic Constraints on Relativizer Omission in Canadian English

2013· article· en· W2317852315 on OpenAlexaboutno aff
Stephen Levey, Carolyn Hill

Bibliographic record

VenueAmerican Speech · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsRelative clauseVariety (cybernetics)Dependent clauseAnimacyVernacularGrammarHead (geology)SociologyPsychologyComputer sciencePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

This study addresses the social and linguistic constraints on relativizer omission in restrictive relative clauses in a mainstream urban variety of Canadian English. Drawing on the framework of variationist sociolinguistics, the authors test an array of factors that have been traditionally implicated in the choice of relative marker (e.g., syntactic function of the relative marker; animacy and definiteness of the antecedent head NP; length of the relative clause), in addition to investigating less widely researched factors, such as the informational content of the matrix clause and the lexical specificity of the head NP. A variable rule analysis of nonsubject relative clauses extracted from 19 speakers stratified by age, sex, and education reveals that relativizer omission is socially sensitive and that properties of the matrix clause and adjacency effects are key determinants in the selection of the zero variant. Recurrent structural configurations exhibited by zero marked relative clauses in vernacular discourse are indicative of grammaticalization. Comparison with other varieties of English reveals that relativizer omission fails to pattern uniformly, suggesting that there is no vernacular norm in this area of the grammar. This absence of uniformity calls into question recent attempts by researchers to formulate a unitary account of relativizer omission by appealing to putatively general language processing constraints.

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 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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.317
Teacher spread0.297 · 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 teacher head, not a consensus.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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