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Record W2142935586 · doi:10.1017/s1360674305001644

<i>No momentary fancy!</i> The <i>zero</i> ‘complementizer’ in English dialects

2005· article· en· W2142935586 on OpenAlexaff
Sali A. Tagliamonte, Jennifer Smith

Bibliographic record

VenueEnglish Language and Linguistics · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComplementizerZero (linguistics)LinguisticsCollocation (remote sensing)GrammaticalizationFeature (linguistics)Contrast (vision)GrammarSyntaxComputer sciencePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper we analyse variable presence of the complementizer that , i.e. I think that/Ø this is interesting , in a large archive of British dialects. Situating this feature within its historical development and synchronic patterning, we seek to understand the mechanism underlying the choice between that and zero . Our findings reveal that, in contrast to the diachronic record, the zero option is predominant – 91 per cent overall. Statistical analyses of competing factors operating on this feature confirm that grammaticalization processes and grammatical complexity play a role. However, the linguistic characteristics of a previously grammaticalized collocation, I think , exerts a greater effect. Its imprint is visible in multiple internal factors which constrain the zero option in the other contexts. We argue that this recurrent pattern in discourse propels the zero option through the grammar. These findings contribute to research arguing for a strong relationship between frequency and reanalysis in linguistic change.

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)0.003
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.011
GPT teacher head0.280
Teacher spread0.269 · 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

Citations71
Published2005
Admission routes1
Has abstractyes

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