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Record W4307720925 · doi:10.1017/jlg.2022.10

Subject relative<i>who</i>in Ontario, Canada: Change from above in a transplanted ecology

2022· article· en· W4307720925 on OpenAlexafffundabout
Marisa Brook, Sali A. Tagliamonte

Bibliographic record

VenueJournal of Linguistic Geography · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsPrestigeGeographyRange (aeronautics)Subject (documents)DemographyEcologyHistorySociologyLinguisticsBiology

Abstract

fetched live from OpenAlex

Abstract Whoas a restrictive relativizer in English is an old change from above. In urban dialects, it still acts as a prestige form, whereas it is infrequent or negligible in rural British and American varieties. We compare earlier findings from Toronto, the largest city in the province of Ontario (D’Arcy & Tagliamonte, 2010), with a range of communities from the Ontario Dialects Project (Tagliamonte, 2003–present). While none of the rural locations has as muchwhoas Toronto, there is a substantial range. Regions along the major highways to the north and east of the city have morewho, while the smaller towns in less accessible locations have less, consistent with a Cascade Model effect (Labov, 2003). Nonetheless,whoshows evidence of diffusion, increasing in apparent time in recent decades. We suggest that this reflects overt pressure from above, consistent with the enduring role that prestige plays in English relativizer variation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0080.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.256
Teacher spread0.233 · 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

Citations2
Published2022
Admission routes3
Has abstractyes

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