MétaCan
Menu
Back to cohort
Record W4388426329 · doi:10.1017/s0954394523000236

Subject dislocation in Ontario English: Insights from sociolinguistic typology

2023· article· en· W4388426329 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLanguage Variation and Change · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTypologySubject (documents)LinguisticsSociocultural evolutionNorm (philosophy)VernacularNeuroscience of multilingualismDislocationSociologyHistoryPARRYAnthropologyEpistemologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract Subject dislocation (SD) is common across languages. In French, it is a vernacular norm. In English, it is comparatively rare. This article examines English SD in a unique contrastive situation in Ontario, Canada: two communities where SD is a community norm, one where individuals speak both English and French (Kapuskasing), and the other where the population speaks English only (Parry Sound). Dislocated subjects are produced by the same underlying linguistic mechanisms in both places, with parallel constraints by type of subject and intervening material, suggesting a typological universal. However, SD is age-graded in Kapuskasing, regardless of heritage language. In Parry Sound, it is obsolescent, in steady decline over the twentieth century. We conclude that while typological trends are underlain by universal cognitive processes, locally embedded sociocultural influences are the source of differentiation.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.961
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.043
GPT teacher head0.302
Teacher spread0.258 · 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