Subject dislocation in Ontario English: Insights from sociolinguistic typology
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".