‘How do you get to Tim Hortons?’ Direction-giving in Ontario dialects
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.
Bibliographic record
Abstract
Abstract In this study, we target the speech act of direction-giving using variationist sociolinguistic methods within a corpus of vernacular speech from six Ontario communities. Not only do we find social and geographical correlates to linguistic choices in direction-giving, but we also establish the influence of the physical layout of the community/place in question. Direction-giving in the urban center of Toronto (Southern Ontario) contrasts with five Northern Ontario communities. Northerners use more relative directions, while Torontonians use more cardinal directions, landmarks, and proper street names – for example, Go east on Bloor to the Manulife Centre . We also find that specific lexical choices (e.g., Take a right vs. Make a right ) distinguish direction-givers in Northern Ontario from those in Toronto. These differences identify direction-giving as an ideal site for sociolinguistic and dialectological investigation and corroborate previous findings documenting regional variation in Canadian English.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it