Bibliographic record
Abstract
Canadian Raising is a phonological process which raises the nucleus of both the /aɪ/ and /aʊ/ diphthongs above 60Hz (Labov et al. 2005: ANAE, p. 205) before voiceless segments. The /aɪ/ diphthong is raised in much of Canada as well as in many American dialects, including the Inland North, resulting in alternations among a large number of minimal pairs distinguished by their voicing such as /lʌɪf/ ‘life’ ∼ /laɪv/ ‘live’ and /brʌɪt/ ‘bright’ ∼ /braɪd/ ‘bride.' This /aɪ/-raising is a classic example of phonological opacity because it is canonically conditioned not only by surface voiceless segments but also underlyingly voiceless segments, as with the flapped /t/ in /rʌɪɾɚ/ ‘writer.’ However, not all /aɪ/-raising speakers exhibit this opaque pattern: so-called transparent or phonetic /aɪ/-raising speakers only raise before surface voiceless segments as in /rʌɪt/ ‘write' but not /raɪɾɚ/ ‘writer.’ The existence of this latter group has renewed debate about the ultimate origins of the raising patterns and the relationship between transparent and canonical raising. This paper contributes to that discussion with a new model of child language acquisition in variable settings, finding that the presence of transparent /aɪ/-raising as well as its rare attestation and sparse distribution can be accounted for as a contact phenomenon in which some child learners innovate a novel transparent raising pattern when their communities contain the appropriate mix of canonical raising and non-raising speakers.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".