Canadian Hockey English: Production and Perception
Bibliographic record
Abstract
The present dissertation investigates the English spoken by ice hockey players in Canada, asking whether there might be a distinct language variety that could be called “Canadian Hockey English”. Applying acoustic analysis to recorded samples from the PAC-LVTI Ontario (Canada) Hockey English Corpus, I study two well-known Canadian English phonetic features: Canadian Raising and the Canadian Vowel Shift. I am particularly interested in determining whether these two variables are conditioned by the degree of hockey players’ engagement in the sport. In parallel, using a three-part online survey, I explore anglophone Ontarians’ knowledge and awareness of both Canadian English and Hockey English. I also test whether respondents can identify hockey players’ speech from listening to speech samples. Results of the production component of the study show that the speech of hockey players displays both Canadian features, and that speakers with a higher degree of involvement in the sport show more Canadian Raising in the /ai/ vowel of the PRICE lexical set, but not in the /au/ vowel of MOUTH. The Canadian Vowel Shift, on the other hand, does not appear to be conditioned by this factor of hockey engagement. The results of the perception component indicate that Ontarian respondents associate lexical, spelling and pronunciation features with Canadian English, which they distinguish from both American and British Englishes. Most respondents also acknowledge the existence of Hockey English, which they identify through lexical features, and which they associate with rurality and a lack of education. Some participants report that HE displays stereotypical features of Canadian English. Although respondents are not accurate in their identification of hockey players, the findings provide valuable insight into the influence of the label “hockey player” on respondents’ ratings of the recorded samples of Canadian English.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".