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Record W4255882545 · doi:10.1017/s000841310000400x

Canadian Raising Retrospect and Prospect

2006· article· en· W4255882545 on OpenAlexaffabout
J. K. Chambers

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRaising (metalworking)DiphthongHistoryLinguisticsPolitical scienceGeographyEngineeringPhilosophy

Abstract

fetched live from OpenAlex

Abstract Canadian Raising, which makes allophonic variants of the low diphthongs /ai/ and /au/, is evaluated with respect to its diachronic, geographic, and synchronic status. Its origins have been established by documentary evidence from 1934. However, comparative dialect evidence from the Linguistic Atlas of the United States and Canada pushes the origins back to the second half of the 19th century. Raising of /ai/ in the northern United States turns out to be different from Canadian Raising, though they overlap. Sociolinguistic studies of (aw)-Fronting in 1980 showed a tendency for fronted onsets to be unraised. Though this was statistically insignificant, any strengthening would threaten the existence of Canadian Raising. Subsequent research shows that the tendency was accidental.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0100.005
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.001

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.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations32
Published2006
Admission routes2
Has abstractyes

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