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Record W7098679578

Linguistic resistance on the New Brunswick-Maine border

2015· article· en· W7098679578 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)Section (typography)Relation (database)Language contactConvergence (economics)American EnglishLinguistic changeEthnic group
DOInot available

Abstract

fetched live from OpenAlex

Comparison of New Brunswick data from Scargill and Warkentin’s 1972 survey of Canadian English and from the Dialect Topography Project (1994-present) reveals a significant convergence over the past 30 years towards American English forms in seventy-eight percent of the items studied. This is noteworthy in itself, given that there is little evidence of sufficient contact to determine any pattern of linguistic diffusion. Still more remarkable, however, are the data from responses to the Dialect Topography questionnaire by younger speakers along one section of the New Brunswick-Maine border. There, in an area where there is significant social contact with Americans, the evidence indicates that Canadian youth are using fewer American forms than their peers in the rest of the province. This paper considers the border effect in the responses of 14-19 year-olds living in St. Stephen, New Brunswick, and in the adjacent town of Calais, Maine. It examines 17 items of the DTP questionnaire that were determined to be Canadian/U.S. shibboleths after Chambers ’ original Golden Horseshoe Study in 1994, and discusses the results in relation to

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.086
GPT teacher head0.350
Teacher spread0.264 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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