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Language attitudes and language change

2010· book-chapter· en· W2481279015 on OpenAlexaboutno aff
Sandra Clarke, Andrew Erskine

Bibliographic record

VenueEdinburgh University Press eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsCasualLanguage changeLinguisticsLexiconStyle (visual arts)InsiderPsychologyIntonation (linguistics)HistoryPolitical science

Abstract

fetched live from OpenAlex

Especially since the mid 20th century, Newfoundland English has experienced considerable change, much of which appears to involve weakening or even loss of local speech features, and greater alignment with supralocal (typically, North American) norms. This chapter begins by contextualising language change relative to (largely negative) insider and outsider attitudes to Newfoundland dialects. Using illustrative examples, the chapter documents the social and stylistic patterns associated with ongoing phonetic and grammatical change. Despite fairly rapid intergenerational decline in the use of some local features, others are shown to be more robust: they display obvious style shifting, in that they tend to be avoided by younger speakers in formal, though not in casual, speech styles. Rapid change is also in evidence at the levels of vocabulary and discourse. Loss of traditional lexicon is countered by the borrowing of lexical innovations from outside the province, along with such “trendy” discourse features as quotative be like, and the prosodic features of creaky voice and high rising intonation in statements.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.038
GPT teacher head0.276
Teacher spread0.238 · 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 designObservational
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
Published2010
Admission routes1
Has abstractyes

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