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Record W2530484833

Sociophonetic history of Newfoundland English in Happy Valley-Goose Bay, Labrador

2015· dissertation· en· W2530484833 on OpenAlexfundaboutno aff
Jenna Edwards

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaMemorial University of Newfoundland
KeywordsLevellingBayGeographyVowelGooseHistoryArchaeologyLinguisticsGeologyCartographyPaleontology
DOInot available

Abstract

fetched live from OpenAlex

In this paper, I report on the variety of English spoken in the relatively new community of Happy Valley-Goose Bay, Labrador. The efects of dialect contact and the process of dialect levelling (Trudgill 1986; Britain 1997, Kerswill and Williams 2000; Kerswill 2002) are observed by examining the development of several vowels in the Happy Valley- Goose Bay vowel system. In this community the migrant generation showed evidence of mixing. The frst generation showed the most evidence of levelling along with the emergence of new distinctions. The second generation showed some evidence of levelling, the emergence of new distinctions, and in some cases a return to patterns present in the migrant generation. These results indicate that diferent vowels within a dialect can move through the stages of dialect contact at diferent rates due to the multitude of infuences on the process of dialect contact.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.039
GPT teacher head0.297
Teacher spread0.259 · 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 routes2
Has abstractyes

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