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Record W2028410381 · doi:10.1121/1.4920801

/l/-darkness in Newfoundland English

2015· article· en· W2028410381 on OpenAlexaffabout
Sara Mackenzie, Paul De Decker, Rosanna Pierson

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCodaVariation (astronomy)DarknessSyllableIrishAmerican EnglishPosition (finance)MathematicsLinguisticsGeologyPhysicsOpticsAstrophysicsSeismologyPhilosophy

Abstract

fetched live from OpenAlex

This paper reports on the first acoustic study on the allophonic distribution of /l/ in Newfoundland, Canada, where Irish-settled varieties of English exhibit light variants in both coda and onset positions (Clarke 2010, Paddock 1982). This pattern is distinct from standard North American English which has a dark, or velarized form in coda position and light [l] in onsets (Halle & Mohanan 1985). Productions from 10 male and 13 female speakers from across the province were collected and spectrally analyzed using Praat 5.4 (Boersma & Weenink 2014). Darkness measurements (F2-F1 at the midpoint of each /l/) were calculated and within-subjects t-tests conducted to examine differences across onset and coda positions. Results show the standard North American pattern exists within our sample, with significantly darker /l/s in coda position. However, some speakers showed coda darkness values comparable to onset /l/s of those speakers with the allophonic variation. Others had darkness values comparable to coda realizations in all positions. These findings are discussed using a model of dialect contact that identifies how, despite the presence of the dominant North American pattern, some speakers of Newfoundland English maintain a several hundreds year old pattern which lacks allophonic variation across syllable positions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.306
Teacher spread0.279 · 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 teacher head, not a consensus.

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

Citations1
Published2015
Admission routes2
Has abstractyes

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