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Record W1890935541 · doi:10.1111/lang.12053

Opening the Window on Comprehensible Pronunciation After 19 Years: A Workplace Training Study

2014· article· en· W1890935541 on OpenAlexafffund
Tracey M. Derwing, Murray J. Munro, Jennifer A. Foote, Erin Waugh, Jason Fleming

Bibliographic record

VenueLanguage Learning · 2014
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsNorQuest CollegeConcordia UniversitySimon Fraser UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPronunciationPsychologyFluencyIntelligibility (philosophy)Stress (linguistics)ProsodyPerceptionLinguisticsPhoneticsCognitive psychologyMathematics education

Abstract

fetched live from OpenAlex

We present the outcomes of a pronunciation training program conducted in a workplace setting with second language speakers who had lived in an English‐speaking environment for an average of 19 years. The research questions concerned whether improvement would occur in the learners’ perception of certain segments and prosody; in the comprehensibility, accentedness, and fluency of their productions as judged by listeners; and in their speech intelligibility. Despite seemingly stable speech patterns, pre‐ and postintervention tests demonstrated significant improvement in perception and in comprehensibility and intelligibility. However, no difference was noted in fluency, and accent was perceived to be stronger in one posttest. Thus the pronunciation instruction was effective, even in putatively fossilized individuals. This study contributes to research showing the partial independence of accent and other speech dimensions.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.345
Teacher spread0.313 · 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

Citations129
Published2014
Admission routes2
Has abstractyes

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