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Record W2999774776 · doi:10.1177/0023830919900372

Exploring Japanese EFL Learners’ Attitudes Toward English Pronunciation and its Relationship to Perceived Accentedness

2020· article· en· W2999774776 on OpenAlexafffund
Aki Tsunemoto, Kim McDonough

Bibliographic record

VenueLanguage and Speech · 2020
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsConcordia University
FundersCanada Research Chairs
KeywordsPronunciationPsychologyLinguisticsExploratory research

Abstract

fetched live from OpenAlex

This study investigates what individual differences may play a role in second language (L2) learners’ pronunciation, exploring whether English as a Foreign Language (EFL) learners’ attitudes toward English is linked to their perceived accentedness. Japanese EFL secondary school students ( N = 62) carried out a 69-word read-aloud task and their speech samples were evaluated by 16 raters for accentedness. A ten-item questionnaire examined the attitudes toward L2 pronunciation of Japanese EFL learners. From the questionnaire, an exploratory factor analysis revealed three dimensions: pronunciation significance, interest in English sounds, and confidence in pronunciation. However, only confidence in pronunciation was significantly correlated with accentedness scores. Results are discussed in terms of the relationship between affective factors and L2 pronunciation attainment.

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)0.002
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.190
GPT teacher head0.361
Teacher spread0.171 · 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

Citations21
Published2020
Admission routes2
Has abstractyes

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