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Record W2889482286 · doi:10.1075/jslp.17039.rui

Nonnative accent and the perceived grammaticality of spoken grammar forms

2018· article· en· W2889482286 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Second Language Pronunciation · 2018
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsGrammaticalityStress (linguistics)GrammarLinguisticsPsychology

Abstract

fetched live from OpenAlex

Abstract Scholars advocate for more classroom attention to be paid to spoken grammar which deviates from commonly taught rules of writing. However, these recommendations have not considered potential barriers that learners may encounter when using spoken grammar with L1 speakers. We investigate one such challenge: the effect of learners’ accents and degree of accentedness on how their use of these forms is subjectively perceived by L1 speakers. Ten non-expert raters rated the grammatical acceptability of four frequent spoken grammar forms, read out by 15 speakers (10 L1 Tagalog, 5 L1 English) rated as having heavy, moderate, or no accents. A one-way ANOVA revealed a significant effect of accent on grammaticality scores. Post-hoc tests showed a strong correlation between accent and perceived grammaticality, with more accented speakers scoring significantly lower on grammaticality. The discussion considers implications for spoken grammar teaching, and future research on the relationship between accent and perceived grammaticality.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.336
Teacher spread0.318 · 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