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Record W2292277171

Wlthtn-category variation in l2 english vowel learning

2009· article· en· W2292277171 on OpenAlexafffundvenueabout
Ron I. Thomson, Talia Isaacs

Bibliographic record

VenueCanadian acoustics · 2009
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcGill UniversityBrock University
FundersSocial Sciences and Humanities Research Council of CanadaBrock University
KeywordsMandarin ChineseVowelLinguisticsVariation (astronomy)Word (group theory)Computer scienceWord listSecond languagePsychologyEnglish as a second languageAmerican EnglishSlavic languagesSpeech recognitionArtificial intelligenceMathematics education
DOInot available

Abstract

fetched live from OpenAlex

A study was conducted to investigate whether second language (L2) learners had the ability to produce English vowels when they were presented in more familiar words and when learners had access to orthographic representations of those words. A number of Standard Mandarin-speaking and Slavic students participated in the study. All these students had enrolled in intensive ESL classes for an average of 5.2 months and were assessed as beginners by the Canadian Language Benchmarks. Stimuli for the investigations comprised of a list of 30 English progressive verbs containing 10 target Canadian English vowels. Words were also selected to include a range of onsets so as to solve any potential contextual biases in performance. The resulting word list was randomized and a male speaker of Canadian English was recorded producing each word with a five second pause inserted between items.

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)0.004
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.290
Teacher spread0.272 · 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

Citations10
Published2009
Admission routes4
Has abstractyes

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