MétaCan
Menu
Back to cohort
Record W4210845648 · doi:10.1177/13621688221076418

Investigating the contribution of L1 fluency, L2 initial fluency, working memory and phonological memory to L2 fluency development

2022· article· en· W4210845648 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLanguage Teaching Research · 2022
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFluencyPsychologyCognitive psychologyTask (project management)Working memoryContext (archaeology)First languageTask analysisSecond languageVerbal fluency testLinguisticsCognitionMathematics education

Abstract

fetched live from OpenAlex

Within the same learning context, learners’ outcomes in terms of oral fluency vary greatly. This study tracked the relative contributions that first language (L1) and initial second language (L2) fluency skill and working memory (WM) made to L2 fluency development. We assessed the performance of French-speaking Grade 6 learners’ ( n = 47, mean age: 11) in a 10-month intensive English program in Quebec, Canada using a picture-cue monologic task based on The Suitcase Story and a semi-structured interview based on the Oral Proficiency Interview (OPI). Working memory was assessed using a backward digit span task and phonological memory (PM) via non-word repetition and serial non-word recognition tasks. Overall, results suggest that L1 fluency, WM and PM played only a minor role in learners’ L2 fluency outcomes, whereas learners’ pre-program levels of L2 fluency constituted an important predictor of L2 fluency development regardless of the speech task used to index fluency.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.068
GPT teacher head0.408
Teacher spread0.340 · 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