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Record W2775205288 · doi:10.7202/1042677ar

Evolution of Self-Repair Behaviour in Narration Among Adult Learners of French as a Second Language

2017· article· en· W2775205288 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Applied Linguistics · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of CanadaUniversité du Québec à Chicoutimi
KeywordsCorrectnessNarrativePsychologyLinguisticsComputer scienceProgramming languagePhilosophy

Abstract

fetched live from OpenAlex

Self-repairs, or revisions of speech that speakers themselves initiate and complete (Salonen & Laakso, 2009), have long been associated with second language (L2) development (e.g., Kormos, 2000a). To our knowledge, however, no research has looked at the evolution of self-repair correctness patterns, that is, the correctness of elements targeted for repair and the correctness of the repair outcomes. Consequently, the present study sought to investigate changes in the self-repair behaviour of English-speaking L2 learners of French over the course of a 5-week period and to verify whether any changes occurred over time. Speech samples of the L2 were collected from 50 adult participants through an elicited narration task at the beginning (Time 1) and the end (Time 2) of a 5-week immersion program. Overall, the results showed that there were qualitative and quantitative changes in self-repairs types, and that correctness of the element being repaired increased significantly over time.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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