MétaCan
Menu
Back to cohort
Record W2991354083 · doi:10.1017/s0142716419000420

Sentence repetition and non-word repetition in early total French immersion

2019· article· en· W2991354083 on OpenAlexaffabout
Maureen Scheidnes

Bibliographic record

VenueApplied Psycholinguistics · 2019
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPsychologySentenceRepetition (rhetorical device)Immersion (mathematics)Neuroscience of multilingualismFrench immersionLinguisticsAudiologyDevelopmental psychologyMathematics educationMedicineMathematics

Abstract

fetched live from OpenAlex

Abstract Recent research has focused on bilingual children’s performance on non-word repetition (NWR) and sentence repetition (SR) tasks, but it remains unclear how their scores can be expected to vary as a function of language exposure, which creates challenges for developing age-appropriate performance expectations. With the goal of examining the impact of limited language exposure on these tasks, French NWR and SR performance from 33 first graders (mean age 6 years, 10 months) in early total French immersion in English-speaking Canada was compared to prior work on bilinguals acquiring French in France. With a mean length of exposure of 1 year, 7 months, but a mean cumulative length of exposure of only 3 months, the children in immersion have much less daily exposure to French than the bilinguals in France. The results showed that children in immersion patterned with the other bilinguals for NWR, but had much weaker SR performance. Within-subjects analyses revealed that, for SR, the children in immersion had stronger scores on wh- questions and relative clauses, which suggests that these structures may be less sensitive to language exposure.

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 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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 teacher head, not a consensus.

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

Citations7
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueApplied PsycholinguisticsSame topicLanguage Development and DisordersFrench-language works237,207