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Record W2030066779 · doi:10.3138/cmlr.2346

The Predictive Effects of L1 and L2 Early Literacy Indicators on Reading in French Immersion

2014· article· en· W2030066779 on OpenAlexvenueno aff
Renée Bourgoin

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2014
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPhonological awarenessReading (process)PsychologyFrench immersionPredictive validityDevelopmental psychologyMathematics educationPedagogyLinguistics

Abstract

fetched live from OpenAlex

Abstract: This study explored the predictive effects of within- and cross-language early literacy indicators with regard to second language (L2) reading achievement in a Grade 3 entry-point French immersion (FI) program. Kindergarten students (N = 83) in a regular English program were administered English early literacy measures. Three years later, once students entered the FI, 56 students from the original cohort were reassessed using French literacy measures. This allowed for an examination of the long-term connections between first language (L1) early literacy indicators and L2 reading outcomes. Regression analysis revealed that L1 early literacy skills relating to aspects of phonological awareness and, more importantly, alphabetic knowledge were significant predictors of L2 reading even when school-based L2 learning was delayed several years. With respect to the French literacy indicators, knowledge of the alphabet and related measures were again significant predictors of L2 reading performance. The predictive effects of French indicators were significant even in the first few months of FI. These results provide additional information about the predictive effects of within- and cross-language early literacy indicators and the extent to which they can be used to identify students who may be at risk for reading difficulties in their L2.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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.

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

Citations30
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicReading and Literacy DevelopmentFrench-language works237,207