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Record W2559453558 · doi:10.1017/s1366728916000304

The influence of classroom input and community exposure on the learning of variable grammar

2016· article· en· W2559453558 on OpenAlexaffabout
Raymond Mougeon, Katherine Rehner

Bibliographic record

VenueBilingualism Language and Cognition · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsGrammarMathematics educationPsychologyCompetence (human resources)PedagogyAP French LanguageClass (philosophy)LinguisticsComputer scienceForeign languageArtificial intelligenceSocial psychology

Abstract

fetched live from OpenAlex

As pointed out by Carroll (Carroll), our team has investigated the influence of input on the spoken French competence of older Ontario bilinguals. Our research has examined the learning of invariant and variable aspects of French grammar. We focus here on the learning of variation, since it is an under-researched topic not covered by Carroll. Our research examines adolescent speakers of Ontario French from French-medium schools (e.g., Mougeon & Beniak, 1991), same-age immersion students (e.g., Mougeon, Nadasdi & Rehner, 2010) and advanced learners from a bilingual university (e.g., Mougeon & Rehner, 2015). Two key dimensions of input are teacher classroom speech and frequency of use of French in the community for the Franco-Ontarian students and amount of extra-curricular interactions with Francophones for the FSL students. Having collected corpora from these student groups, we compared the output of learners with primarily classroom-based input with that of learners with broader ranging (extra-) curricular input. The availability of teacher in-class recordings for these learner groups has been crucial in identifying additional factors influencing these students’ output.

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)0.003
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 score0.233
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.035
GPT teacher head0.365
Teacher spread0.330 · 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 designQualitative
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

Citations8
Published2016
Admission routes2
Has abstractyes

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