MétaCan
Menu
Back to cohort
Record W2031446367 · doi:10.1075/jicb.2.1.02bur

Three factors in vocabulary acquisition in a university French immersion adjunct context

2014· article· en· W2031446367 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

VenueJournal of Immersion and Content-Based Language Education · 2014
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAdjunctCLARITYVocabularyFrench immersionContext (archaeology)PsychologyClass (philosophy)Mathematics educationComputer scienceLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

This study investigates the role of teaching, context, and repetition in the acquisition of specialized vocabulary. It involves thirteen students enrolled in a French immersion class linked to a French adjunct language course at the University of Ottawa, Canada. Based on Webb’s (2008) classification, the researchers have examined and rated the contexts in which students were exposed to a sample of thirty words in their immersion course (lectures and readings). Of these, some (n = 22) were taught explicitly over the semester and others (n = 8) were not taught, as they were words students encountered incidentally in their readings or lectures. Results in this study showed that: a) incidental exposure did not lead to vocabulary acquisition regardless of clarity of context and number of exposures, and b) explicit teaching led to differential learning outcomes not fully explained by clarity of context or number of exposures. The study concludes with a discussion of other factors affecting vocabulary learning in the immersion adjunct context.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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