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Record W4396775187 · doi:10.1017/s0272263124000317

How well are primary and secondary meanings of L2 words acquired?

2024· article· en· W4396775187 on OpenAlex
Beatriz González‐Fernández, Stuart Webb

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.

Bibliographic record

VenueStudies in Second Language Acquisition · 2024
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsWestern University
Fundersnot available
KeywordsPrimary (astronomy)LinguisticsPsychologyCognitive psychologyPhilosophyPhysicsAstrophysics

Abstract

fetched live from OpenAlex

Abstract Most words in a language have more than one meaning. Yet, few studies have explicitly examined the acquisition of secondary meanings of L2 words and the extent to which polysemy and homonymy affect vocabulary learning. This study explores the effect of polysemy and homonymy on the deliberate acquisition of the form–meaning connections of L2 words. Thirty-six EFL learners (compared with a control group of 30) learned secondary polysemous and homonymous meanings of familiar words and primary meanings of unfamiliar words using flashcards. Knowledge of target words was measured using meaning–recall and meaning–recognition tests immediately after the treatment and again one week later. The findings indicated that learning another meaning for a familiar word was just as difficult as learning the primary meaning of an unfamiliar word, suggesting that the type of meaning (primary, secondary polysemous, or secondary homonymous) might not be an influencing factor in the deliberate acquisition of L2 words.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0310.000

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 head0.018
GPT teacher head0.317
Teacher spread0.299 · 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