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Record W4220852420 · doi:10.5539/ells.v12n2p32

A Grammatical-Lexicographic Study of Structure in Some Selected Samples of Second Language Mental Lexicon of Kuwaiti Speakers

2022· article· en· W4220852420 on OpenAlexvenueno aff
Yousef M. Alenezi, Maisoun Alzankawi

Bibliographic record

VenueEnglish Language and Literature Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsWord AssociationVocabularyPsychologyFirst languageLexiconTest (biology)Meaning (existential)Association (psychology)Mental lexicon

Abstract

fetched live from OpenAlex

This study investigates Kuwaiti learners’ use of English Word Associations. The issue of how second language (L2) learners structure their lexical knowledge has been of interest to L2 researchers for decades. However, the role of language proficiency in determining qualitative and quantitative features of lexical knowledge is unexplored. This study replicates Zareva (2007); therefore, the word association test used is the same. For this purpose, 40 Kuwait University students were distributed into two clusters according to their language aptitude levels. In addition, another set of five native speakers of English was tested to compare the organisation of word association of the Kuwaiti speakers to the organisation of word association of the native speakers of English. The method involved a written vocabulary test consisting of 76 different word items where subjects were asked to select the suitable answer out of 4 possible answers related to the given word’s meaning and think of three possible words to associate with the given word. Results showed consistency with Zareva’s findings and suggest that variations in lexical knowledge organisation involving native speakers and L2 learners are quantitative instead of qualitative.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.292
Teacher spread0.282 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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