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Record W2302891154 · doi:10.14288/1.0078288

English and Japanese word associations and syntagmatic-paradigmatic shift of Japanese children learning English as a second language

2010· article· en· W2302891154 on OpenAlexaboutno aff
Yuko Yasutake

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsSyntagmatic analysisLinguisticsWord (group theory)PsychologyLanguage acquisitionArtificial intelligenceNatural language processingComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Research in word association studies found that children give predominantly syntagmatic responses (responses from different form classes from stimuli). English children were found to undergo a shift to paradigmatic (responses from the same form classes as stimuli) before age ten (referred to as S-P shift) which is the adult norm. On the other hand, Japanese children do not have S-P shift, and Japanese adults' responses are dominantly syntagmatic (Moran 1968). Leicester (1981) collected English word association responses from Japanese beginner and advanced learners of English as a second language and found S-P shift like increase of paradigmatic responses as English ability improves. This study purports to replicate Leicester's study among children. It is because the existence of the S-P shift in English of second-language learners whose first language does not have the shift would mean that second language learning parallels first language acquisition. Two main hypothesis were tested: 1. That Japanese children learning English as a second language will give dominantly syntagmatic responses in Japanese regardless of their grade level. 2. That Japanese children learning English as a second language of higher grade level will give more paradigmatic responses than those of lower grade level. Three subsidiary hypotheses were tested: 3. That Japanese children learning English as a second language will give different proportion of paradigmatic responses in Japanese and English. 4. That Japanese children learning English as a second language will give different pattern of responses in each language. 5. That Japanese children learning English as a second language will give fewer paradigmatic responses in English than monolingual English children of the same grade. Thirty students each of grades one, three, and five from two Japanese supplementary schools in Vancouver and Seattle were used as subjects. The subjects attend regular English classes at public schools, and therefore, their English ability was assumed to parallel their grade level. 27-item word association test was administered in English and Japanese. The ratio of paradigmatic responses was analyzed according to grade level. In agreement with literature, no grade difference was found among Japanese paradigmatic responses. In English, however, grade one subjects performed most paradigmatically, and thereby, no linear correspondence between English ability and English paradigmatic responses was found. Although English responses were close to the English norm, and Japanese responses to the Japanese norm, a significant number of Japanese responses were given in English association by grade five students. Significant difference in paradigmaticity was also found when two schools were compared as well as between two languages. Grade one students outperformed equivalent English monolingual children in English. It was speculated that young children develop L2 vocabulary systems independently and directly from the start resulting in higher rate of paradigmatic responses, whereas older children initially construct a one to one association between LI and L2, resulting in translation responses and low paradigmaticity in the case of English. School difference suggests that there are some other variables affecting word association.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0110.000

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 head0.202
Teacher spread0.198 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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