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Record W2028819862 · doi:10.1017/s1366728905002257

Within-language attention control in second language processing

2005· article· en· W2028819862 on OpenAlexaff
MARLENE TAUBE-SCHIFFNORMAN, Norman Segalowitz

Bibliographic record

VenueBilingualism Language and Cognition · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsConcordia University
Fundersnot available
KeywordsOperationalizationControl (management)Task (project management)PsychologyPerspective (graphical)CognitionCognitive psychologyLanguage proficiencyLinguisticsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This study investigated attention control in tasks involving the processing of relational terms (more highly grammaticized linguistic stimuli: spatial prepositions) and non-relational terms (less highly grammaticized lexical stimuli: nouns) in a first (L1) and second language (L2). Participants were adult bilinguals with greater proficiency in their L1 (English) than in their L2 (French) as determined by self-report and performance on a speeded word classification task. Attention control was operationalized in terms of shift costs obtained in an alternating runs experimental design (Rogers and Monsell, 1995). As hypothesized from consideration of the attention-directing functions of language, participants displayed significantly greater shift costs (lower attention control) for relational terms when performing in the L2 as compared to the L1, but no difference in shift costs for non-relational terms between the two languages. The results are discussed from a cognitive linguistic perspective and in relation to second language proficiency development.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.280
Teacher spread0.265 · 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 designBench or experimental
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

Citations14
Published2005
Admission routes1
Has abstractyes

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