Majority language skill, not measures of bilingualism, predicts executive attention in bilingual children
Bibliographic record
Abstract
Evidence is mixed regarding whether and why bilingual children might be advantaged in the development of executive functions. Five preregistered hypotheses regarding sources of a bilingual advantage were tested with data from 102 Spanish-English bilingual children and 25 English monolingual children who were administered a test of executive attention, the flanker task, at 7, 8, and 9 years of age. Measures of the children's early and concurrent bilingual exposure and their concurrent English and Spanish skill were available from a larger longitudinal study in which these children participated. Tests of the preregistered hypotheses yielded null findings: The bilingual children's executive attention abilities were unrelated to their amount of early exposure to mixed input, to balance in their early dual language exposure, to balance in their concurrent exposure, to their degree of bilingualism, or to their combined Spanish + English vocabulary score. English vocabulary score was a positive significant correlate of executive attention among the bilingual children, but those bilingual children above the group median in English vocabulary did not outperform the monolingual children when the comparison was adjusted for nonverbal IQ. These findings suggest that a language learning ability may explain the association between bilingualism and executive function. Because the best statistical approach to testing for effects on differences is a matter of dispute, all analyses were conducted with both a difference score and a residual gain score as the outcome variable. The central findings, but not all findings, were the same with both approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".