L1 and L2 picture naming in Mandarin–English bilinguals: A test of Bilingual Dual Coding Theory
Why this work is in the frame
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Bibliographic record
Abstract
This study examined the nature of bilinguals’ conceptual representations and the links from these representations to words in L1 and L2. Specifically, we tested an assumption of the Bilingual Dual Coding Theory that conceptual representations include image representations, and that learning two languages in separate contexts can result in differences in referential images for L1 and L2. Mandarin–English participants named aloud culturally-biased images and culturally-unbiased filler images presented on a computer screen in both Mandarin (L1) and English (L2). Culturally-biased images were named significantly faster in the culturally-congruent language than in the incongruent language. These findings indicate that some image representations are more strongly connected to one language than the other, providing support for the Bilingual Dual Coding Theory.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it