Cross-language activation of idiom meanings: Evidence from French– Vietnamese– and Indonesian–English bilinguals
Bibliographic record
Abstract
Abstract The aim of the present study was to determine whether bilinguals activate the figurative meaning of an idiom that is specific to one language when they are exposed to its translation in their other language. We used a cross-modal priming task in which participants heard L2 English sentences that ended with an idiom translated from their L1. They then saw a visually presented stimulus that was either related to the meaning of the L1 idiom, a matched control word, or a nonword, and made a lexical decision. Three experiments were run, each with a different group of bilinguals (French–English, Vietnamese–English, and Indonesian–English), and each with a monolingual English control group. In all three studies, the effect of relatedness for bilinguals and monolinguals differed, demonstrating cross-language activation of idiom meanings. Evidence was obtained that suggested that culture-specific information in idioms influenced processing.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".