The time course of cross-language activation in deaf ASL–English bilinguals
Bibliographic record
Abstract
What is the time course of cross-language activation in deaf sign-print bilinguals? Prior studies demonstrating cross-language activation in deaf bilinguals used paradigms that would allow strategic or conscious translation. This study investigates whether cross-language activation can be eliminated by reducing the time available for lexical processing. Deaf ASL-English bilinguals and hearing English monolinguals viewed pairs of English words and judged their semantic similarity. Half of the stimuli had phonologically related translations in ASL, but participants saw only English words. We replicated prior findings of cross-language activation despite the introduction of a much faster rate of presentation. Further, the deaf bilinguals were as fast or faster than hearing monolinguals despite the fact that the task was in their second language. The results allow us to rule out the possibility that deaf ASL-English bilinguals only activate ASL phonological forms when given ample time for strategic or conscious translation across their two languages.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".