Bilingual lexical access during L1 sentence reading: The effects of L2 knowledge, semantic constraint, and L1–L2 intermixing.
Bibliographic record
Abstract
Libben and Titone (2009) recently observed that cognate facilitation and interlingual homograph interference were attenuated by increased semantic constraint during bilingual second language (L2) reading, using eye movement measures. We now investigate whether cross-language activation also occurs during first language (L1) reading as a function of age of L2 acquisition and task demands (i.e., inclusion of L2 sentences). In Experiment 1, participants read high and low constraint English (L1) sentences containing interlingual homographs, cognates, or control words. In Experiment 2, we included French (L2) filler sentences to increase salience of the L2 during L1 reading. The results suggest that bilinguals reading in their L1 show nonselective activation to the extent that they acquired their L2 early in life. Similar to our previous work on L2 reading, high contextual constraint attenuated cross-language activation for cognates. The inclusion of French filler items promoted greater cross-language activation, especially for late stage reading measures. Thus, L1 bilingual reading is modulated by L2 knowledge, semantic constraint, and task demands.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".