L2 exposure modulates the scope of planning during first and second language production
Bibliographic record
Abstract
Abstract The psycholinguistic literature suggests that the length of a to-be-spoken phrase impacts the scope of speech planning, as reflected by different patterns of speech onset latencies. However, it is unclear whether such findings extend to first and second language (L1, L2) speech planning. Here, the same bilingual adults produced multi-phrase numerical equations (i.e., with natural break points) and single-phrase numbers (without natural break points) in their L1 and L2. For single-phrase utterances, both L1 and L2 were affected by L2 exposure. For multi-phrase utterances, L1 scope of planning was similar to what has been previously reported for monolinguals; however, L2 scope of planning exhibited variable patterns as a function of individual differences in L2 exposure. Thus, the scope of planning among bilinguals varies as a function of the complexity of their utterances: specifically, by whether people are speaking in their L1 or L2, and bilingual language experience.
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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 | 0.000 | 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) | 0.003 | 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".