Bilingual and monolingual adults’ lexical choice in storytelling
Bibliographic record
Abstract
Abstract Bilinguals often have a harder time accessing words for production than monolinguals, perhaps because they have less exposure to words from each language (the weaker-links hypothesis). This research on lexical access mostly comes from studies of words in isolation. The purpose of the present study was to test whether bilinguals also show greater lexical access difficulties than monolinguals when telling a story. In the context of a narrative, we predicted that bilinguals would produce fewer different words and words of higher frequency than monolinguals, in order to make lexical access easier. For the same reason, we also predicted that bilinguals would use more cognates than monolinguals. English monolinguals, French monolinguals, and highly proficient French-English bilinguals watched a cartoon and told the story back. We coded the words they used for frequency and cognate status. In English, the results showed little difference between bilinguals and monolinguals on word frequency and cognate status. In French, first-language-English bilinguals used higher frequency words than first-language-French bilinguals. These results support predictions from the weaker-links hypothesis in lexical access for storytelling, albeit only for French.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".