The impact of multilingualism and proficiency on L2 vocabulary knowledge: contrasting high and low multilinguals
Bibliographic record
Abstract
This study investigates the effects of multilingualism and the degree of proficiency in different languages on vocabulary knowledge among Spanish language learners.Participants completed a 160word meaning recall test designed to measure their knowledge of the 8,000 most frequent Spanish words and a self-assessment questionnaire on their multilingual profile.The results show that students with high multilingual profiles (knowing more than three languages) demonstrated greater vocabulary knowledge than learners with low multilingual profiles (knowing three or fewer languages), especially for words in low-frequency vocabulary ranges.However, the positive impact of multilingualism on vocabulary knowledge is only significant among learners with a high proficiency in Spanish (C1-C2 level), suggesting that identifying as highly proficient in multiple languages is advantageous only when learning vocabulary at higher proficiency levels.These results corroborate the benefits of multilingualism for fostering vocabulary development in a foreign language, while offering a nuanced picture of how additional languages (LX) are acquired by multilingual learners.
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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 | 0.004 |
| 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 | 0.000 | 0.001 |
| 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".