Cognate effect and lexical processing in English-Spanish and Spanish-English bilinguals
Bibliographic record
Abstract
Cognates have served as a useful tool for investigating the bilingual lexicon inmany studies, but very little research has been carried out on different types ofcognates, specifically, partial cognates and their role in cross-linguistic effect.The present study examines cognate effect in the speech production and acceptabilityjudgment of two groups of highly proficient, late-onset English-Spanish(n = 12) and Spanish-English (n = 12) bilinguals within a single-language (English)context. The findings of two tasks, a production task, whereby participants wereasked to spontaneously produce synonyms to prompt words, and an acceptabilityjudgment task of a variety of sentences including use of false and partial English-Spanish cognates are reported here, framed within non-selective, integrated modelsof lexical representation. The results suggest a significant cognate effect in both bilingualgroups in both tasks compared to their monolingual counterparts with, surprisingly,greater significance demonstrated from L2 to L1 influence, particularly inproduction. These findings add to the growing support for semantic modulation atthe conceptual level of lexical processing in highly proficient bilinguals. doi:10.5294/laclil.2016.9.1.8
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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 | 0.003 |
| 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 | 0.000 |
| 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".