Bibliographic record
Abstract
Abstract Of the numerous factors affecting language development, a particular role has been assigned to Metalinguistic Awareness (MLA) as a major constituent of the cognitive development of experienced language learners, while being itself a key to accelerated language learning (e.g., Jessner, 2008 ). The present study explores the relationship between multilingual usage and MLA in French-speaking Quebeckers (n = 66) with different language backgrounds who start to learn German after English in a formal setting. ‘Multilingual experience’ was operationalized by the frequency and the diversity of foreign language use across 10 different contexts of use. A reflexive dimension of MLA was assessed by means of the THAM-3 ( Pinto & El Euch, 2015 ), and complemented by think-aloud protocols produced during a multilingual translation task, which reflected an applied dimension of MLA. Multiple regression analyses suggest that both frequency and diversity of non-native language use in specifically literacy-based activities predicted the applied dimension of MLA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".