Second Language Phrases Acquisition: a Corpus-based Survey ACQUISITION DES EXPRESSIONS DE LA SECONDE LANGUE: ENQUETE BASEE SUR LE CORPUS
Bibliographic record
Abstract
English phrases play an important role in language description and acquisition. The most frequently used English phrases that should take priority of learning can be sorted out mainly by quantitative analysis with the help of modern English corpus. Second language phrases acquisition deserves a considerable research topic in second language vocabulary acquisition. Key Words: lexical phrases, second language phrases acquisition, corpus Resume: Les expressions anglaises jouent un role important dans la description et l’acquisition linguistiques. Les expressions anglaises utilisees le plus frequemment qui donnent la priorite a l’apprentissage peuvent etre degagees principalement par des analyses quantitaves avec l’aide du corpus d’anglais moderne. L’acquisition des expressions anglaises de la seconde langue merite d’etre un sujet de recherches important dans l’acquisition du vocabulaire de la seconde langue. Mots-Cles: expressions lexicales, acquisition des expressions de la seconde langue, corpus
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 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 teacher head, 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".