Maîtrise des clitiques datifs dans les structures bitransitives en français L2 par des apprenants anglophones : influence de la structure argumentale de la L1
Bibliographic record
Abstract
The objective of this study is to measure the influence of L1 verb argument structure, as well as verb meaning, on the mastery of dative clitics in French as a second language for a group of Anglophone learners. More specifically, we focus on ditransitive structures. While French and English share the V NP PP structure, English also has a double-object structure, V NP NP, for a subset of verbs. The results of our study show that L1 argument structure influences the mastery of dative clitics in French, especially for verbs that only accept the double-object structure in English. Further, the behaviour of our participants with verbs that accept the dative alternation led us to conduct a follow-up study. The findings show that verb meaning also influences performance with dative clitics, but this effect cannot be explained by L1 influence.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".