Les locutions verbales et les constructions à verbe support en français L2
Bibliographic record
Abstract
L’objectif de ce travail de recherche est d’étudier la distinction formelle entre les locutions verbales et les constructions à verbe support telles qu’elles sont présentées et décrites par les chercheurs travaillant dans le cadre théorique du lexique-grammaire. Dans ce but, nous avons conçu quatre tâches que nous avons proposées à nos deux groupes de participants : des locuteurs natifs du français et des apprenants du FL2. Nous avons testé plusieurs aspects de la maîtrise des constructions verbales complexes en français par nos participants en mettant en lumière les différences dans les tâches de perception ainsi que dans les tâches de production des structures ciblées. Cette étude démontre que, bien que la perception des structures verbales complexes par les apprenants du FL2 soit assez semblable à celle des locuteurs natifs de cette langue, leur production représente un aspect assez difficile pour les premiers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".