L’effet de la (ir)régularité verbale sur le choix de variante du futur en français L2
Bibliographic record
Abstract
The current study considers the use of various grammatical structures expressing the future tense by 10 intermediate French learners. We examine the effect of the verbal paradigm – regular versus irregular – on the learners’ preferred structure in order to determine if they prefer the periphrastic construction, particularly when it comes to irregular verbs. We predicted that the learners’ use of the simple future depended on their ability to correctly conjugate verbs in simple future, meaning that learners who had more difficulties with this variant would use it less often. However, results show that learners used the simple future equally, and as often, with both regular and irregular verbs and that they preferred the periphrastic construction with both verb types. In fact, even those learners with the highest scores on a verb conjugation test targeting the simple future preferred the periphrastic future. We argue that this preference for the periphrastic future is either due to the influence of the learners’ L1 or to the fact that the periphrastic future is an analytic construction, making it cognitively simpler.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".