Conditional morphology in <i>si</i>-clauses: A Canadian-French reanalysis
Bibliographic record
Abstract
This article reports on a synchronic analysis in the surface variation between the conditional and the imperfect or pluperfect indicative in hypothetical clauses headed by the subordinator si. The empirical basis of the study is a corpus of French spoken in the national capital region of Canada, which comprises 120 informants. The study also has a diachronic component concerning the evolution of the variable based on a collection of published works since Early Modern French. The most interesting aspect of the results is the system wherein the morphological exponent of the verb is determined by the modal reading of the utterance. It is revealed that this grammatical trait was attested at earlier steps in the development of the language and that it helps to resolve a form-function asymmetry resulting from use of the indicative imperfect in a conditional context. Cet article présente les résultats d'une analyse synchronique en lien avec la variation de surface entre les formes du conditionnel et celles de l'indicatif imparfait ou du plus-que-parfait dans les propositions hypothétiques ayant en tête la conjonction si. L'assise empirique de cette étude repose sur une base de données en français parlé dans la capitale nationale du Canada et comprenant 120 locuteurs. L'étude comprend aussi un volet diachronique sur l'évolution de la variable qui comprend le dépouillement d'un grand nombre d'ouvrages publiés depuis les débuts du français moderne. L'aspect le plus intéressant de l'analyse révèle un système où l'expression morphologique verbale est assignée en fonction de la modalité de l'énoncé. En outre, cette particularité de la grammaire est attestée à une étape antérieure de la langue et elle a l'avantage de résoudre l'asymétrie entre les formes et la fonction, engendrée par l'emploi de l'indicatif imparfait en contexte conditionnel.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".