Real‐time changes in the paradigm of personal pronouns in Montreal French
Bibliographic record
Abstract
Based on the results of three variationist studies on personal pronouns used in Montreal French, this article shows how real‐time data can shed light on ‘apparent time interpretation’ and increase our understanding of morphosyntactic changes. Longitudinal data for a 24‐year period from three corpora of spoken French are used to discuss cases of variation: variation between the clitics on and nous , alternation between on and tu/vous, and variation among non‐clitic plural pronouns. While the first case illustrates a change occurring over a long period of time, the other variables show changes observable in the 24‐year time span under study. In particular, analysis of the variation among non‐clitic pronouns suggests a socio‐stylistic specialization of the variants at a certain stage in the grammaticalization of compound forms. In sum, this article uses longitudinal evidence to show how the variables are involved in a process of restructuring the paradigm of the French pronouns.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".