Quantification et microvariation : les adjectifs de dimension spatiale
Bibliographic record
Abstract
Résumé Cette étude en microvariation porte sur des constructions nominales quantifiées (Elle a pas long de jupe) impliquant des adjectifs de dimension spatiale en français québécois et examine comment elles se distinguent de celles avec le quantificateurbeaucoup. Après une brève description des faits, je propose une structure sous-jacente pour ces constructions et une analyse des propriétés reférentielles des N que ces adjectifs quantifient : N de masse, N collectifs, N d’Espèces au singulier et quelquefois au pluriel avec certains adjectifs quantificateurs seulement, mais jamais des Individualités. Sont aussi abordées les restrictions sur la modification et les restrictions aspectuelles qu’elles manifestent. J’en viens à la conclusion que la microvariation observée est minime. Elle est le résultat d’une interaction entre les propriétés lexicales de ces adjectifs de dimension et les principes de la Grammaire universelle.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".