Entre la norma en ús i les propostes normatives: recerca, vehiculació, implantació
Bibliographic record
Abstract
En tractar de la implantacio social de les normes linguistiques, hem de tenir present que forma part d?una finalitat mes important: aconseguir la qualitat de la llengua en els usos publics. Per tant, es el resultat d?un conjunt de factors i agents socials. Els estudis de J. Maurais sobre la norma linguistica i la qualitat linguistica en el context de Quebec son un bon referent. Les normes linguistiques son primordialment socials i s?inscriuen en la variacio linguistica. Ac- tualment, la intervencio normativa ha de partir d?aquesta naturalesa social i variable de les normes. L?estandarditzacio, com a establiment o implantacio de les normes, es un proces cooperatiu, en que els resultats depenen de la coordinacio sistematica entre l?autoritat normativa i els grans agents de la vehiculacio.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.032 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".