Sobre les Regles d'esquivar vocables i «la qüestió de la llengua»
Bibliographic record
Abstract
Si siempre es laborioso y delicado reseñar una obra de un maestro, lo es más aún en un caso como éste, en que a lo intrincado de la historia secular y crítica de la obra de que trata el Dr. Badia podría añadirse la que ha despertado ya este mismo estudio suyo en tan corto espacio de tiempo. Nos anima, sin embargo, el hecho de darlo a conocer en el ámbito de la Filología Española, especialmente cuando esta voluntad de difusión se hace manifiesta en su autor desde el comienzo. Poner en relación este objeto de estudio con los estudios hispánicos es coherente con la línea del Dr. Badia como hispanista, aunque el interés del trabajo al que nos referimos alcanza al mundo de la romanística, concepto al que apelaba él mismo recientemente —en otra publicación del Institut d'Estudis Catalans— al dar nueva vida a la revista Estudis Romanics…
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".