¿Realmentes existen?: la “pluralización” de los adverbios en -mente en español actual
Bibliographic record
Abstract
En este trabajo se presenta un fenómeno no normativo casi desconocido en español, la “pluralización” de los adverbios en -mente (lugares realmentes sorprendentes), que no se encuentra recogido en las principales gramáticas de esta lengua. A partir de los datos del Corpus del español, damos a conocer este fenómeno, mostramos en qué países se documenta y con qué frecuencia. Posteriormente, analizamos qué adverbios en -mente muestran esta -s final en español actual y en qué contextos sintácticos se dan. En concreto, mostramos que en este fenómeno se encuentran implicados fundamentalmente adverbios de grado, adverbios relacionados con la modalidad y adverbios focalizadores, sobre todo cuando aparecen como modificadores de adjetivos y como modificadores oracionales. Finalmente, proponemos una explicación para la presencia de esta -s final a partir de dos procesos distintos, pero complementarios, que afectan a la categoría gramatical del adverbio en español: la concordancia adverbial, descrita hasta el momento para los adverbios cuantificadores que modifican a un adjetivo, y la “falsa” pluralización del adverbio.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".