La huella de Galdós en la novela social española contemporánea
Bibliographic record
Abstract
Resumen: En este trabajo pretendemos exponer cómo el compromiso formulado por Galdós de retratar la sociedad que le rodea, mostrar sus defectos e intentar encontrar fórmulas para mejorarla, caló hondo en algunos novelistas sociales españoles contemporáneos como Juan Marsé, Rafael Chirbes, Almudena Grandes, o Antonio Muñoz Molina, entre otros. Para ello, en primer lugar, presentaremos cuáles eran los principios filosófico-sociales de Benito Pérez Galdós, seguidamente veremos cuál era la importancia que tenían la sociedad y la historia en su literatura, y por último analizaremos la huella galdosiana en los novelistas sociales de nuestro tiempo. Palabras clave: Benito Pérez Galdós, sociedad, principios filosóficos, huella, novelistas sociales. The footprint of Galdós In the Contemporary Spanish Social Novel Abstract: In this work, we intend to outline how Galdós' commitment to portray the society around him, to show its defects and to try to find ways to improve it, found its way into some contemporary Spanish social novelists such as Juan Marsé, Rafael Chirbes, Almudena Grandes and Antonio Muñoz Molina, among others. To this end, we will first present the philosophical and social principles of Benito Pérez Galdós, then we will see what importance society and history had in his literature, and finally we will analyse the Galdosian imprint on the social novelists of our time. Key words: Benito Pérez Galdós, society, philosophical principles, imprint, social novelists
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".