Representaciones de la división azul en la narrativa española actual (2005-2016)
Bibliographic record
Abstract
La División Azul fue la representación de España en el frente del Este durante la II Guerra Mundial. El tema fue utilizado en varias novelas y libros autobiográficos durante la dictadura franquista. En este corpus, no muy extenso y del que forman parte autores como Tomás Salvador, Luis Romero o Dionisio Ridruejo, los voluntarios dejaron por escrito su experiencia en la Unión Soviética. En la actualidad, este periodo histórico ha sido retomado por varios novelistas reconocidos, entre los que se encuentran Almudena Grandes, Lorenzo Silva, Juan Manuel de Prada o Carla Montero, para la composición de sus narraciones. El objetivo del siguiente artículo es introducir las cinco características —la memoria en la novela negra, la novela histórica, el acto afiliativo, la hipertextualidad y la aparición de temas ocultos— que nosotros identificamos en este tipo de textos. https://doi.org/10.17398/2660-7301.42.133
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".