Bibliographic record
Abstract
El Romanticismo fue un movimiento extremadamente influyente que surgió a finales del siglo 18 y que tuvo un gran impacto en varias áreas, incluida la literatura. Innumerables escritores han representado en sus obras características esenciales del Romanticismo como la representación de horror y emociones intensas, el uso de entornos naturales exóticos y salvajes, el nacionalismo, el individualismo, la mente humana, y el simbolismo, entre muchas otras. En este artículo, se muestra cómo el Romanticismo influyó, en concreto, la narrativa breve norteamericana analizando cinco obras: “Rip Van Winkle,” de Washington Irving; “The Minister’s Black Veil,” de Nathaniel Hawthorne; “Bartleby, the Scrivener,” de Herman Melville; y “The Minister’s Black Veil” y “The Tell-Tale Heart,” de Edgar Allan Poe. Los resultados que se han obtenido de este análisis han demostrado que estas cinco historias breves se pueden considerar trabajos románticos porque reflejan múltiples características del Romanticismo. De hecho, estos autores retratan las peculiaridades de los dos sub-campos más importantes del Romanticismo Americano conocidos como “Romanticismo Claro” y “Romanticismo Oscuro.” Romanticism was an extremely influential movement which flourished at the end of the 18th century and which had a huge impact on various areas, including literature. Countless writers have represented in their works key Romantic features such as the depiction of horror and intense emotions, the use of exotic and wild natural settings, nationalism, individualism, the reproduction of the human psyche, and symbolism, among many others. In this paper, it is shown how the Romantic Movement influenced, more specifically, the North American short story by analysing five works: Washington Irving’s “Rip Van Winkle,” Nathaniel Hawthorne’s “The Minister’s Black Veil,” Herman Melville’s “Bartleby, the Scrivener,” and Edgar Allan Poe’s “The Masque of the Red Death” and “The Tell-Tale Heart.” The results which have been obtained from this analysis have demonstrated that these five short stories can be considered as Romantic works because they reflect multiple characteristics of the Romantic Movement. In fact, these writers portray the peculiarities of the most important subfields of American Romanticism, which are known as “Light Romanticism” and “Dark Romanticism.”
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 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".