No matarás: los mandatos éticos del rostro en Soldados de Salamina (2001) y La sombra de Heidegger (2005)
Bibliographic record
Abstract
Este artículo propone un estudio comparativo de las novelas Soldados de Salamina (2001) de Javier Cercas y La sombra de Heidegger (2005) de José Pablo Feinmann a partir de la noción de “rostro” de la fenomenología existencial de Emmanuel Levinas. Se examina cómo las novelas indagan en el rostro del otro como un dispositivo generador de discurso que establece una relación posible entre literatura y ética filosófica. Asimismo, este trabajo explora cómo la hibridez genérica, es decir, el carácter meta-historiográfico de la narración en Cercas y el ensayo dentro de la novela en el caso de Feinmann, permite una aproximación crítica al principio privilegiado de la ética levinasiana: no matarás.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".