Bibliographic record
Abstract
En su novela Tantas veces Pedro, el autor peruano Alfredo Bryce Echenique utiliza las herramientas de la metaficción para hacer una parodia del género hagiográfico y de la Biblia, así burlándose de la religión católica. Para probar esta tesis, este trabajo combina las teorías de metaficción y parodia establecidas por la teórica Linda Hutcheon con el concepto de una hagiografía o “vida de santo”. Además de esta combinación, se explora la historia de la literatura peruana, en particular su larga tradición hagiográfica. Al juntar estas ideas, se puede ver cómo la obra de Bryce Echenique es una parodia humorística de escritura religiosa y, así, una crítica de la misma religión. In his novel Tantas veces Pedro, the Peruvian author Alfredo Bryce Echenique employs the tools of metafiction in order to parody the hagiographic genre and the Bible, thus mocking the Catholic religion. In order to prove this hypothesis, this work combines the theories of metafiction and parody established by theorist Linda Hutcheon with the concept of hagiography or “life of a saint”. Along with this combination, this work explores the history of Peruvian literature, paying particular attention to its long hagiographical tradition. By joining all these ideas, one can see how this work of Bryce Echenique’s is a humorous parody of religious writing and, thus, a mockery of the religion itself.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".