Bibliographic record
Abstract
This chapter addresses the evolution of the crime fiction genre in Latin America by examining the relationship between three of the continent’s major cities and three historical moments. The following case studies chosen are: Buenos Aires in the stories of Seis problemas para Don Isidro Parodi (Six Problems for Don Isidro Parodi , 1942) by Jorge Luis Borges and Adolfo Bioy Casares; Havana in Armando Cristóbal Pérez’s novel La ronda de los rubies (The Ring of Rubies , 1973); and Mexico City in Días de combate ( Days of Combat , 1976) by Paco Ignacio Taibo II. The chapter traces a textual trajectory from Borges and Bioy’s parodic games with the English models of mystery fiction to Taibo’s scathing national questioning of the Mexican neo-crime fiction, passing through Cristóbal’s politically committed and Cuban revolutionary crime fiction. That trajectory demonstrates the flexibility of the crime fiction genre, which has allowed it to branch out and adapt to the literary needs of different authors and contexts in the period between 1930 and 1980 in Latin American literature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".