Bibliographic record
Abstract
Abstract The Latin American novel has often been associated with these two literary modes, at least since the Boom of the 1960s. This chapter defines and discusses both terms, highlighting parallels and distinctions, and briefly analyzes a few key novels, including narratives from the so-called post-Boom period. It also assesses the importance of the modes for Latin American fiction, discusses some of the controversies surrounding them, and examines them in the context of Latin American history and culture. Literature associated with magical realism and the marvelous real is extremely diverse, and this chapter emphasizes the important differences between individual narratives and between the position of their authors. Special attention is given to the connections between these modes and ethnographic fiction, primitivism, hybridity, cultural heterogeneity, transculturation, postcolonial theory, postmodernism, and discourses of identity. Finally, instead of relegating the modes to the dustbin of exoticism in which Latin America presents itself as a fascinating non-Western other, aided by a successful editorial strategy in an increasingly global consumer market, the chapter rethinks their significance in the light of more recent concepts such as the pluriverse and the ecology of others.
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 | 0.001 | 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 | 0.003 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".