Bibliographic record
Abstract
The decade of the 1960s provoked a specific interest in Latin America and its literature, largely owing to the impact of the Cuban Revolution and the attention it paid to the struggle in the cultural field. If until that point the continent’s great writers were perceived as isolated figures, the new context after 1959 created the conditions for them to be read as part of a group that was committed to the common duty of putting a new face on Latin American literature. In fact, the so-called Boom cannot be understood without considering the specific political context that acted as its sounding board. An intrinsic part of the atmosphere at the time, then, were heated debates that foregrounded the role of the intellectual in society, intense polemics regarding the limits of freedom of expression under socialism, and fiery conflicts about the status of literature in a revolutionary society. Paradoxically, the very same period was also seen by its protagonists as one of transition toward a new, as yet undefined, stage. If the decade of the 1960s was dominated by left-wing thought and by the idea of the continental revolution, the 1970s meant the withdrawal of the left, and a gradual rise for the right. In its own way – always and naturally tangentially – literature has narrated all those transitions.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".