Bibliographic record
Abstract
Eduardo Galeano, autor uruguayo de Memoria del fuego, (1982, 1984, 1986), historia revisionaria de Americas en tres vol?menes, ha desarrollado un acercamiento a la historiograf?a que desestabiliza la narrativa tradicional del pasado, de la historia oficial, a trav?s del uso de archivos alternativos, narraciones sincr?nicas y no lineales, materiales encontrados, relatos alegorizados y condensados de acontecimientos familiares, mitos ind?genas y una mir?ada de otras estrategias y t?cnicas. Al mismo tiempo, Galeano aboga por la responsabilidad ?tica inherente en el presente hist?rico como fundamento para un futuro condicional, futuro capaz de transformarse a medida que se va haciendo. La historia desobediente, disonante, disidente, viene a ser el medio de movilizar alternativas contra las rutinas de la obediencia que gobiernan el sistema de silencio y miedo. La historia, como la practica Galeano, recupera voces silenciadas y marginalizadas para convertirlas en testigos de la memoria en contra de la amnesia.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".