Simón Bolívar and friends: Recent biographies of independence figures in Colombia and Venezuela
Bibliographic record
Abstract
Abstract The biographical genre is closely linked to the process of state building throughout Latin America and the Atlantic world. In the 19th century, statesmen and scholars produced hagiographies of their heroes' lives and viciously attacked their enemies' reputations. In a survey of recent academic biographies of independence figures in Colombia and Venezuela, several themes quickly become apparent. First, general biography remains extremely popular with both readers and writers for a broader public (including for children), but rigorous, well‐documented, scholarly studies are much fewer in number. Second, the genre remains dominated by studies of the lives of Euro‐descended creole men, most of whom were military or political actors, overwhelmingly aligned with patriot side, and resident in urban areas. Third—and directly related to the previous trend—is that most of the biographies are predicated on the concept of glory and glorious achievements. Fourth, biography remains a stubbornly national genre; in research sources and content, there appears to be little cross‐fertilization and content across countries, continents, or languages. And finally, Simón Bolívar remains a towering figure, not only because of the sheer number of biographies devoted to him specifically but also because he casts his long shadow over the life stories of virtually everyone else.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".