La traducción de Los Diálogos de Amor de León Hebreo: Notas para el entendimiento humano del Inca Garcilaso de la Vega
Bibliographic record
Abstract
En las páginas que siguen se buscará trascender las nociones que relegan la traducción de Los Diálogos de Amor de León Hebreo por el Inca Garcilaso de la Vega a un mero ejercicio de carácter utilitarista. Me cuestionáné el porqué de la elección de este texto por parte del Inca y analizaré aspectos idiosincráticos y conceptuales de la obra, con el objetivo de arrojar luz sobre la compleja identidad del Inca Garcilaso de la Vega. This paper aims at interpreting the translation of Los Diálogos de Amor (León Hebreo) by the Inca Garcilaso de la Vega beyond a mere exercise of pure utilitarianism. His election of this work to be translated and the analysis of the idiosyncrasies of the text aim at shedding some light on the identity complexities of el Inca Garcilaso de la Vega.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".