Ecocinismos. El medio ambiente natural y humano bajo la linterna cínica
Bibliographic record
Abstract
En la culminación de un largo ciclo dedico este libro a mis padres, Próculo y Elvira, y a mis hermanos, Carlos y Ana María, por su impagable ánimo y apoyo.Quiero agradecer especialmente a dos personas su colaboración en el desarrollo de esta obra.La primera de ellas es mi director de tesis, Luciano Espinosa, quien a la par que dejaba desarrollar libremente mis ideas, ha sabido aconsejarme y corregirme minuciosamente en las diferentes revisiones del texto.El resultado final no hubiese sido posible sin esta sabia mezcla de libertad y rigor que él conjuga en sí mismo, y que constituye para mí un ejemplo personal que difícilmente olvidaré.La segunda es Marta, quien ha compartido conmigo en estos tres últimos años la más natural y humana de las relaciones y ha sabido soportar las pesadas disquisiciones de este aspirante a filósofo.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".