Wagschal, Steven. Minding Animals in the Old and New Worlds. A Cognitive Historical Analysis. Toronto: University of Toronto Press, 2018. x + 343 pp.
Bibliographic record
Abstract
Los ltimos aos han sido testigos de una veloz proliferacin de trabajos en torno a lo que se ha venido a llamar animal studies, ofreciendo al lector interesado toda una constelacin de aproximaciones provenientes de la historia econmica, de la sociologa y la antropologa y, cmo no, de la literatura y el arte de la Pennsula Ibrica.Gran parte de este impulso ha tenido su origen en el mbito universitario norteamericano, desde donde un selecto grupo de hispanistas ha ido ofreciendo nuevas lecturas de textos en muchos casos ampliamente conocidos, pero que por diferentes razones haban dejado sin responder determinadas preguntas que ahora se pueden abordar con un ms completo arsenal metodolgico.Como resultado, empezamos ya a disfrutar de una excelente oferta de estudios centrados en literaturas y periodos diversos, con especial nfasis en el momento de expansin imperial desde la transicin del Medioevo a la temprana modernidad.El presente libro, firmado por Steven Wagschal (
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".