Daughters of Alchemy: Women and Scientific Culture in Early Modern Italy
Bibliographic record
Abstract
comptes rendus 221 of town and country, Raber eschews the exploitation of animals in the service of purportedly higher human concerns, such as literary explication.Not surprisingly, Edward Topsell looms large in Raber's study, and she relies heavily on his History of Four-footed Beasts (1607) to speak for the general English experience of, say, burrowing moles and barking dogs.But this is preferable to the over-reliance on Ovid that features in so many studies of animals and Renaissance culture; indeed the Metamorphoses are mentioned only once in Raber's study, a conspicuous marginalization of a literary source that exemplifies her methodological critique of materialist criticism that is not sufficiently material.Raber is generous in acknowledging the work of her predecessors and colleagues in the field; and minor disagreements on points of interpretation are discretely stowed in the endnotes.The book is thoroughly researched, meticulously edited, and handsomely illustrated with more than two-dozen figures.And Raber's conclusion is genuinely moving, as it surveys the mourning practices of elephants to demonstrate how animals command language, display complex social organization, and exhibit collective memory-further undermining the grounds on which Cartesian dualism and human exceptionalism are built.In myriad ways, she concludes, animals share "those attributes of the mind-reason, emotion, moral judgment-that define the category 'human' " (185), and her fascinating study consolidates the place of our shared embodiment in early modern studies.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".