Perfect Wives, Other Women: Adultery and Inquisition in Early Modern Spain
Bibliographic record
Abstract
In Perfect Wives, Other Women Georgina Dopico Black examines the role played by women’s bodies—specifically the bodies of wives—in Spain and Spanish America during the Inquisition. In her quest to show how both the body and soul of the married woman became the site of anxious inquiry, Dopico Black mines a variety of Golden Age texts for instances in which the era’s persistent preoccupation with racial, religious, and cultural otherness was reflected in the depiction of women. Subject to the scrutiny of a remarkable array of gazes—inquisitors, theologians, religious reformers, confessors, poets, playwrights, and, not least among them, husbands—the bodies of perfect and imperfect wives elicited diverse readings. Dopico Black reveals how imperialism, the Inquisition, inflation, and economic decline each contributed to a correspondence between the meanings of these human bodies and “other” bodies, such as those of the Jew, the Moor, the Lutheran, the degenerate, and whoever else departed from a recognized norm. The body of the wife, in other words, became associated with categories separate from anatomy, reflecting the particular hermeneutics employed during the Inquisition regarding the surveillance of otherness. Dopico Black’s compelling argument will engage students of Spanish and Spanish American history and literature, gender studies, women’s studies, social psychology and cultural 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 | 0.002 | 0.002 |
| 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 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".