Nussdorfer, Laurie. City of Men: Service and Servants in Baroque Rome
Bibliographic record
Abstract
Laurie Nussdorfer's new book begins with a broad question: What was manhood in a city of men?In Rome, where elite (mostly clerical) households were an important driver of the economy, domestic service employed many skilled and unskilled men.Nussdorfer poses three questions that help think about manhood's meaning, especially for celibate clergy and non-elite men.When man's superiority depended on dominating women, how did it appear in households without women?How did the cardinal's household become the model for elite lay households in household management texts?How did the traditional model of marriage and a family fit non-elite men in service, when so many men lived with their padrone?Hovering above is another question: How do we know about male servants, as individuals and as an aggregate, who mostly had neither wealth nor high status?Nussdorfer knits together a variety of primary sources, which answers this last question and makes the book a pleasure and profit to read.Chapter 1 offers a primer on the household management texts that serve as the study's foundation.As the College of Cardinals expanded dramatically after 1500 and more European states sent resident ambassadors to Rome, maestro di casa literature replaced waning interest in courtier literature.Paolo Cortesi's De Cardinalatu (1510) set the stage for a more detailed discussion of household staff and how to project honour, status, and respectability in a city deeply marked by ceremonial responsibilities.While not all of Rome's elite households were led by an ecclesiastical padrone, publishers argued that the advice and staffing model was equally appropriate for use in lay households.Indeed, the makeup of the most elite ecclesiastical and noble lay households was strikingly similar.Nussdorfer compares Aldobrandini, Borghese, Montalto, Orsini, and other households to support this conclusion and show that they mostly aligned with the number and type of servants that authors advocated.In chapters 2 and 3, Nussdorfer introduces complementary sets of primary sources that situate the household manuals in the real world.The Stati delle anime were annual parish surveys of all Roman households, which survive in increasing numbers from 1600.Another important type of record
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".