Bibliographic record
Abstract
The 252 extant letters of Margherita Datini (b. 1360–d. 1423) to her husband, the merchant Francesco di Marco Datini (b. c. 1335–d. 1410), represent the largest collection of early Italian vernacular correspondence by a lay woman to have come to light. They are all the more unusual because Francesco’s letters to Margherita also survive, enabling us to follow a marital conversation that continued for almost three decades. The couple’s exchanges reveal a very different portrait of marriage than was envisaged by prescriptive texts of the period. Or rather, the letters provide evidence that Margherita and Francesco had a conventional enough view of how their relationship should be conducted, but the challenges of everyday life in an urban environment riven by factionalism and competitiveness forced them often to ignore the gender stereotypes of their day. Fourteenth-century advice manuals, such as Paola da Certaldo’s Libro di buoni costumi, described female virtue in narrow terms and demarcated the roles of husband and wife strictly, recommending that women be confined to the household and restrained from participating in men’s affairs. Margherita, however, collaborated in the supervision of Francesco’s building projects, even occasionally pursued the merchant’s debtors, and offered her husband shrewd advice, revealing the extent to which she was fully conversant with contemporary politics. She was cognizant of the need to participate in the social networking that was a fundamental feature of Florentine society and cultivated the magnate connections of her own aristocratic family to secure useful allies for the more humbly-born Francesco. Margherita’s inability to bear children was a source of bitter disappointment to the couple, but it indubitably facilitated her ability to take on a greater role in her husband’s affairs than was usual. The Datini couple’s letters also reveal many details about their households in Florence and Prato. The routines and experiences of the servants, neighbors, friends, and relatives with whom Margherita associated are documented in colloquial and evocative prose, providing a rare view of women’s social interactions and emotions in a period blighted by recurring outbreaks of plague, an unstable political climate, and difficult economic conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.209 | 0.127 |
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".