Bibliographic record
Abstract
Gender, Mediation, and Popular Education in Venice, 1760–1830, examines how women with enough cultural capital could turn their identity as representatives of "the public" – those on the receiving end of education – to their advantage, producing knowledge under the guise of relaying it. Author Susan Dalton demonstrates how elite women turned their reputation for ignorance into an opportunity to establish themselves as published authors at the dawn of the nineteenth century in Venice. Many literary figures saw women as a group in need of education. By deploying essentialist understandings of femininity, whereby women possessed superior moral virtue but deficient rationality, these women entered the world of print as cultural mediators, identified by contemporaries as key players in the social projects of public education and moral edification central to the European Enlightenment. Focussing on Isabella Teotochi Albrizzi and Giustina Renier Michiel, both renowned Venetian authors, Dalton introduces two well-known Italian women of letters to English-speaking scholars, re-evaluates the impact of their writing in Italy and raises questions about female authorship across Europe, broadens our conceptions of gender norms, and enriches our knowledge of a little-known period of women’s writing in Italy. This volume is an essential resource for students and scholars alike interested in women’s and gender history, early modern history and social and cultural history.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".