Bibliographic record
Abstract
Anglo-Jewish Women and Modern Scholarship Medieval Anglo-Jewish women were a constant presence in law courts. There are whole generations of women who survive in the records of the extraordinary bureaucracy of thirteenth-century England, most notably in the seventy-two extant rolls of the Exchequer of the Jews for the dates 1219–1290, but also in marriage contracts, close rolls, letters, tallages, and shetarot (i.e., starrs, bonds of debt or acquittance written in Hebrew and according to Jewish custom), among other miscellaneous documents. Michael Adler in 1934 proclaimed the Anglo-Jewess, for the vital role she played in the English economy and courts, “unequalled in those days in any country.” Barrie Dobson maintained that the Anglo-Jewish woman was “a more influential and even formidable figure than her Christian counterpart.” Victoria Hoyle's work on moneylending between Anglo-Jewish and Christian women documents “641 references to 310 distinct and individual Jewish women…in the published plea rolls” of the Jewish Exchequer, not counting cases of ambiguity. Hannah Meyer, in her impressive 2009 Cambridge dissertation, concluded that “using gender as a primary tool of analysis” for the available records means “the inescapable visibility of Jewish [female] uniqueness.” In the thirteenth century, several major Anglo-Jewish financiers were women. Licoricia of Winchester, about whom Suzanne Bartlet wrote a posthumously published book, is only the wealthiest and most famous among them. Others include Henna of York, Mirabelle of Gloucester, Belia of Bedford, Chera of Winchester, and Abigail of London. These are women for whom we can track full careers, who travelled and appeared in court independently, owned properties, and lent mostly to men of various social and ecclesiastical stations. They and lesser figures appear startlingly frequently in national records, and it appears that they were literate and leading figures in Jewish– Christian business relations. In attempts to understand and reconstruct their lives, literacies, and agency, there is a glut of archival material to explore – “a gigantic lucky dip,” as Dobson called it. And yet these women receive relatively little scholarly attention. They are caught between academic disciplines and between deep scholarly histories that say there is little Jewish material to study from medieval England or that Jewish women are simply not much depicted in the medieval sources of the dominant Christian culture.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".