Medieval Widowhood and Textual Guidance: The Corpus Revisions of <i>Ancrene Wisse</i> and the de Braose Anchoresses
Bibliographic record
Abstract
In 1990, Margaret Wade Labarge published a seminal article on medieval widowhood and religious devotion, arguing that “among the upper classes widowhood could provide for the first time in a woman’s life a freedom of action and choice that she had not previously enjoyed.”1 She pointed out that not all medieval widows were elderly, and indeed, one of the widows whose life she explored, Loretta, countess of Leicester, was widowed in her early twenties. Such women might wish to avoid remarriage for a variety of reasons, yet their lives were far from over even if they were widowed in their thirties or forties: Loretta lived well into her eighties. Labarge outlined a number of “second careers” that widows might undertake in the secular world, though her article focused on women who “turned to an active religious life and, in reality, took up a new career.”2 She argued that “Because of their superior social position these women had the luxury of a choice among several patterns of religious life, as recluse, or nun, or mystic living a devout life in the world.”3 Labarge concentrated on the influence that widows in the religious life could exercise, presenting one example of each of these three patterns: Loretta, countess of Leicester, who became a recluse by 1221; Ela, countess of Salisbury, who founded Lacock Abbey in 1232 and entered it as a nun, serving as abbess for nearly twenty years; and St. Birgitta, wife and daughter of Swedish nobles, who influenced popes and kings through her mystical Revelations.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".