Bibliographic record
Abstract
Courtesy of her father and husbands, the subject of this article was known by a succession of titles during her lifetime. Born in 1443, she was the only child of John Beaufort, duke of Somerset, making her Lady Margaret Beaufort. The duke died in 1444, leaving her as an extremely valuable commodity in the aristocratic marriage market. In 1450 she was hastily contracted to another child, John de la Pole, a “de futuro” arrangement that was easily annulled three years later. At nine she was married to Henry VI’s half-brother Edmund Tudor, earl of Richmond, and at thirteen she was widowed before giving birth to her only child, Henry, who was therefore earl of Richmond from birth. In 1458 she was married again, to Sir Henry Stafford. Though her birth and kinship made Margaret a natural Lancastrian, Stafford fought on the Yorkist side at the battle of Barnet in 1471 and died of his wounds. Margaret’s final marriage (1472) was to the northern magnate Thomas Stanley, Baron Stanley and king of Mann. In 1483 she schemed for the overthrow of the Yorkist Richard III and in 1485 her son Henry returned from exile in Brittany and France, defeated Richard in battle, and became King Henry VII, the implication being that Margaret had renounced her own claim to the throne in order to secure his. The new king’s stepfather became earl of Derby, making Margaret a countess twice over, though the status she assumed was that of queen dowager. For convenience, she was known as “the king’s mother.” She died in 1509, having survived her son by ten weeks. This bibliography surveys Reference Works, Overviews, Primary Sources, Journals, and Collections of Papers, before Margaret Beaufort’s life and times are explored in the next two sections. Dynasties and Dynasticism approaches her by means of the families into which she was born or married. Biographies and Studies are of Margaret herself. Personal piety was the thread that tied together her dealings with her social inferiors, whom she clothed and fed, instructed in the faith by means of the printed word, and for whose benefit she endowed preachers and lecturers to teach the Christian message, together with colleges for the training of future priests. Those various activities are dealt with in the sections devoted to Domestic and Regional Patronage, Books, and Universities, though it is true that her small wimpled figure has tended to loom larger in the published histories of Cambridge than in those of Oxford.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 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) | 0.199 | 0.068 |
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".