Bibliographic record
Abstract
In Florence, a city where there was no princely court to provide titles of authority to women and at a time when women were frequently kept from the public sphere of men, Lucrezia Tornabuoni (b. 1425–d. 1482) exercised an impressive influence over the politics and culture around her. Her parents were members of two of the oldest and most powerful Florentine families, the Tornabuoni and Guicciardini, and with her marriage to the eldest son of Cosimo de’ Medici, she was destined to become the prima donna of the city. Her family network would, in fact, serve as her source of influence: she was sister to the banker Giovanni Tornabuoni, wife of Piero de’ Medici, the de facto head of the Republic, mother of Lorenzo “the Magnificent,” and grandmother of future popes Leo X and Clement VII. Lucrezia would act as close advisor to her brother, husband, and children as well as overseeing the education of many of her grandchildren. Her influence extended beyond expected roles of domestic management, and in Tornabuoni’s case specifically, her activities would include that of landowner, business woman, patron, political emissary, and poet. She collected rents on properties owned in Pisa, remodeled and managed thermal baths at Bagno a Morbo, traveled to Rome to interview her son’s prospective bride, managed a dowry charity for poor girls, and ran the daily affairs of the Medici household while her husband was often ill. These experiences, all of which demonstrate remarkable intelligence and character, inform her poetic works. Her writings are almost exclusively religious in nature. She versified books of both the Old and New Testaments as well as composed several lauds that were set to music. In her more narrative works, she frequently tackles the difficult question of how to be a Christian woman in a world of commerce and war, not surprising for a woman who succeeded in performing piety as well as demonstrating sharp business acumen. Furthermore, she was beloved by her people, even in a time when Medici relations were often tense. When Lucrezia Tornabuoni died, her eulogist praised her for advising magistrates as well as the humble. He also praised that her political decisions had been more “prudent” than those of her son, the ruler of Florence, Lorenzo de’ Medici, and perhaps it is the words of her son Lorenzo that are most telling: after his mother’s death, he wrote the duchess of Ferrara to say that he had lost not just a mother but his only refuge and relief.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".