Catherine de Médicis (1519–1589) et le portrait : esquisse d’une collection royale au féminin
Bibliographic record
Abstract
This paper represents the first scholarly analysis of the collection of portraits amassed by Catherine de' Medici (1519–1589), Queen of France, during her reign of more than forty years. The fact that no portrait has yet been identified as having belonged to her may explain why this subject has never been broached. This paper will demonstrate that Catherine had a vision in her collecting, thus contradicting Louis Dimer’s 1926 opinion that she collected portraits without any specific program in mind. This article begins with a review of the main sources. Following Catherine’s death, more than 250 portraits in the Hôtel de la Reine in Paris were listed in the inventory drawn up in the summer of 1589. Some documents, mainly correspondence, deal with their acquisition and name French and Italian artists. This article then looks at other European Renaissance collections of portraits. Comparisons with these reveal that Catherine de' Medici's collection – consisting of portraits of family members, political figures, rulers, kings and queens – was among the most important of her time. Moreover, it will be shown that Catherine seems to have introduced to France the new concept of an exhibition space, a gallery, entirely devoted to portraits, which was to become very popular in the seventeenth century. This essay closes with a case study exploring the exchanges of portraits between France and England in 1571 and, in particular, 1580 and 1582, thus exposing the symbolic function of portraiture in the political sphere and the role of the diplomatic corps.
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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 | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".