Bibliographic record
Abstract
This article examines the relationship between Marguerite de Navarre’s biblical plays and the genre of the fifteenth- and sixteenth-century medieval mystery play by focusing on three dramatic elements: staging, characters, and language. While, with respect to staging, Marguerite recaptures the structure of the mystery play, she takes less interest in the representation of the movements of the characters and in the realistic scenes, which were central to this medieval genre; as she reduces the dramatic events and their dynamics, she concedes little to the performance, privileging hearing over seeing. Regarding the characters, Marguerite also moves away from the conventions of the mystery play, according to which characters were endowed with familiar, concrete, human traits. Except for a few conspicuous cases, the queen of Navarre shows a preference for symbolic, abstract entities, or for human characters so disembodied that their faith or holiness takes them away from the human world and closer to the heavens. As for the language of her plays, Marguerite creates a poetic rhythm that almost depletes the life and suppleness of the dialogue. Thus the vivacity of the verbal exchanges is transcended to the advantage of other styles that are less suited to the genre of theater, with the exception of the sermon and spiritual lyricism. In conclusion, Marguerite, in her four biblical plays, undermines the medieval form of the mystery play, which, however, she also recaptures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".