"Each...according...to his intention": Three Phases of Christine de Pizan's Literary Influence Through the Ages
Bibliographic record
Abstract
Many scholars participating in the current boom in Christine de Pizan studies tend to think of the "discovery of Christine" as a phenomenon limited to the past thirty—or even ten—years. In truth, however, Christine has been alive in the Western literary imagination—if not flamboyantly so—since the fifteenth century. Alongside her predictable presence among resurgent feminists, her courageously political-moral persona, whether in verse or in prose, has found welcome within the least likely writings, "embroidered" or "mortared" into the totality of the particular author's message, as one of the author's "strands" or "bricks," chascune at elle doit servir, selon la fin de l'intention oú it tent "each one where it should best serve, according to the needs of his intention," to use Christine's own metaphors for (especially didactic) literary composition.' The reasons for Christine's enduring attraction are twofold: her heroic conversion from helpless victim to active participant in the major events of her era, and her talent for literary self-fashioning while evoking this real-life transformation. Both traits would be replicated among even the most improbable of her modern borrowers.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.035 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".