Renaissance Humanist Reinterpretations of Eve; The Writings of Christine De Pizan and Isotta Nogarolla
Bibliographic record
Abstract
The purpose of my research is to explore the ways that intellectuals reinterpreted Eve using the Humanistic method during the Renaissance, questioning the naturalized relationship between women and sin. Humanism, a growing movement during the 15th century, placed emphasis on ascertaining meaning through analyzing works for their intended meaning and considering the context, while also revering God and antiquity alongside attention to the individual. Christine De Pizan and Isotta Nogarola use the Humanistic method of analysis in different ways to argue that Eve, and womankind, do not deserve a devious reputation and it is not justified by God. I will use historical artworks and writings to show how Eve was depicted prior to and during Renaissance Humanism. For example, Michelangelo’s Sistine Chapel depiction of the Fall fundamentally differs from other previous works by redistributing the culpability of Adam and Eve; no longer is Eve a sensual being, nor entirely to blame for the Fall. Additionally, as is necessary with any historical analysis, I will examine the contextual factors that allowed for the reinterpretation of Eve, especially by women, including the ways that both were a product and yet also ahead of their time. Whether the reinterpretations are pro-feminine or not is irrelevant in many respects, for the significance stems from women taking back a piece of historiography of the prototype woman, Eve.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.048 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".