How to Know the Witch: Trivial Domestication, Tragicomedy, and Race in <i>The Witch of Edmonton</i>
Bibliographic record
Abstract
What does it mean to “know” a witch in early modern culture, and how do questionable knowledge-processes become tested and verified in comedies? Dekker, Ford, and Rowley’s 1621 tragicomedy, The Witch of Edmonton, addresses these questions of epistemology through its formal experiments. This essay demonstrates how The Witch of Edmonton reflects conflicting legal and epistemological processes of witch-discovery in the early modern period, but ultimately deploys its own tragicomic poetics to stage a theatrical and racializing method of discerning a virtually unknowable truth. The digressive comic subplot of Cuddy Banks embedded within The Witch of Edmonton’s tragic trajectory works together with the playwrights’ formal manipulations of racialized domestic discourses of breastmilk to advance what I call a strategy of “trivial domestication” to racially brand the witch’s body of Elizabeth Sawyer as both laughably trivial and incurably ignorant. The play thus works to produce an idea of knowledge as a theatrical ability to correctly discern trivial figures of immutable ignorance—even as its tragicomic poetics paradoxically underscore its very artificiality. [Y.K.]
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.017 | 0.068 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".