Landscapes of the witches' sabbath: space, place, and fantasy in early modern Europe, 1500-1750
Bibliographic record
Abstract
Amidst the early modern European witch craze, fantasies of the witches’ sabbath spread across the continent, spurred by the terrors and anxieties of people across the social strata. Believed to be the gathering of diabolic witches who would worship the Devil, feast, dance, and engage in demonic orgies, the sabbath inverted early modern customs and rites to play a central role in witchcraft belief. While the belief in the sabbath may seem rooted in fantasy, those constructing the sabbath narratives needed to place their stories in a real setting to make them believable. This thesis explores the landscapes associated with the witches’ sabbath across early modern Europe, using these spaces and narratives to understand the relationship between people and landscape over time. Delving into the mentalités of common people and learned demonologists alike, this thesis explores the landscapes of the sabbath from Portugal to Poland to uncover how different cultural and geographic contexts moulded the sabbath belief to fit their local landscape. Using two specific case studies – Zug, Switzerland and the Pays de Labourd, France – and other examples from the European witch craze, this thesis argues that the sabbath narratives are indicative of local perceptions of landscape, reflecting personal and societal values, emotions, and anxieties tied to space. This thesis explores mountains, forests, cemeteries, and many more landscapes tied to the sabbath myth, analyzing each landscape using spatial historical methodologies and a boots-on-the-ground approach, walking through the world of early modern witchcraft belief. Moreover, through the examination of the legacies of the sabbath in the world of art, it investigates how the perception of landscape changed across time, and how early modern relationships with space have shifted and carried on into the modern world, long after the end of the witch craze.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".