Healers and midwives accused of witchcraft (1563–1736) - What secondary analysis of the Scottish survey of witchcraft can contribute to the teaching of nursing and midwifery history
Bibliographic record
Abstract
BACKGROUND: Nearly 4000 people were accused of witchcraft in Scotland between 1563 and 1736. Some of these were healers, midwives, and nurses. OBJECTIVE: To investigate Scotland's folk-healers and midwives accused of witchcraft and review their work from a nursing and midwifery perspective. DESIGN: Secondary analysis of the Survey of Scottish Witchcraft. METHODS: Those on the Survey with witchcraft accusations relating to folk-healing or midwifery were identified and their biographies were created from Survey data (2021). Individual biographical data were descriptively analysed. Healing/midwifery practice information was tabulated and thematically analysed. RESULTS: 142 individuals were identified (85 % women), 51 % were found guilty, 90 % were executed. Most (98 %) were folk-healers with 10 accused for midwifery reasons. Mainly their work was accused of causing harm. Three themes emerged: their use of rituals; unorthodox religious practices and treatments. Rituals included actions carried out a certain number of times. Religious practices frequently referenced Catholicism. Many of their treatments for ingestion, application or bathing used items still recognised for their health properties. Approximately, 10 % of the 142, mainly in the 1500s/early 1600s, utilised expensive items and complex treatments which had more in common with 'elite' knowledge rather than simple folklore. CONCLUSIONS: Across all 142 people, many aspects of their work are identifiable within more contemporary nursing and midwifery practice including their use of rituals, treatments, and holism. Mostly the accused were folk-practitioners, but a few (1500s/early 1600s) appear to have been healers working akin to physicians. Following the Protestant reformation (1560) their work, unlike that of physicians, was marginalised, considered unorthodox and harmful because they were women and/or their work reflected Catholicism. European hospital nursing originates in the monastic houses, but little is known about these early religious nurses. This study is novel in suggesting that whoever taught these accused witch/healers may have been connected to the monastic hospitals pre-Reformation.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".