The Unfinished Business of Anna Kingsford: Science, Enchantment, and Experiments on Animals
Bibliographic record
Abstract
The project takes seriously Dr Anna Kingsford’s (1846-1888) claim that vivisection is a type of sorcery and science, a type of occult or spiritual undertaking believing that the assertion, which gained currency during the 19th–century antivivisection movement and is now overlooked, is yet unfinished and therefore a potentially powerful figuration for current antivivisectionists. To that end, the dissertation provides a critical and intersectional reading of the 19th-century British and European antivivisection movement, the fin de siècle occult revival, and Kingsford’s role in each, often working to bring these worlds together. This historical analysis includes an examination of Victorian attitudes to the period’s changing understanding of gender, species, race, and science. Building on this historical foundation, the dissertation will provide a theoretical discussion of Kingsford’s contemporary resonances with emerging disciplines in the environmental and posthumanities, including critical animal studies, material feminism, feminist posthumanism, and science and technology studies. Many theorists in these fields are interested in reappraising the roles of affect, enchantment, mysticism, and wonder in ethical thinking and human-animal-environmental relations. This project builds on these historical and theoretical insights by providing an “enchanted” analysis of the contemporary laboratory space, experiments on animals, and a reading of three case studies of ongoing animal experimentation paradigms (i.e., maternal deprivation, learned helplessness, and the organizational-activational hypothesis of homosexuality) which I argue lend themselves to a Kingsford-inspired analysis. Furthermore, this project articulates a novel “enchanted animal ethic” involving a feminist and neo-Spinozist articulation of human-animal and environmental ethics that makes space for mystical, non-secular modes of meaning-making, care-centered multispecies community building, and social and political movements. Finally, the project and an enchanted understanding of animal ethics will be useful to interdisciplinary scholars and advocates seeking a paradigm change in the sciences away from experiments on animals and towards a more humane and efficacious science as well as more egalitarian and meaningful relationships with animals and the more-than-human world.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| 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".