Bibliographic record
Abstract
Pigs were ‘creatures of the threshold’ and objects of both ‘fear and fascination’ for much of the eighteenth century. They were hybrid, at once fully animal but also disturbingly human. On the one hand, they were valued members of the household economy and cherished for their company; on the other, they were considered hideous creatures associated with untamed desires, ‘unclean souls’, base morals and sin (Stallybrass and White, 1986, p. 47; Mizelle, 2011, p. 36). Pigs’ ambiguous human-animal nature, frequently articulated along class lines and always political, resulted in ‘typical pig imagery [that] scourges immorality and critiques departures from social norms as leading to potential disorder and social instability’ (Fisher, 2000, p. 304). Samuel Johnson, for example, considered them creatures ‘remarkable for stupidity and nastiness’, Alexander Pope equated them with the ‘dirty’ and mindless mob, and Edmund Burke famously used their imagery to drive home his views of the labouring classes as the ‘swinish multitude’ (qtd. in Fisher, p. 303–5). Pigs and the people associated with them were often cause for concern, and this widespread association of the animals with social upheaval, intellectual deficiency and lax morals are the focus of this chapter. Looking specifically to the exceptional career of one pig in particular, the famous Learned Pig, this chapter examines the influence and role of live animals in understandings of animality and the performance of national identity alongside embodiments of ‘human’ and ‘animal’ at the end of the eighteenth century. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.005 |
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".