Contagion by Conceit: Menstruosity and the Rhetoric of Smallpox into the Age of Inoculation
Bibliographic record
Abstract
An incident towards the close of Sarah Fielding’s sentimental novel The Adventures of David Simple (1753) raises questions central to the concerns of this volume regarding how we interpret historical representations of contagion.1 The novel’s eponymous hero and his wife Camilla have received a request from Mr Ratcliff, their rich but autocratic and treacherous relation, demanding a visit from their son Peter, to whom he stands godfather. David’s difficult decision to refuse this request at the risk of undermining his son’s prospects is made easier when ‘young Peter fell ill of the Smallpox’. Camilla persuades David to write Ratcliff a ‘civil’ letter explaining ‘that the Boy was at present too ill to take a Journey, and they were apprehensive was breeding the Small-pox’ (p. 387). Affronted, Ratcliff replies with a tirade against their ingratitude and deception, to which he adds this postscript: P.S. … you have rewarded all my dear wife’s good Offices to you, with her Destruction; for, by my being abroad, she unfortunately opened your Letter, and I found her in Fits on my return, with the Fright of seeing the name of the Small-pox in your careless letter: and you know too, she has never had that Distemper, (p. 386) 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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.046 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".