Prostitute or Parasite: The Entanglement of Scientific and Social Victorian Discourses
Bibliographic record
Abstract
Where does scientific inspiration come from? How does society determine its identity? Biology acts as a source for social metaphor, just as society can be the catalyst to drive scientific discovery. Though the word “parasite” has its origins in Greek drama, it became popularly associated with biology with the advent of the microscope. The story of the “parasite” is complicated by the frequent adoption of biological language to describe society and reinforce constructed social hierarchy. Prostitutes, as a group, are socially “parasitized” in the 19th century largely because of the threat of rapidly spreading venereal disease. The Contagious Diseases Acts, passed from 1864-1869, were a drastic medical solution to a problem that could have been more easily solved through milder social reforms. The primary motivation seems to be a fear of contagion, class mixing, and the weakening of the empire. Both the unseen biological parasite and the prostitute or “social parasite” act as threatening forces in the Victorian mind. The language of primary social and scientific literature from the 19th century shows each discourse being influenced by the other in an inextricably entangled way.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.032 | 0.099 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".