More than a case of mistaken identity: Adult entertainment and the making of early sexology
Bibliographic record
Abstract
Sexology emerged as a discipline during a period of keen concern about the social effects of sexually explicit media. In this context, sex researchers and their allies took pains to establish the respectability of their work, a process that often involved positioning sexual science in opposition to erotic literature and images. This article argues that this presentation of sexual science obfuscated sex researchers’ complex relationship with erotic print culture, which during the late 19th and early 20th centuries provided sexual scientists with access to explicit material that served as evidence for theories about human sexuality, facilitated transnational exchanges of sexual-scientific thought by bringing sex research across borders, and introduced sex research to wider audiences. Erotic print culture can thus be seen as one of several fields that contributed to the interdisciplinary development of sexology and facilitated the diffusion of sexual-scientific theories. Sex researchers’ shifting, often ambivalent relationship with erotic print and its producers emphasizes that while the boundaries of sexology were extremely porous, they were also heavily policed: Working to establish a modern, respectable new branch of science, sexual scientists reframed the output of other fields of enquiry as products of their own, blotted their reliance on these sources from the historical record, and denigrated them in public writing.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.059 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".