Bibliographic record
Abstract
Asexuality, quickly becoming a burgeoning sexual identity category and subject of academic inquiry, relies at this budding moment of identity demarcation on a series of scientific studies that seek to ‘discover’ the truth of asexuality in and on the body. This article considers the existing scientific research on asexuality, including both older and more obscure mentions of asexuality as well as contemporary studies, through two twin claims: (1) that asexuality, as a sexual identity, is entirely specific to our current cultural moment – that it is in this sense culturally contingent, and (2) that scientific research on asexuality, while providing asexuality with a sense of credibility, is also shaping the possibilities and impossibilities of what counts as asexuality and how it operates. In the first section, I consider how older scientific research on asexuality, spanning from the late 1970s to the early 1990s, is characterized by a disinterest in asexuality. Next, turning to recent work on asexuality, the beginning of which is marked by Anthony Bogaert’s 2004 study, I demonstrate how asexuality becomes ‘discovered’, mapped, and pursued by science, making it culturally intelligible even while often naturalizing, in the process, what I argue are harmful sexual differences.
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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 | 0.045 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.071 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".