Bibliographic record
Abstract
Abstract. Sexual scientists have recognized for over a century that biologic males who seek sex reassignment – male-to-female (MtF) transsexuals – are not a homogeneous clinical population but comprise two or more distinct subtypes with different symptoms and developmental trajectories. The most widely used typologies of MtF transsexualism have been based on sexual orientation and have distinguished between persons who are androphilic (exclusively sexually attracted to males) and those who are nonandrophilic (sexually attracted to females, both males and females, or neither gender). In 1989, psychologist Ray Blanchard proposed that most nonandrophilic MtF transsexuals display a paraphilic sexual orientation called autogynephilia, defined as the propensity to be sexually aroused by the thought or image of oneself as a woman. Studies conducted by Blanchard and colleagues provided empirical support for this proposal, leading to the hypothesis that almost all nonandrophilic MtF transsexuals are autogynephilic, whereas almost all androphilic MtF transsexuals are not. Blanchard’s ideas received increased attention in 2003 after they were discussed in a book by psychologist J. Michael Bailey. The concept of autogynephilia subsequently became intensely controversial among researchers, clinicians, and MtF transsexuals themselves, causing widespread repercussions. This article reviews the theory of autogynephilia, the evidence supporting it, the objections raised by its critics, and the implications of the resulting controversy for research and clinical care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".