Bibliographic record
Abstract
For some, Gender Identity Disorder (GID) becomes the only way to achieve sex reassignment surgery (SRS). It will be shown that GID acts as a problematic regulatory mechanism based on its application. It will be argued that GID normalizes a dichotomous view of gender. In this way, GID’s implicit applications allow the mental health professional to assert their views of what proper gendered behavior is, further normalizing a binary view of gender. Insurance companies require a GID diagnosis in order to provide economic assistance to those wishing to undergo sex reassignment surgery. Those who cannot afford to transition must fall under GID’s gaze in order to achieve SRS. This will be shown to be unacceptable and a way in which GID operates as a regulatory mechanism. Appealing to a GID diagnosis can further stigmatize the individual who wishes to transition due to the necessitation of distress as an explicit mechanism of diagnosis. Having to fall under GID may internalize the negative aspects of the diagnosis. A criticism of GID as a form of psychopathology will be given and also be linked to the idea of GID as a regulatory apparatus. It will be shown that there should be no link between ethical discomfort and GID-free sex reassignment surgery. Also, it will be shown that psychopathology has normalizing capabilities that further entrench gender binaries. It is important to consider the removal of GID from the DSM, but, as a condition, still offer funding for sex reassignment surgery without having to appeal to a mental health professional’s assessment.
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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.107 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.021 | 0.044 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".