Bibliographic record
Abstract
Trans people suffer from significant health disparities in multiple areas, one of which is public health. Real or perceived stigma and discrimination within biomedicine and healthcare delivery, in general, can affect trans people’s desire and ability to access appropriate care, thereby impacting their own health. The biggest barrier to both safe hormone therapy and adequate general medical care for transgender patients is the lack of access to care. Despite guidelines and data supporting the current transgender medicine treatment paradigm, trans patients report that a lack of providers experienced in trans medicine represents the single largest component inhibiting access. Transgender care is not taught in conventional medical training programs and very few doctors have the necessary knowledge and level of comfort. As such, this book provides up-to-date information on the health of transgender people. Chapters address such topics as standards for transgender care, the treatment of gender dysphoria, the lived experiences of transgender persons in Brazil and India, and much more.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.025 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.058 |
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; both teacher heads agree on what is shown here.
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".