Medical Queeries: Transgender Healthcare
Bibliographic record
Abstract
Abstract Transgender individuals, particularly those who are undergoing or have undergone sex reassignment therapies or surgeries, constitute an under-serviced population when it comes to access to healthcare. This is the result of a variety of reasons. However, physician behavior and negative experiences within the health care system are both commonly cited reasons why transgender individuals fail to seek appropriate medical attention. The goal of this resource is to inform physicians and other health care providers of some of the major issues and barriers that transgender people face when seeking medical care. It also proposes several potential solutions to these problems. “Medical Queeries: Presenting Transcare Initiatives,” is an empowering educational film that provides health care workers with an opportunity to better understand and reflect upon the needs of the transgender community. The film features a transgender individual who focuses on the approaches health care providers (particularly physicians and nurses) can consider in order to improve transcare management. After viewing this video, the audience should be able to define transgender, transcare, and develop self-awareness of how to combat transgender barriers to health care. The accompanying PowerPoint presentation serves as a discussion tool to further enhance student learning. This learning module requires only a projector and screen, and a facilitator. The session can be run in 45-60 minutes, including time allotted for discussion. The length of the presentation means that it can be done over a lunch hour or fitted into a regular meeting. Discussion is key—having someone to help facilitate conversation will make the session engaging, interesting, and informative. The video has been distributed through the Association of Faculties of Medicine of Canada, and through various transgender healthcare presentations in health care settings such as the London Health Sciences Centre. It is also found on the Canadian Healthcare Education Commons.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".