Bibliographic record
Abstract
Trans people in BC experience multiple barriers to accessing health and social services. The top three reported barriers – financial expense of services, lack of service availability, and waitlist for services (Goldberg, Matte, MacMillan, & Hudspith, 2003) – point to a scarcity of services available within the publicly funded health and social service systems. The longstanding difficulties faced by trans people in accessing competent care were complicated in 2002 by the closure of the Gender Dysphoria Program (GDP) at Vancouver Hospital. The GDP, established in the early 1980s, focused on the assessment and treatment of people who met DSM criteria for “Gender Identity Disorder”. The GDP offered endocrinological, urological/gynecological, psychiatric, psychological, and social services, and was the sole gatekeeper for public health coverage for transition-related surgeries. In May 2002, as a result of provincial cuts to health transfer funding, the GDP was closed. Vancouver Coastal Health (the health region responsible for funding the GDP) agreed to work with the trans community to create a new service. Following a review of models in other regions, interviews with key service providers, and a community survey, one year after the GDP closure Vancouver Coastal Health adopted a decentralized, community-based, peer-driven model of care
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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".