Need for more research on and health interventions for transgender people
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Recently, lesbian, gay, bisexual, and transgender (LGBT) scientific production is growing, but transgender (TG) people is less considered in the LGBT-related research, highlighting the lack of representative data on this neglected population. METHODS: To assess the current status of scientific production on TG population, a bibliometric study was performed using the articles on TG people deposited in five databases, including PubMed/Medline, Scopus, Science Citation Index (SCI), Scientific Electronic Library Online (SciELO) and Latin American and Caribbean Health Sciences Literature (LILACS). RESULTS: The PubMed/Medline search retrieved 2370 documents, which represented 0.008% of all articles recorded in Medline. The Scopus search identified 4974 articles. At SCI, 2863 articles were identified. A search of the SciELO database identified 39 articles, whereas the LILACS search identified 44 articles. Most papers were from the US (57.59%), followed by Canada (5.15%), the UK (4.42%), Australia (3.19%), The Netherlands (2.46%) and Peru (1.83%). These six countries accounted for 74.6% of all scientific output. CONCLUSIONS: The findings indicate that the TG-related research is low, especially in low-income developing countries, where stigma and discrimination are common. More awareness, knowledge, and sensitivity in healthcare communities are needed to eliminate barriers in health attention and research in this population.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it