Documenting Research with Transgender, Nonbinary, and Other Gender Diverse (Trans) Individuals and Communities: Introducing the Global Trans Research Evidence Map
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
There is limited information about how transgender, nonbinary, and other gender diverse (trans) people have been studied and represented by researchers. The objectives of this study were to: (1) increase access to trans research; (2) map and describe trans research across subject fields; and (3) identify evidence gaps and opportunities for more responsible research. Eligibility criteria were established to include empirical research of any design, which included trans participants or their personal information and that was published in English in peer-reviewed journals. A search of 15 academic databases resulted in 25,230 references; data presented include 690 trans-focused articles that met the screening criteria and were published between 2010 and 2014. The 10 topics studied most frequently were: (1) therapeutics and surgeries; (2) gender identity and expression; (3) mental health; (4) biology and physiology; (5) discrimination and marginalization; (6) physical health; (7) sexual health, HIV, and sexually transmitted infections; (8) health and mental health services; (9) social support, relationships, and families; and (10) resilience, well-being, and quality of life. This map also highlights the relatively minor attention that has been paid to a number of study topics, including ethnicity, culture, race, and racialization; housing; income; employment; and space and place. Results of this review have the potential to increase awareness of existing trans research, to characterize evidence gaps, and to inform strategic research prioritization. With this information, it is more likely that trans communities and allies will be in a position to benefit from existing research and to hold researchers accountable.
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 | 0.020 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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