Visualizing patterns and gaps in transgender sexual and reproductive health: A bibliometric and content analysis of literature (1990–2020)
Bibliographic record
Abstract
Background: Transgender people face numerous obstacles to accessing adequate, affordable, and appropriate sexual and reproductive health (SRH) services as outlined by the UN's Sustainable Development Goal 3.7 target of achieving universal access to SRH services by 2030. However, transgender SRH sits as a poorly researched area within public health that makes it difficult to understand the current dilemmas facing transgender SRH. This article reports the findings of a study aimed at taking stock of global research in transgender SRH. Methods: A bibliometric analysis, used to gain insights from the retrieved literature's metadata, alongside a content analysis were utilized to examine the growth, impact, and content of retrieved articles. Results: Nine hundred fourteen journal articles were retrieved, predominately in English (884; 96.7%). These involved 3653 authors from 46 affiliated countries. Most frequent keywords included HIV, PrEP, and gender identity; corresponding to the SRH issues studied, namely HIV/AIDs and gender reassignment. Top cited and overall articles originated heavily from US affiliated authors. Content analysis outlined the articles' inclusion of the transgender community to largely have a mixed focus with cisgender people in research, these articles largely disease-focused and conducted within cities in the United States. Conclusions: Growth in transgender SRH research was minimal until the early-2010s, after which a steep rise can be observed. Research retrieved has a disproportionate clinical and biomedical focus around HIV and related STI issues suggesting a failure to engage with reproductive justice and more comprehensive rights-based understanding of SRH. The sustained use of derogative language suggests a need for greater inclusion and awareness of trans identities within research and publishing. The dominance of the United States in authorship and as a site of research establishes the need for more geographically diverse research, trans, and LMIC-led research enquiry and creating greater opportunities for cross-cultural, comparative, and collaborative scholarly work.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".