Trends in Scientific Output on the Lesbian, Gay, Bisexual, and Transgender (LGBT) Community Research: A Bibliometric Analysis of the Literature
Bibliographic record
Abstract
Introduction: Lesbian, Gay, Bisexual, and Transgender (LGBT) represent a diverse group with special needs due to the unusual developmental experiences and social inequalities. This paper aims to explore and outline a future research direction in LGBT issues through tracing our historical understanding of this population from an aspect of scientific research. Methods: LGBT-related peer-reviewed documents were retrieved from the PubMed database and the study period was set from the inception to 2021. Python-based methods were then performed to analyze the publication metadata and extract the most prominent research topics based on the abstract contents. Key points covered in the study were the development and trend of scientific effort and research themes in the LGBT topic, identified through the Bigram model and Latent Dirichlet Allocation algorithm. Results: A total of 21,221 publication records were retrieved from the PubMed database. Literature analyses demonstrated that scientific research in LGBT had grown gradually but began to gain momentum since 2010, evidencing increased attention to this demographic in the last decade. Regarding the region-wise scientific effort in LGBT, the United States (U.S.) was the most productive country (with > 45% of the total publications), followed by the United Kingdom (UK), Canada, Australia, and the Netherlands. Furthermore, Peru and Thailand, besides the U.S., Australia, and Canada, were the top countries that had relatively allocated more of their scientific efforts to LGBT research based on the calculated activity indices. Topics attracting the most attention in LGBT research over time were “male sexuality and risk", followed by "sexual development", "health care service", "social experience", and "intervention strategies". Discussion: This study provided a broad view of the developmental trends in LGBT research from invisibility to attention through a bibliometric lens and could serve as a data-based guideline for policymakers and social scientists. Take-home message: As shown by this bibliometric analysis, scientific research in Lesbian, Gay, Bisexual, and Transgender (LBGT) had grown gradually but began to gain momentum since 2010, evidencing increased attention to this demographic in the last decade.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.041 | 0.152 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".