Emerging Trends in Social Isolation of People Living with HIV: A Bibliometric Analysis
Bibliographic record
Abstract
Objective: A bibliometric analysis of the field of social isolation of people living with HIV was used to understand the context and trends of research in the field. Methods: A visual analysis of authors, institutions, country and keywords was conducted using CiteSpace 6.1R2 software. Results: A total of 1310 studies on social isolation of people living with HIV were retrieved from the WoS core database. The number of publications on the social isolation of people living with HIV showed an overall increasing trend, with the highest number of publications (147) in 2021. Author Otis, Joanne ranked first in the number of publications (8), while the University of Toronto (46) was the research institution with the most publications. Keyword clustering showed that the first cluster was hiv/aid; keywords with high co-occurrence centrality were “prevalence” (0.20) “aid” (0.18), and “impact” (0.17). “Qualitative research”, “risk factors”, and “older adults” are the hotspots of current research. Conclusion: Research on social isolation of People Living with HIV has shown certain characteristics and trends in terms of the number of articles published, research focus and interdisciplinary cooperation. Future research should continue to explore the strengths and application potential of this field in depth, and provide more comprehensive and effective scientific support for the prevention and treatment of social isolation among people living with HIV through interdisciplinary cooperation and expansion of research focus.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.183 | 0.189 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".