Multilevel elements associated with HIV serosorting for sexual encounters: a scoping literature review
Bibliographic record
Abstract
A scoping literature review to identify the multilevel HIV serosorting related elements was developed. Articles from EBSCO, PubMed, PsyNET and Science Direct with serosort* or serosorting at the tittle or abstract, written in English or Spanish were included. No restriction in type of population or design were applied. 239 records were retrieved after duplicates removed, but 181 references were extracted for full-text review. Individual level: HIV knowledge, serostatus, risk perceptions, abilities to disclose and for condom use negotiation, motivations, use of drugs, stigma, attitudes toward condom use, and perceptions/beliefs about the HIV and related treatments, HIV infection rates/testing and behavioral factors. Interpersonal level: social networks, abilities (sexual behavior negotiation, and communication). Community level: stigma, social norms, access to HIV related services. Structural level: political context, HIV related funding and public policies. HIV Serosorting is not solely an interpersonal behavior it involves multilevel elements that must be acknowledged by professionals and stakeholders.
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.
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 | 0.021 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.047 | 0.035 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".