Social capital and HIV-serodiscordance: Disparities in access to personal and professional resources for HIV-positive and HIV-negative partners
Bibliographic record
Abstract
As people living with HIV are living longer lives, they have a correspondingly greater opportunity to enjoy long-term romantic and sexual partnerships, including with persons who do not live with HIV ("serodiscordant" relationships). In these dyads, asymmetries may emerge in access to social resources between partners. In this paper we examined how serodiscordant couples access informal (interpersonal, such as family and friends) and formal (practitioner, such as doctor or social worker) social resources for health. We recruited 540 participants in current serodiscordant relationships, working with 150 AIDS service organizations and HIV clinics across Canada from 2016 to 2018. Our findings demonstrate that partners with HIV have greater access to formal resources than their partners (through health care professionals, therapists/counselors/support workers), while both persons have similar access to resources through informal social relationships (family and friends). Furthermore, the findings indicated that HIV positive partners accessed more varied forms of support through formal ties, compared to HIV negative persons. We offer recommendations for changes to how HIV-negative partners in a serodiscordant relationship are served and cared for, and particularly, the importance of moving toward dyad-focused policies and practices.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".