The dynamics of sexual risk amongst South African youth in age-disparate relationships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: South Africa has the highest burden of HIV in the world with over 8 million people living with HIV. Young women and girls account for a quarter of new HIV infections while making up only 10% of the population. A key driver of HIV incidence is transactional and survival sex between adolescent girls or young women and older men (the latter referred to as 'sugar-daddies' or 'blessers'). This paper expands on the existing literature on age-disparate and intergenerational relationships to provide social and behavioural interpretations of how young men, commonly omitted from studies on this topic, and women in concurrent relationships with both their peers and older partners perceive and navigate sexual risk. Method: We conducted a qualitative study in a rural setting of uMgungundlovu District, KwaZulu-Natal Province, with purposively selected male and female participants aged 18-24 years old in age-disparate relationships. Semi-structured in-depth interviews (IDI) were conducted and analysed using interpretative phenomenological analysis (IPA) to explore existing information, motivations, and behavioural practices around relationships and sexual risk. Results: The themes and related sub-themes found through IPA included the following: (1) navigating dating: narratives that show a strong preference for being in an age-disparate relationship; the challenges that young people face when choosing an older person as a side partner; and social media applications seen as creating opportunities to meet side partners; and (2) the distribution of love and trust in a multi-party sexual network: condom (mis)use differentiates between straights-those in a serious relationship-and sides; and the power of eye-test seroguessing, the praxis of testing people visually for HIV in nullifying existing knowledge about sexual and reproductive health risk. Discussion: This research offers an understanding of how schemas of non-condom use are organised. We observed that while condom-less sex is often viewed as essential to building social capital in a serious relationship, it is not the only factor that determines sexual relationship power. Eye-test seroguessing not only develops consortium (trust, reciprocity, and solidarity), but it fulfils the psycho-social need to belong to a network of serious relationships. Moreover, it is critical to the enactment of masculinities because it consolidates femininity to keep men happy, i.e., by being passive in the sexual encounter, women constrain their self-efficacy to act contrary to the conventions of reputable women. Therefore, it is plausible that in the serosorting that occurs prior to unprotected sexual acts, the power of eye-test seroguessing limits the ability to engage in safe sexual practices.
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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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it