Blesser relationships among orphaned adolescent girls in contexts of poverty and gender inequality in South African townships
Bibliographic record
Abstract
The term blesser has become part of South Africa's contemporary lexicon, replacing the older terminology of 'sugar daddy.' While much recent literature has focused on the blesser phenomenon, the voices of orphaned adolescent girls on their entanglement in blesser relationships have had insufficient attention. Using the theory of gender and power as an analytical lens, this qualitative study analyses the visual and textual data generated by orphaned adolescent girls on their relationships with blessers. To generate data, the participants used photovoice to represent their relationships with older male sexual partners in their resource-poor South African township neighbourhoods. Our analysis reveals a set of factors that render orphaned adolescent girls vulnerable to age-disparate relationships, such as the structural dimensions of their lives, including their status as orphaned girls, heteropatriarchy, age-based hierarchies, and poverty in their households and communities. On the other hand, our analysis explores the less understood area of the relative agency, intentionality, and proactive approach that orphaned girls take to initiating and negotiating blesser relationships. The findings have implications for further research that will expand our understanding of girls' agency-and the structural limits to that agency-in adverse socio-cultural circumstances. Such research holds potential for interventions that might enable orphaned girls to better advocate for themselves in the context of unequal power relations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".