The political economy of concurrent partners: toward a history of sex–love–gift connections in the time of AIDS
Bibliographic record
Abstract
Over the last decade, one of the most influential explanations for high HIV prevalence in sub-Saharan Africa is the existence of sexual networks characterised by concurrent partners. Recently, however, a growing number of scholars have challenged the evidential basis for the concurrency argument. While this dispute has led to a call for more sophisticated quantitative methods to measure concurrency, this article widens the discussion to emphasise the political economic roots and qualitative dimension of concurrent partnered relations. Specifically, the paper argues for the importance of situating concurrency within key historical processes and, to that end, gives special consideration to the growth of ‘transactional sex' – non-prostitute but material relations between men and women. Critics of the concurrency–HIV thesis have sometimes dismissed as anecdotal accounts of sex–gift exchanges in Africa. Yet by exploring through an ethnographic/historical lens the changing configuration of sex, love and gifts in South Africa, this article illuminates different manifestations of concurrency, including connections between concurrency and condom use.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| 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".