Experiences of Female Commercial Sex Workers in Marabastad, Pretoria
Bibliographic record
Abstract
This paper discusses critically the experiences of the female commercial sex workers in Marabastad, Pretoria in South Africa. Even though commercial sex work is illegal in South Africa, evidence suggests that some women practice it owing to various factors and an investigative analysis of engaging in such an illegal activity in South Africa needs thorough investigation. This paper aims at providing synthesis on the bio-psychosocial benefits and risks of commercial sex work for women involved in it. A qualitative research approach was adopted which purposely interviewed nine women who practised commercial sex work in Marabastad. Due to secrecy in commercial sex work, snowball sampling was also employed to ensure that only women involved in the practice would be accessed to reach data saturation point for the study. Data were analysed thematically to capture the experiences of women. The findings showed that even though women practise commercial sex work in Marabastad, risks are more experienced than the benefits. Unpleasant life circumstances were revealed as the most compelling reasons women practised commercial sex work despite the inevitable bio-psychosocial consequences. This paper recommends various multi-sectorial approaches to ameliorate the consequences experienced by women practicing commercial sex work in Marabastad in South Africa.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".