Trafficking As a Human Rights Violation: Is South Africa’s Curriculum Stuck in a Traffick Jam?
Bibliographic record
Abstract
Human trafficking is a form of modern day slavery and is often collectively referred to as a human rights violation.However, human trafficking is more complex than this suggests as this article attempts to demonstrate. It begins bydescribing the landscape of international trends in human trafficking, with particular attention to child trafficking. Next,national trends in South African legislation and education are outlined. It then describes a qualitative documentresearch study that was conducted to explore the landscape of this phenomenon. The aim was to ascertain the extent towhich human trafficking, child trafficking in particular, is addressed in the national curriculum. The document analysisincluded all of the compulsory subjects in Grades R to 12. By employing content analysis, the areas in the explicitcurriculum where human trafficking is included could be identified. Based on the findings of this research, SouthAfrica’s curriculum seems to be stuck in a traffick jam in the sense that it does not adequately explore the topic ofhuman trafficking. As a result, children are not gaining an awareness and knowledge of the realities of this kind oftrafficking. This article concludes with an appeal to curriculum scholars to embrace curriculum as a complicatedconversation that expresses lived experiences and a desire for a profoundly transformative curriculum in the future,which can help to prevent the trafficking of our children. Such discourse would be a way of breaking the shackles thatare binding our children and preventing them from embracing their vulnerability.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| 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".