No. 79: Rendering South Africa Undesirable: A Critique of Refugee and Informal Sector Policy
Bibliographic record
Abstract
To understand the policy environment within which refugees establish and operate their enterprises in South Africa’s informal sector, this report brings together two streams of policy analysis. The first concerns the changing refugee policies and the erosion of the progressive approach that characterized the immediate post-apartheid period. The second concerns the informal sector policy, which oscillates between tolerance and attempted destruction at national and municipal levels. While there have been longstanding tensions between foreign and South African informal sector operators, an overtly anti-foreign migrant sentiment has increasingly been expressed in official policy and practice. This report describes the strategies being used to turn South Africa into an undesirable destination for refugees, including the setting up of additional procedural, administrative and logistical hurdles; the undercutting of court judgments affirming the right of asylum-seekers and refugees to employment and self-employment; ensuring that protection is always temporary by making it extremely difficult for refugees to progress to permanent residence and eventual citizenship; and restricting opportunities to pursue a livelihood in the informal sector. The authors conclude that the protection of refugee rights is likely to continue to depend on a cohort of non-governmental organizations prioritizing migrant livelihood rights and being willing and able to pursue time-consuming and costly litigation on their behalf.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.049 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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".