Refugee Precarity and Collective Transformation: Ongoing Struggles for a Liberatory Praxis in Urban South Africa
Bibliographic record
Abstract
South Africa is a significant destination for forced migrants fleeing conflict and seeking better futures. Although South Africa is a signatory on international refugee conventions and protocols, in practice, asylum seekers face bureaucratic delays, uncertainty, and obstacles in obtaining refugee status or residency permits, which creates challenges in accessing employment, accommodation, and other forms of social inclusion. In response, many forced migrants network with kin and neighbours, self‐organise, and connect to various migrant associations, faith‐based groups, and supportive social spaces. Within these spaces of migrant solidarity, this article focuses on the transformative potential of refugee‐led collective organisation, political action, alliance building, refugee research, and everyday forms of welcome within forced migrant communities. Through a review of literature alongside examples from our research in Cape Town, the article explores some of the opportunities and obstacles to building solidarity in refugee collective worlds. We refer to this potential for a liberatory praxis as an ongoing struggle. On the one hand, forced migrant precarity, mistrust, and trauma create obstacles to their participation in community organising or engaged academic research. However, while forced migrants experience waiting and exclusion, they also create possibilities of hope through what Gramsci (1971) referred to as “renovating and making critical already existing activities” of their lived experiences. Overall, the article concludes with reflections on how theorising and building deeper alliances with academic and community spaces may generate a more liberatory praxis with and for forced migrants in urban 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.032 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.003 | 0.006 |
| 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".