Setbacks and Partial Victories: Social Justice Struggles After 28 Years of Democracy in South Africa
Bibliographic record
Abstract
Post-apartheid South Africa is ravaged by crises of extreme unemployment, poverty, and inequality. While the majority who were politically excluded by apartheid can now choose their government through democratic elections, social and economic justice continues to elude them. Neoliberal policies which seek to reduce state expenditure on social services and promote state policies that protect the interests of big businesses at the expense of working-class and poor communities, along with corruption and abuse of power, are the primary causes of poverty and unemployment. However, what is missing in the assessments of social justice since the pre-1994 democratic era is the recognition that social justice organisations have not simply disappeared, but have actually remained involved in social justice struggles. Based on information from in-depth interviews and internet sources, this article records some of the partial victories scored through these struggles, albeit in the context of generalised pauperisation of working-class and poor communities. These partial victories in the era of defeats show that these organisations, although weakened, have not given up the struggle for social justice.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.025 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.008 |
| 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".