The counter‐reparative impacts of South Africa's reparations gap: victims as reparations ‘experts’ and the role of victims’ organizations
Bibliographic record
Abstract
Abstract This article offers a victim‐centric analysis of reparations relating to apartheid in South Africa. We identify a multi‐dimensional ‘reparations gap’, which refers to the disconnect between victims and the state in relation to reparations, including the meanings attributed to reparations, and the perception, evaluation, and experience of reparations. The reparations gap has had profoundly ‘counter‐reparative’ impacts on the relationship between victims and the government. Appreciating victims as reparations ‘experts’ with unique knowledge rooted in lived experience, this article explores their narratives of the ongoing need for reparations, specifically relating to a nexus of historically induced structural and systemic injustice. The article calls for the comprehensive and continuous participation of victims and their organizations to close the reparations gap.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.030 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".