Bibliographic record
Abstract
Asian Indians arrived in South Africa in 1860 during the era of the British Empire. Three occupational groups were represented: indentured agricultural workers, business entrepreneurs and a few professionals. Their presence was not welcomed by White South Africa. The ideology of Apartheid (“separateness”) ushered in oppressive legislation for all Non-Whites from 1948 until the first democratic elections of 1994, a period of trauma, violence and pain for Non-White peoples. This report centres on traumatic personal experiences during Apartheid of 100 Asian Indians, 54 males and 46 females, professional and business people, Hindus, Muslims and Christians, living in segregated racial zones of metropolitan Durban, South Africa. These traumatic incidents yielded six basic themes identified by the technique of constant comparative analysis, a central qualitative analytical approach in grounded theory. Four themes related directly to Apartheid laws; two themes to interactions with the White public and police, invariably involving abuse. The experiences created emotional distress, powerlessness, anger and fear. Few risked protesting discriminatory laws as most were immobilised by fear. Forty-six % judged they adapted to the Apartheid system, and most were aware of its psychological effects. Illustrating with excerpts from the reported experiences, a psycho-socio-political analysis of the dynamics of oppression is presented in the context of the stages of conscientisation to empowerment (Prilleltensky & Gonick, 1996).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.038 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.003 |
| 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".