REALITIES AND DISCOURSES ON SOUTH AFRICAN XENOPHOBIA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The responses to the January 2015 looting of foreign-owned shops inSoweto and in April in Durban's central business district and elsewhere reveal more about the South African national consciousness than the events themselves. The ritual condemnations; the initial denial of xenophobia in preference to labelling it criminality; blaming victims and convoluted excuses of perpetrators are almost worse than the official silence and long-standing passivity about well-known xenophobic attitudes. When the President insists that "South Africans in general are not xenophobic", he ignores all surveys (Afrobarometer) showing a vast majority distrust (black) foreigners, wish to restrict their residence rights and prohibit the eventual acquisition of citizenship.On these scores South African attitudes are not unique. Antiimmigrant hostility inflicts most European societies. Perhaps suspicion of strangers is even universal: preferential kin selection as an evolutionaryadvantage, as sociobiologists assert. What is uniquely South African is the ferocious mob violence against fellow Africans. Why? The structural violence of apartheid laws has continued in the post-apartheid era for many reasons: the breakdown of family cohesion in poor areas which no longer shames brutalised youngsters; loss of moral legitimacy by government institutions, particularly a dysfunctional justice system; violence was glorified in the 'armed struggle', but, above all, marginalised slum dwellers learned that they only receive attention when they act destructively. Despite a rule bound constitution for conflict resolution, in a representative survey (Afrobarometer) 43 per cent in the Western Cape agreed with the suggestion that "it is sometimes necessary to use violence in support for a just cause".
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it