Ubuntu: Applying a Southern Theoretical Paradigm to Counter Youth Radicalization
Bibliographic record
Abstract
Abstract As societal and community institutions, schools operate within certain worldviews. These worldviews impact the aims and objectives of schooling and therefore influence the culture of the school and classroom, not to mention the content of the curriculum and teacher practices. In this paper I consider the “traditional” African worldview of Ubuntu as a framework or a foundation for schooling and education to combat the alienation and discrimination faced by many students in the schools in Western countries which are pushing neo-liberal objectives but that lead them to violence and increasingly, to radicalization. I look at the recent phenomenon of radicalization that makes societies and nations unsafe, and some of the push and pull factors that are increasingly attracting some students in the contemporary world to extremist actions. While the threat of Islamic terrorism seems to have subsided, the threats from extreme right-wing nationalist and alt-right groups is increasing at a fast pace (Ghosh et al, 2016a; Eger and Valdex, 2014; Fadel, 2019; Jones, 2018). I contrast the concept of Ubuntu with Western values of humanism and analyze the core values of the Ubuntu worldview in pedagogical practices. I conclude that present punitive measures are ineffective in preventing radicalization which poses a security threat to all nations, but that schooling has an important role to play in combating this phenomenon through a worldview that is not only humanistic but different in its very understanding of what a human being is and therefore, in preventing schools from alienating individuals and groups.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".