Understanding Ubuntu and its contribution to social work education in Africa and other regions of the world
Bibliographic record
Abstract
The overarching philosophy of Black people of Africa is known by different names but Ubuntu is the most popular name. Ubuntu’s origin is attributable to Black Africans in all regions of the continent—North, West, Central, East and South. Different communities may emphasize its different aspects but they are common knowledges, values and practices. The article begins with a discussion of the philosophy of Ubuntu and its application at the micro (individual and family), meso (communal), macro (societal, environmental and spiritual) levels. The roles of Ubuntu in social work education are then discussed with a focus on Africa. These roles are offering a philosophical foundation; being a source of ethics and values; being a source of knowledge including theories; offering a history of African social work; shaping social work methods; building the confidence of educators, learners and communities; shaping research; being a pedagogical approach; enriching fieldwork education; and indigenizing and decolonizing. However, there are several impediments to the full use of Ubuntu, including the colonial history of the profession, changes to African society and lack of Ubuntu-inspired educational resources. The authors recommend continuous development and use of educational resources that are created with Ubuntu philosophy as a guiding principle.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".