“It takes a village to raise a child,” university teachers’ views on traditional education, modern education, and future I integration in Ethiopia
Bibliographic record
Abstract
Introduction Indigenous education has recently gained prominence in international debates for its role in addressing the social, economic, and political issues faced by African states. Ethiopia, like other African countries, had its education system based primarily on the transmission of socio-professional aptitudes, religious values, skills, and intergenerational knowledge as a way to preserve the social, cultural, and religious values of the Ethiopian community. In the early 20th century, Ethiopia wholeheartedly adopted a Western higher education system in a tabula rasa approach that sought to obliterate deeply rooted cultural norms and rapidly transition the country’s traditional religious system to a secular one. Methods This qualitative study used semi-structured interviews to explore the perspectives of Ethiopian university teachers about the benefits and limitations of traditional education and the potential to integrate traditional and modern education in Ethiopian universities. Results Study findings show that, despite agreement that “traditional” education is distinct from other educational systems, there are varying notions of what constitutes “indigenous” education. Participants also suggested that the dominant rationale for the tabula rasa approach in Ethiopian modern education was to modernise the country and embrace a global perspective on education that incorporates ideas and advances from other cultures while still being firmly entrenched in local values and educational systems. Discussion Insights have implications for education systems in African and other low- and middle-income countries (LMICs) in terms of developing strategies for the pluralistic approach to knowledge systems.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".