Bibliographic record
Abstract
This Special Issue is organized around the theme of "transition into a new African university in the Global South in the 21st Century" to reflect on historical trajectories, contemporary challenges, and future prospects of African higher education systems.The special issue is a product of an open call that targeted a wide range of scholars with diverse experiences and viewpoints.Incorporating diverse perspectives from various conceptual, theoretical, methodological, and empirical aspects of higher education transformation, this special issue presents a collection of scholarly papers that are both grounded in empirical evidence and are conceptually rigorous.The papers featured in this special issue offer thought-provoking perspectives and inspire critical debate on the issue of the future of African higher education.The papers have been arranged into four sub-thematic areas, namely, (i) Experiences and emerging practices within the African university, (ii) Barriers and transformation (iii) Transitioning to the new African university, and (iv) The future of the new African university. (i) Experiences and Emerging Practices within African UniversitiesThis sub-theme explores the emerging trends in African higher education systems that present both challenges and opportunities.This is with particular emphasis and relevance to students' epistemic access and success.It delves into the emergence of plurilingual practices which
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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 | 0.007 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.019 | 0.018 |
| Insufficient payload (model declined to judge) | 0.060 | 0.048 |
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".