Supplying Basic Education and Learning to Sub-Saharan Africa in the Twenty-First Century
Bibliographic record
Abstract
This article posits that schooling in Sub-Saharan Africa has so far failed to yield the results expected of it on twogrounds. First, the population of persons accessing both basic education and other levels of education is negligible incomparison with those who ought to access them (1 out of every 4 primary school age children; less than half of thequalified secondary school students; about 7% gross enrolment within higher education). Second, schooling hasfailed to deliver the kind of socio-economic development expected in the case of Sub-Saharan Africa as a highprevalence of poverty still exists and incongruity continues to exist between the education provided and thelivelihoods of Sub-Saharan Africans. Using this poor educational and development performance as justification, amore utilitarian, relevant and sustainable approach to basic education and learning is recommended for Africa goingforward. This recommended approach combines both the current school system with a special non-formal educationsystem for the purpose of delivering basic education and learning in Sub-Saharan Africa in the twenty-first century.
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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 | 0.001 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".