The Need for Progress in an Era of Transformation: South African Professional Military Education and Military Effectiveness
Bibliographic record
Abstract
The article explores the link between defence sector reform, military effectiveness, and education. During the post-1994 transition, defence sector reform in South Africa primarily involved the ‘transformation’ of the South African National Defence Force (SANDF). The transformation of the military, though, was predominantly driven by the notion of racial representation with little emphasis on embedding military effectiveness as a central element of the transformation effort. While, education was recognised as a key element in the transformation of the military, the emphasis was on the programmes of the National War and Defence Colleges in Pretoria, targeting senior military officers. However, the accreditation of these institutional programmes through alignment with civilian universities was problematic and has forced the military to critically evaluate the pathway for the development of its officer corps. The evolving approach of the SANDF towards military education provides a useful case study to highlight the importance of a long-term view of military effectiveness, underpinned by a committed and educated officer corps, as a central component of defence reform initiatives.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".