African States and Development: A Historical Perspective on State Legitimacy and Development Capacity, 1890-2010
Bibliographic record
Abstract
Do African states have the capacity for ‘Development’? African states are described either as incapable or uninterested in development, but these have not been historicized. This paper examines when, where and under what conditions states in sub-Saharan Africa were capable of nurturing development and when, where and under what conditions they were not. Judging African states to be incapable or uninterested in development would call for a complete reorientation of most internationally sponsored development policy initiatives.This paper aims to provide a comparative basis by changing the objective from explaining the relative dysfunction of states in Africa, towards explaining determinants of how those states function, thus keeping with the principle of ‘reciprocal comparison’. Research has so far tended towards normative statements about how African states ought to be, rather than concrete analysis of how states function. At present, we have no clear empirical metric to gauge whether African states are more capable, stronger or more legitimate today than they were 20, 50 or 100 years ago. This paper sheds light on comparative state development capacity in Sub-Saharan Africa by evaluating the conditions under which capacities for development were strengthened and under which such conditions were weakened.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".