What Next for the Political Economy of Development in Africa? Facing Up to the Challenge of Economic Transformation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sub-Saharan Africa faces an alarming long-term outlook. With a massive demographic dividend in prospect, few countries have the means to turn this to their advantage by rapidly expanding employment-intensive economic sectors. Economic analysis is facing up to this challenge, with new attention to structural change, technology absorption and the capabilities of firms. However, this article argues, it has not got to the nub of the problem. Two connected issues have been under-examined: the productivity breakthrough in agriculture without which employment-intensive manufacturing will not take off; and the weak producer incentives generated by prevailing rural social-property relations. While most economists are ‘Smithian’ in their neglect of property relations, political science research has done less than it might to help. Responding energetically to ‘bringing the state back in’, it has generated a rich body of evidence on the configurations of power that make regimes effectively developmental. But these findings remain crucially incomplete. In future, the focus should be on the political economy of bringing productivity-enhancing social disciplines to the countryside.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it