AFRICAN GROWTH RECURRING: AN ECONOMIC HISTORY PERSPECTIVE ON AFRICAN GROWTH EPISODES, 1690–2010
Bibliographic record
Abstract
Africa has not suffered a chronic failure of growth. In fact, Africa has experienced recurring periods of growth, and this paper reviews some of these growth “spurts” to substantiate that claim. The immediate cause of low income in Africa is that these “spurts” have always been followed by a ‘‘bust’’. This is a significant reorientation of the central research question – away from a search for the root causes of Africa's underdevelopment and towards explaining the causes and effects of growth and decline. The growth spurts are approached as local responses to a global demand for African produced commodities. In this paper, I shall argue that these supply responses involved more than a reallocation of land and labour; they entailed investment and required institutional change. It is precisely because these periods of rapid economic change and accumulation caused significant qualitative changes in how society and the economy were organized that they cannot be ignored – as they have tended to be in the search for a root cause of Africa's chronic failure to achieve growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| 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".