The Relativity of Poverty and Income: How Reliable are African Economic Statistics?
Bibliographic record
Abstract
It has been argued that the fundamental cause of Africa’s current relative poverty is a lack of pro-growth institutions deriving either from the colonial system, the period of slavery, or from particular geographic or population characteristics. This article takes a fresh look at estimates of African country incomes. It subjects the available datasets to tests of accuracy, reliability, and volatility, and finds that there is very little to explain in terms of diversity of income between countries. With the exception of some resource-rich enclaves, a few island states, and South Africa, the income of one African economy is not meaningfully different from another. It is found that the majority of African countries should for all practical purposes be considered to have the same income level. The article therefore concludes that it is futile to use GDP estimates to prove a link between income today and existence of pro-growth institutions in the past, and recommends a searching reconsideration of the almost exclusive use of GDP as a measure of relative development.
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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 | 0.022 | 0.208 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".