Poverty Eradication in Fragile Places: Prospects for Harvesting the Highest Hanging Fruit by 2030
Bibliographic record
Abstract
This paper explores the range of likely and potential progress on poverty eradication in fragile states to 2030. Using the International Futures model and recently released 2011 International Comparison Program data, this paper calculates current (2015) poverty for a US$1.90 poverty line, and subsequently runs three scenarios. The estimates suggest that there are 485 million poor in fragile states in 2015, a 33.5 per cent poverty rate. This paper’s Base Case scenario results in a forecasted 22.8 per cent poverty rate in fragile states by 2030. The most optimistic scenario yields a 13.1 per cent poverty rate for this group of countries (257 million). An optimistic scenario reflecting political constraints in fragile states yields a 19.1 per cent poverty rate (376 million). Even under the most optimistic circumstances, fragile states will almost certainly be home to hundreds of millions of poor in 2030, suggesting that the world must do things dramatically differently if we are to reach the high hanging fruit and truly ‘leave no one behind’ in the next fifteen years of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".