Where do the world’s multidimensionally poor people live?: OPHI working paper no. 61
Bibliographic record
Abstract
This paper asks where do the world’s multidimensionally poor people live? The paper considers how the\nglobal distribution of multidimensional poverty differs from the global distribution of income poverty\nand assesses the sensitivity of findings to widely used (although somewhat arbitrary) country\nclassifications. Surprisingly perhaps, only a quarter of multidimensionally poor people and just one-third\nof severely multidimensionally poor people live in the world’s poorest countries – meaning Low Income\nCountries (LICs) or Least Developed Countries (LDCs). The sensitivity of findings about country\nthresholds for low and middle-income countries is discussed. The paper argues that there is a split of\ndistribution poverty between both stable Middle-Income Countries (MICs) and low-income fragile states\nand that there is a 'multidimensional bottom billion' living in stable MICs. \n The analysis is based on 83 countries and uses the 2011 MPI poverty estimates of the UNDP HDR.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".