Achieving the Millennium Development Goals in Sub‐Saharan Africa: A Macroeconomic Monitoring Framework
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a macroeconomic approach to monitoring progress toward achieving the Millennium Development Goals (MDGs) in Sub‐Saharan Africa. At the heart of our framework is a macro model which captures key linkages between foreign aid, public investment (disaggregated into education, infrastructure and health), the supply side and poverty. The model is then linked through cross‐country regressions to indicators of malnutrition, infant mortality, life expectancy and access to safe water. A composite MDG Indicator is also calculated. The functioning of our framework is illustrated by simulating the impact of an increase in foreign aid to Niger at the MDG horizon of 2015, under alternative assumptions about the degree of efficiency of public investment. Our approach can serve as the building block for Strategy Papers for Human Development (SPAHD), a more encompassing concept than the current ‘Poverty Reduction’ Strategy Papers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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