MétaCan
Menu
Back to cohort

Achieving the Millennium Development Goals in Sub‐Saharan Africa: A Macroeconomic Monitoring Framework

2006· article· en· W3123614766 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Economy · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsMillennium Development GoalsLife expectancyPovertyEconomicsInvestment (military)Aid effectivenessDevelopment economicsEconomic growthPublic investmentMalnutritionMacroDeveloping countryMacroeconomicsPopulationPolitical scienceMedicineFiscal policyPoliticsEnvironmental healthComputer science

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.251
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it