Social Policies under SAP in Ghana: Implications for Children's Human Capital Formation
Bibliographic record
Abstract
In the 1980s and 1990s, the International Monetary Fund (imf) and World Bank recommended a structural adjustment program (SAP) in Ghana as a response to its economic crises. This paper examines educational and health policies under SAP and addresses the following issues: How did educational and health policies impact children? What are the implications of these impacts for the future of children and human capital formation? To answer these questions, we investigate the (1) availability and accessibility of schools and health facilities; (2) quality of schools and health care; (3) costs associated with schooling and using health facilities; and (4) factors that moderate the impact of education and health policies on the lives of children. The findings are that of (1) low educational attainment; (2) poor health, high morbidity and mortality levels; and (3) inequities based on geography, income, and gender. The implication for policy is that there is a need to promote human capital development by investing in it.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".