Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Financial protection against the cost of unforeseen ill health has become a global concern as expressed in the 2005 World Health Assembly resolution (WHA58.33), which urges its member states to "plan the transition to universal coverage of their citizens". An important element of financial risk protection is to distribute health care financing fairly in relation to ability to pay. The distribution of health care financing burden across socio-economic groups has been estimated for European countries, the USA and Asia. Until recently there was no such analysis in Africa and this paper seeks to contribute to filling this gap. It presents the first comprehensive analysis of the distribution of health care financing in relation to ability to pay in Ghana. METHODS: Secondary data from the Ghana Living Standard Survey (GLSS) 2005/2006 were used. This was triangulated with data from the Ministry of Finance and other relevant sources, and further complemented with primary household data collected in six districts. We implored standard methodologies (including Kakwani index and test for dominance) for assessing progressivity in health care financing in this paper. RESULTS: Ghana's health care financing system is generally progressive. The progressivity of health financing is driven largely by the overall progressivity of taxes, which account for close to 50% of health care funding. The national health insurance (NHI) levy (part of VAT) is mildly progressive and formal sector NHI payroll deductions are also progressive. However, informal sector NHI contributions were found to be regressive. Out-of-pocket payments, which account for 45% of funding, are regressive form of health payment to households. CONCLUSION: For Ghana to attain adequate financial risk protection and ultimately achieve universal coverage, it needs to extend pre-payment cover to all in the informal sector, possibly through funding their contributions entirely from tax, and address other issues affecting the expansion of the National Health Insurance. Furthermore, the pre-payment funding pool for health care needs to grow so budgetary allocation to the health sector can be enhanced.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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