Mongolia’s Public Spending On Noncommunicable Diseases Is Similar To The Spending Of Higher-Income Countries
Bibliographic record
Abstract
Although there is increased recognition of the global challenge posed by noncommunicable diseases (NCDs), translating that awareness into resources for action requires better data than typically available in low- and middle-income countries. One middle-income country that does have good-quality information is Mongolia. Using detailed administrative data from Mongolia and supplementary survey-based information, we estimated public spending on four NCDs in Mongolia and reached four main conclusions. First, Mongolia's public spending patterns on NCDs are similar to NCD spending observed in countries with much higher per capita incomes. Second, public spending for NCDs is low relative to the NCD disease burden in Mongolia. Third, public-sector NCD spending is dominated by inpatient care and hospital-based specialist outpatient services, which suggests inefficiency in resource use. Finally, while public spending on cardiovascular disease is evenly distributed across regions, for cancers it is heavily concentrated in the nation's capital.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".