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.
Bibliographic record
Abstract
Malaria ranks among the foremost health issues facing tropical countries. In this paper, we explore the determinants of cross-country differences in malaria morbidity, and examine the linkage between malaria and economic growth. Using a classification rule analysis, we confirm the dominant role of climate in accounting for cross-country differences in malaria morbidity. The data, however, do not suggest that tropical location is destiny: controlling for climate, we find that access to rural healthcare and income equality influence malaria morbidity. In a cross-section growth framework, we find a significant negative association between higher malaria morbidity and the growth rate of GDP per capita which is robust to a number of modifications, including controlling for reverse causation. The estimated absolute growth impact of malaria differs sharply across countries; it exceeds a quarter percent per annum in a quarter of the sample countries. Most of these are located in Sub-Saharan Africa (with an estimated average annual growth reduction of 0.55 percent).
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 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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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