An ecosystem approach to health and its applications to tropical and emerging diseases
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
Disease and health outcomes occur within a complex socio-ecological context characterized by feedback loops across space and time, self-organization, holarchies, and sudden changes in organization when thresholds are reached. Disease control programs, even if they are successful, may undermine health; conversely, programs in agriculture and economic development designed to improve health may simply alter disease patterns. A research and development strategy to promote sustainable health must therefore incorporate multiple scales, multiple perspectives, and high degrees of uncertainty. The ecosystem approach developed by researchers in the Great Lakes Basin meets these criteria. This has implications for community involvement in research, development policies, and for understanding and controlling tropical and emerging diseases. Even if unsuccessful in achieving specific outcome targets, however, the requirements of this approach for open and democratic communication, negotiation, and ecological awareness make its implementation worthwhile.
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 | 0.000 | 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 | 0.000 | 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