Bibliographic record
Abstract
Population-level health interventions are policies or programs that shift the distribution of health risk by addressing the underlying social, economic and environmental conditions. These interventions might be programs or policies designed and developed in the health sector, but they are more likely to be in sectors elsewhere, such as education, housing or employment. Population health intervention research attempts to capture the value and differential effect of these interventions, the processes by which they bring about change and the contexts within which they work best. In health research, unhelpful distinctions maintained in the past between research and evaluation have retarded the development of knowledge and led to patchy evidence about policies and programs. Myths about what can and cannot be achieved within community-level intervention research have similarly held the field back. The pathway forward integrates systematic inquiry approaches from a variety of disciplines.
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.
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 | 0.290 | 0.496 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.020 | 0.029 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".