Planetary health: Creating rapid impact assessment tools
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
Addressing current environmental, social, health, and democratic challenges requires projects and evaluations to be conceptualized differently. This article proposes a pathway to creating rapid impact assessment tools that consider the dimensions that matter the most to ensure positive impacts for a thriving future. This work is based on three premises for evaluation practice, which needs to: contribute to a positive ecosystem, adopt a holistic perspective, and engage participants in deliberative and democratic practices. We first review related evaluation approaches—health impact and environmental impact assessments—to learn from these experiences and avoid their pitfalls. Second, we present and illustrate how the Planetary Health Rapid Impact Assessment tools can be developed and used. This article, is intended to inspire and support policymakers, program designers, decision-makers, administrators, and evaluators willing to positively influence planetary health and introduce such tools in their projects.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
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