Integrated modeling of nature’s role in human well-being: A research agenda
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
• Integrated models can assess effects of ecosystem services on the global economy. • Insights from integrated models can improve management for sustainable development. • To be most useful, models need to link ecological impacts and human well-being. • Key advances include better incorporation of equity and social-ecological feedbacks. Integrated assessment models that incorporate biodiversity and ecosystem services could be an important tool for improving our understanding of interconnected social-economic-ecological systems, and for analyzing how policy alternatives can shift future trajectories towards more sustainable development. Despite recent scientific and technological advances, key gaps remain in the scientific community’s ability to deliver information to decision-makers at the pace and scale needed to address sustainability challenges. We identify five research frontiers for integrated social-economic-ecological modeling (primarily focused on terrestrial systems) to incorporate biodiversity and ecosystem services: 1) downscaling impacts of direct and indirect drivers on ecosystems; 2) incorporating feedbacks in ecosystems; 3) linking ecological impacts to human well-being, 4) disaggregating outcomes for distributional equity considerations, and 5) incorporating dynamic feedbacks of ecosystem services on the social-economic system. We discuss progress and challenges along each of these five frontiers and the science-policy linkages needed to move new research and information into action.
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) | 0.002 | 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