Modeling Dynamic Systems for Sustainable Development 
Bibliographic record
Abstract
We summarize recent progress in dynamic modeling of nature-society systems to inform efforts towards sustainable development.  Drawing on lessons learned from a series of virtual workshops and a journal Special Feature, we identify and highlight examples of novel methods and advances, focusing on four stages of modeling practice -- defining purpose, selecting components, analyzing interactions, and assessing interventions. We highlight insights for researchers interested in assessing the implementation of system-wide sustainability strategies, with a focus on human well-being as an overarching objective, including methods that incorporate nature-society interactions into sectoral decision-support models, simulating cross-sector connections and differing contexts, and implementing computational and statistical approaches that evaluate decision scenarios under uncertainty. We additionally highlight techniques that can serve to foreground issues of power differentials among actors, including methods that can capture diverse societal actions and their agency, and incorporate different perspectives and normative visions. As a concrete example of the utility of a set of methods and advances from this survey of coupled nature-society systems modeling, we show how advances in computational techniques can be used to assess the degree to which national-scale climate policies in the United States can impact air pollution exposure to different racial/ethnic groups. 
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How this classification was reachedexpand
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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.000 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; a candidate call from one teacher head, not a consensus.
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".