Participatory and Collaborative Modeling of Sustainable Systems: A Systematic Review
Bibliographic record
Abstract
Sustainability has become a key characteristic of modern systems. Unfortunately, the convoluted nature of sustainability limits its understanding and hinders the design of sustainable systems. Thus, cooperation among a diverse set of stakeholders is paramount to sound sustainability-related decisions. Collaborative modeling has demonstrated benefits in facilitating cooperation between technical experts in engineering problems; but fails to include non-technical stakeholders in the modeling endeavor. In contrast, participatory modeling excels in facilitating high-level modeling among a diverse set of stakeholders, often of non-technical profiles; but fails to generate actionable engineering models. To instigate a convergence between the two disciplines, we systematically survey the field of collaborative and participatory modeling for sustainable systems. By analyzing 24 primary studies (published until June 2024), we identify common challenges, cooperation models, modeling formalisms and tools; and recommend future avenues of research.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".