Promises and risks of nonstate action in climate and sustainability governance
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
Sustainable Development Goals and the Paris Agreement stand as milestone diplomatic achievements. However, immense discrepancies between political commitments and governmental action remain. Combined national climate commitments fall far short of the Paris Agreement's 1.5/2°C targets. Similar political ambition gaps persist across various areas of sustainable development. Many therefore argue that actions by nonstate actors, such as businesses and investors, cities and regions, and nongovernmental organizations (NGOs), are crucial. These voices have resonated across the United Nations (UN) system, leading to growing recognition, promotion, and mobilization of such actions in ever greater numbers. This article investigates optimistic arguments about nonstate engagement, namely: (a) “the more the better”; (b) “everybody wins”; (c) “everyone does their part”; and (d) “more brings more.” However, these optimistic arguments may not be matched in practice due to governance risks. The current emphasis on quantifiable impacts may lead to the under‐appreciation of variegated social, economic, and environmental impacts. Claims that everybody stands to benefit may easily be contradicted by outcomes that are not in line with priorities and needs in developing countries. Despite the seeming depoliticization of the role of nonstate actors in implementation, actions may still lead to politically contentious outcomes. Finally, nonstate climate and sustainability actions may not be self‐reinforcing but may heavily depend on supporting mechanisms. The article concludes with governance risk‐reduction strategies that can be combined to maximize nonstate potential in sustainable and climate‐resilient transformations. This article is categorized under: Policy and Governance > Multilevel and Transnational Climate Change Governance
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 it