Socioecological System Transformation: Lessons from COVID-19
Bibliographic record
Abstract
Environmentalists have long warned of a coming shock to the system. COVID-19 exposed fragility in the system and has the potential to result in radical social change. With socioeconomic interruptions cascading through tightly intertwined economic, social, environmental, and political systems, many are not working to find the opportunities for change. Prefigurative politics in communities have demonstrated rapid and successful responses to the pandemic. These successes, and others throughout history, demonstrate that prefigurative politics are important for response to crisis. Given the failure of mainstream environmentalism, we use systemic transformation literature to suggest novel strategies to strengthen cooperative prefigurative politics. In this paper, we look at ways in which COVID-19 shock is leveraged in local and global economic contexts. We also explore how the pandemic has exposed paradoxes of global connectivity and interdependence. While responses shed light on potential lessons for ecological sustainability governance, COVID-19 has also demonstrated the importance of local resilience strategies. We use local manufacturing as an example of a possible localized, yet globally connected, resilience strategy and explore some preliminary data that highlight possible tradeoffs of economic contraction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".