Socioecological System Transformation: Lessons from COVID-19
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
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.
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) | 0.005 | 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