Early Lessons of COVID-19 for Governance of the North American Great Lakes and the Baltic Sea
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
The commitment to advance the protection of the North American Great Lakes and the Baltic Sea continues during the COVID-19 pandemic. The resilience of the research community was displayed as policy decisions were made for the first virtual conferences this year to share scientific findings and expertise in both regions. As this pandemic continues to challenge the world, countries have responded to the threat and continue to deal with the uncertainties of this wicked transboundary problem in many different ways. This article discusses key governance and policy issues that have been revealed thus far that can inform the governance of the transboundary North American Great Lakes and the Baltic Sea. Key lessons from the pandemic include waiting for total scientific certainty to act can lead to fatal consequences and our symbiotic connection with nature. Further insights from the pandemic include the importance of context, science-based leadership, institutional accountability, and acknowledging that nature knows no borders.
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 | 0.001 |
| 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 it