Sedimentology of Composite Sand-and-Gravel Beach-Shoreface Complexes
Bibliographic record
Abstract
The COVID-19 pandemic has given rise to unprecedented and extraordinary conditions. It represents a profound threat to health and political and economic stability globally. It is the pressing issue of the current historical moment and is likely to have far-reaching social and political implications over the next decade. Political psychology can inform our preparedness for the next phase of the pandemic as well as our planning for a post COVID-19 world. We hope that this special issue will play its part in helping us to think how we manage and live with COVID-19 over the coming decade. In this editorial, we review the key themes arising from the contributions to our special issue and, alongside existing knowledge highlight the relevance of political psychology to finding solutions during this time of crisis. The contributions to this special issue and the pandemic raise many classic topics of central interest to political psychology: leadership, solidarity and division, nationalism, equality, racism, and international and intergroup relations. In our editorial, we offer an analysis that highlights three key themes. First, the importance of sociopolitical factors in shaping behavior during this pandemic. Second, the relevance of political leadership and rhetoric to collective efforts to tackle SARS-COV-2. And third, how sociopolitical cohesion and division has become increasingly relevant during this time of threat and crisis.
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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 | 0.000 | 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) | 0.001 | 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".