COVID-19 and Re-Globalization: What Can We Foresee?
Bibliographic record
Abstract
The coronavirus outbreak has shown how interdependent and interconnected the world is. A virus that originated in Wuhan, China continues to spread to nearly every country. Two weeks after the detection of the first coronavirus case in Wuhan, coronavirus cases appeared across multiple continents, depicting the rapid spread of the virus due to the rise of globalization. In less than three weeks, the virus spread across multiple continents, traveling to Europe, Thailand, Japan, South Korea, the United States, and Canada. G20 leaders, in a virtual meeting, noted in their statement, “The virus respects no borders. Combatting this pandemic calls for a transparent, robust, coordinated, large-scale, and science-based global response in the spirit of solidarity.” Which is right. Addressing and mitigating the outbreak requires a comprehensive international response.
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.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.064 | 0.027 |
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".