COVID-19 как вызов политической системе и демократии в России и мире
Bibliographic record
Abstract
The COVID-19 pandemic is unfolding at a time when the political system inherent in the last quarter of the 20th – the first decades of the 21st century, with democracy as the key component, is in decline. According to data compiled by Freedom House, democracy has been in a recession for more than a decade, and more and more citizens in different countries, including recognized leaders of democracy, lose and not get civil and political rights every year. The key problem is that COVID-19 could turn a democratic recession into a depression, which threatens to turn political systems toward authoritarianism, the spread of which around the world can be compared to a modern pandemic. The question arises if autocratic regimes generally are able to take tougher political measures to curb the spread of the virus. If so, are they more effective or China is an exception? This article is written as part of the state task on the topic of the NIR for 2019–2021 «Russian Society before New Challenges: Dynamics of Social and Economic Situation, Value Orientations and Social Participation of Various Population Groups».
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".