Bibliographic record
Abstract
Democratic countries implemented measures that a few months before were unimaginable » he health crisis that humanity is currently going through must not prevent us from thinking about how we want and how we are going to come out of it.Undoubtedly, despite the very serious sacrifices this pandemic will demand of all of us, humanity will survive.But how?What are we ready to sacrifice to overcome it?This article will deal with recent authoritarian, populist, and democratic forms of government that have been emerging and how they have been strengthened or weakened as a result of the present state of emergency. The authoritarian form in the time of the pandemicSince before the outbreak of the current pandemic, two contrasting models were being offered to global society: the democratic model and the authoritarian one, exemplified by China, which has been rapidly developing its economy, expanding its infrastructure, upgrading its industry to reach high technological standards, lifting 600 millions of its inhabitants out of poverty, and ensuring that the emerging new middle-class can access the comforts of the developed world.The leaders and partisans of this model claim that democracy and individual freedom, as we know it in the West, would jeopardize the state's ability to continue this impressive process.The majority of the Chinese population accepts this premise: democracy and individual rights can wait, and in exchange, their countrythat was poor until recentlydevelops at surprising speed.The values that are at the base of democratic societies could be delayed in exchange for strong economic development.Some disagreed with this premise: the youth of Tx
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".