Nations Resort to a Redistribution to Rescue the Western Model for the Post-Pandemic World: An EU and Canadian Approach
Bibliographic record
Abstract
The novel coronavirus pandemic has triggered an economic slowdown worldwide, aggravating those steadily accumulated inequalities in income and wealth redistribution. Western-type capitalism, international cooperation, and European integration have found themselves at risk. This article points out the resemblances and dissimilarities in policies combating therecessions of 2008 and 2020 on both sides of the Atlantic, focusing specifically on the EU and Canada. It assesses the rising popularity of the welfarestate concept applied both to individuals and entire businesses deemed essential for democracy, notably in the EU, for which the protection of citizens’ well-being and solidarity values are at the core of bloc integration. Conceptually confl icting solutions for those crises refl ect a profound shift in policy making, reinforcing state interventions vs the neoliberal approach and intensifying discussions on a universal basic income as a tool in redressing socio-economic inequalities. This paper highlights the need for a trans-disciplinary approach to benefi t policy making.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".