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Record W3152448999 · doi:10.14666/2194-7759-10-1-001

Proof positive? Testing the universal basic income as a post-covid new normal: The cases of the baltic and canada

2021· article· en· W3152448999 on OpenAlexaffabout
Tatjana Muravska, Denis Dyomkin

Bibliographic record

VenueRePEc: Research Papers in Economics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsBasic incomePolitical scienceSolidarityWorkfarePovertyWelfare stateDevelopment economicsSocial protectionGovernment (linguistics)State (computer science)Safety netHuman rightsSocial securityCoronavirus disease 2019 (COVID-19)Political economyEconomic growthPublic administrationSociologyWelfareLawEconomicsPolitics

Abstract

fetched live from OpenAlex

The global response to the coronavirus has highlighted gaping holes in the social security net. Resultantly, the unconditional basic income (UBI) idea has gained traction worldwide throughout 2020, both among the public and politicians looking for solutions to address poverty and stimulate economic recovery. The shift from viewing the UBI as a utopia towards recognizing it as an internationally acceptable policy requires further exploration. By comparing the pandemic-sparked interventionist policies on both sides of the Atlantic, the paper analyses the de facto introduction of the UBI in socially progressive countries, taking Canada and the Baltics as test cases. The authors conclude that the global crisis, exposing the alarming state of affairs of social security, has reopened an intense debate over the role of government interventions and the scope of the welfare state and paved the way for reforms that would embrace better state funding, with an emphasis on social solidarity.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.499

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0220.019
Scholarly communication0.0080.003
Open science0.0030.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.034
GPT teacher head0.318
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicSocial Policy and Reform StudiesFrench-language works237,207