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Universal Basic Income: The Political Economic Aspect

2019· article· en· W3002491385 on OpenAlexaboutno aff

Bibliographic record

VenueEconomic Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBasic incomeBasic needsPoliticsGovernment (linguistics)EconomicsWelfare stateWelfarePublic economicsLabour economicsEconomic growthPolitical sciencePovertyMarket economyLaw

Abstract

fetched live from OpenAlex

The idea of universal basic income first emerged in the Late Middle Ages. In the second half of the 20th century, it began to be actively discussed as a political al become very popular. In a number of countries, such as Canada, Finland and the Netherlands, local experiments involving basic income have been taking place. This article addresses the main arguments for and against basic income. Some authors regard basic income as a populist and paternalist policy, which is an incorrect judgment, as its adequate implementation could lead to budgetary savings, reduce the size of government, and lower state interference in the lives of citizens. Another objection is that basic income would discourage labor and stimulate social dependency; however, local experiments in partial introduction of basic income and similar benefits have not confirmed this statement. The claim that basic income is too expensive of a measure does not consider that it is supposed to replace numerous other social benefits and would therefore most likely result in reduced administrative costs. Basic income is a social welfare measure most compatible with the nature of labor and the labor market under the technological revolution that has begun, where labor has been getting increasingly distributed and aimed at the workers’ self-realization rather than their survival. In practice, basic income is to be implemented gradually, only covering selected groups of individuals at first and expanding the range of recipients over time. In basic income administration, a certain role can be played by municipal governments.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.015
Scholarly communication0.0040.006
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.307
Teacher spread0.293 · 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 designTheoretical or conceptual
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

Citations4
Published2019
Admission routes1
Has abstractyes

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