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Record W4231078775 · doi:10.22215/etd/2021-14388

Who Supports Basic Income? Constituency as a Constraint in Political Feasibility Testing

2021· dissertation· en· W4231078775 on OpenAlexaffabout
Patricia Wallinger

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsBasic incomePoliticsPublic economicsIdeologyPropositionPerceptionIncome distributionPublic opinionEconomicsWelfarePolitical sciencePsychologyLawMarket economy

Abstract

fetched live from OpenAlex

With a provincial welfare system in crisis, Basic Income is re-merging as a strategy to guarantee a minimum level of income for everyone, regardless of employment status.According to polls, public opinion on Basic Income in Ontario is almost evenly divided among those supporting it and those rejecting it.From a policymaking perspective, understanding the demand for policy changes is critical in assessing the political feasibility of Basic Income.This research tests the political feasibility of Basic Income by examining soft constraints, specifically, its constituency base.It inquires on the socio-economic characteristics behind public support for Basic Income through the analysis of a survey conducted in 2016.The findings provide insights on the constituency base of Basic Income which proves to have no socio-demographic homogeneity.Instead, perception-and ideology-related variables have been identified as predictors of attitudes towards the Basic Income proposition in Ontario.

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)0.016
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.006
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.052
GPT teacher head0.396
Teacher spread0.344 · 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 designQualitative
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

Citations0
Published2021
Admission routes2
Has abstractyes

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