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Record W2172756335 · doi:10.19030/iber.v12i5.7822

The Relationship Between Economic Freedom And Income Equality In The United States

2013· article· en· W2172756335 on OpenAlexaboutno aff
Allen L. Webster

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic freedomSocioeconomic statusEconomic inequalityAutonomyInequalityDistribution (mathematics)SovereigntyIndex of Economic FreedomEconomicsIncome distributionState (computer science)Development economicsDemographic economicsIndex (typography)Political scienceEconomic growthSociologyLawDemographyPopulationPolitics

Abstract

fetched live from OpenAlex

While considerable research in the past has focused on the socioeconomic impact of economic freedom on economic growth among nations, less emphasis has been devoted to the relationship between economic sovereignty and income equality. This is particularly true when the area of focus has been restricted to comparisons among states within the United States. Furthermore, what work has been offered comparing US states has proven to be contradictory. Certain studies reviewed in this paper suggest that higher measures of economic freedom are associated with greater income inequality. On the other hand, evidence exists that less inequality is found in areas with greater economic autonomy. This study uses the Gini Index as measures of income distribution. The Fraser Institute in Vancouver, Canada offers well-respected measures of economic freedom among the US states and the provinces of Canada. These data are used to further examine relationships between state levels of economic freedom and income distribution with the intent to offer some general consensus regarding this all-important association.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.165
GPT teacher head0.419
Teacher spread0.255 · 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 teacher head, not a consensus.

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

Citations12
Published2013
Admission routes1
Has abstractyes

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