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Record W4320022507 · doi:10.29327/1172323.6-2

A RELAÇÃO ENTRE AS LIBERDADES POLÍTICA E ECONÔMICA E O PIB REAL PER CAPITA DOS PAÍSES: UM ESTUDO DE CORTE TRANSVERSAL

2022· article· pt· W4320022507 on OpenAlexaff
Arthur Tavares Pacheco, Paulo Rogério Scarano

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsFraser Institute
Fundersnot available
KeywordsTransversal (combinatorics)HumanitiesPolitical scienceWelfare economicsEconomicsMathematicsArt

Abstract

fetched live from OpenAlex

O objetivo do presente trabalho é avaliar em que medida a liberdade econômica e a liberdade política afetam o desempenho econômico dos países.Para tanto, realiza-se uma análise em corte transversal, em que o desempenho econômico é medido pelo PIB per capita em paridade do poder de compra dos países, a liberdade política é mensurada pelo índice Freedom in the World (FiW) da Freedom House (2021) e a liberdade econômica pelo índice Economic Freedom of the World (EFW) do Fraser Institute (2021).Além disso, também se testa os componentes dos referidos índices, desta maneira há a possibilidade de verificar o quanto cada um deles impacta no desempenho econômico dos países.Nesse sentido, os resultados mostram que ambos os índices de liberdades econômica e política podem ser considerados significativos para o desempenho econômico dos países, e que para cada ponto adicional na nota das instituições de liberdade econômica se estima um aumento de até 75% no PIB per capita em paridade do poder de compra, enquanto a liberdade política pode impactar em um aumento de até 0,7% no PIB per capita (em PPP) dos países.Por sua vez, quando testados os componentes dos índices, o item que se revelou estatisticamente significativo foi o sistema legal e os direitos de propriedade.

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)0.002
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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

Citations0
Published2022
Admission routes1
Has abstractno

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