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Record W2937499397 · doi:10.5267/j.msl.2019.4.002

Does institutional quality matter in fostering social progress: A cross national examination

2019· article· en· W2937499397 on OpenAlexvenueno aff
Nesrin Almatarneh, Okechukwu Lawerence Emeagwali

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityGross domestic productPer capitaQuality (philosophy)Index (typography)Corporate governanceProduct (mathematics)Social changeEconomic growthPolitical scienceEconomicsDevelopment economicsBusinessSociologyDemographyManagement

Abstract

fetched live from OpenAlex

The first Social Progress Index (SPI) report was released in 2013; a handful of studies examined the determinants of social progress at country level as an instrument in evaluating nation's prosperity. This study focuses on determining the relationship between institutional quality measured by the World Governance Index (WGI) and social progress measured (SPI).The results are based on the secondary data from 107 countries over a four year period (2014-2017), after controlling Gross Domestic Product per capita, innovativeness and trustworthiness. The result was in favor of the fixed effect model. The findings illustrate that institutional quality was consistently significant in fostering social progress. This study is unique in that, it is the first that examined the role of formal institutional quality in promoting social progress at country level by using SPI as a measurement of social progress.

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)0.010
metaresearch head score (Gemma)0.016
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 score0.011
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.266
Teacher spread0.247 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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