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Transitional dynamics and the evolution of information transparency: a global analysis

2022· article· en· W4286644012 on OpenAlex
Andrew Williams, Tsun Se Cheong, Michal Wojewodzki

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEstudios de economía · 2022
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
Fundersnot available
KeywordsConvergence (economics)EconomicsQuarter (Canadian coin)Transparency (behavior)Sample (material)Distribution (mathematics)Period (music)SituatedDemographic economicsDeveloping countryDevelopment economicsGeographyEconomic growthPolitical scienceMathematics

Abstract

fetched live from OpenAlex

The last quarter of the 20th century was a period of sustained economic growth across many countries. Countries' institutional arrangements have been commonly employed as factors in the convergence studies of economic growth and income levels. However, the issue of whether institutions themselves converge has been under-researched. Using the nonparametric distribution dynamics approach and a sample of 194 countries during the 1980-2010 period, we examine a tendency for countries' informational transparency (IT) to converge over time. We find that whilst there is some evidence of unconditional convergence across countries, there is stronger evidence for convergence clubs to emerge, at both regional and income levels. Notably, the level of IT of the low-and lowermiddle-income countries and those situated in Africa, and Middle East regions tend to converge towards a level significantly below the global average. We also find a strong relationship between income and IT.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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