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Record W3110782924 · doi:10.1177/1866802x20975036

Are They All the Same? The Distribution of Personal Wealth Between the Left and the Right in Latin America

2020· article· en· W3110782924 on OpenAlexafffund
Nordin Lazreg, Alejandro Ángel, Denis Saint‐Martin

Bibliographic record

VenueJournal of Politics in Latin America · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Society in Latin America
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLatin AmericansIdeologyPoliticsPosition (finance)Distribution (mathematics)Left and rightPolitical economyPolitical scienceSocial capitalSociologyDevelopment economicsEconomicsLawFinance

Abstract

fetched live from OpenAlex

Conventional wisdom indicates that politicians in Latin America are all wealthy. However, the literature on both political elites and social origins of political parties indicates that we should expect differences in the capital accumulation of politicians depending on their ideological position. This study seeks to explore that question using financial disclosure forms made available in six Latin American countries: Argentina, Bolivia, Brazil, Chile, Peru, and the Dominican Republic. We calculate the median wealth of the main political parties in each country and compared them according to their ideological position on the left–right continuum. We consistently find that the most right-leaning party in each country had a higher median wealth than the most left-leaning one. This relation is non-linear since centrist parties often represent anomalies in the distribution of wealth. When there are no ideological differences, we do not observe significant wealth differences either.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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