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Record W4200611578 · doi:10.1080/01900692.2021.2003814

Re-democratization in Chile: Is the “New” Democracy Better than the “Old”?

2021· article· en· W4200611578 on OpenAlexaff
Mauricio Olavarría Gambi, Laura Levick

Bibliographic record

VenueInternational Journal of Public Administration · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Society in Latin America
Canadian institutionsSt. Thomas University
FundersUniversidad de Santiago de Chile
KeywordsDemocratizationDemocracyConceptualizationAuthoritarianismLatin AmericansPolitical sciencePositive economicsQuality (philosophy)Political economySociologyDevelopment economicsEconomicsEpistemologyLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

Much of the literature on democratic transitions has focused on the transition from authoritarianism to democracy, but few studies have examined how democracies that re-emerged compare to those that existed in the past. Examining the Chilean case, this study explores the degree to which the “new” democracy has recovered its former strength, posing a similar question for other Latin American countries. It considers the conceptualization of quality of democracy that underpins this controversy and explores the methodological challenges of intertemporal comparison, which may be relevant for other cases that have experienced periods of authoritarian rule and process of re-democratization. We find that, overall, democracy in the contemporary period is more robust. Yet, to an important extent, indices’ different understandings of the concept of the quality of democracy are relevant in terms of the degree to which they emphasize procedural aspects versus democratic outcomes.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.006
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.002
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 head0.027
GPT teacher head0.348
Teacher spread0.321 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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