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Record W1534560257 · doi:10.1177/186810341403300302

The Limits and Potential of Liberal Democratisation in Southeast Asia

2014· article· en· W1534560257 on OpenAlexaff
Sorpong Peou

Bibliographic record

VenueJournal of Current Southeast Asian Affairs · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDemocratizationAuthoritarianismDictatorshipSoutheast asiaDemocracyPolitical economyPoliticsPolitical scienceRegime changeState (computer science)Political changeDevelopment economicsSociologyEconomicsLawEthnology

Abstract

fetched live from OpenAlex

This article argues that Southeast Asia is a region where uneven political development presents a theoretical challenge to the study of regime change and continuity in the academic field of comparative politics. Of the 11 political regimes, only Timor-Leste, the Philippines, and Indonesia can now be considered liberally democratic. However, these democracies are far from consolidated. The other eight regimes range from soft dictatorships to electoral authoritarian regimes and illiberal democracies. This article seeks to explain why no single theory adequately explains regime change and continuity in this region. Impediments to democratisation are many – one of which is the fact that traditional and undemocratic institutions remain strong and that transitions to civilian rule remain vulnerable to other powerful state institutions, most notably the armed forces.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.015
Scholarly communication0.0060.004
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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 designNot applicable
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

Citations26
Published2014
Admission routes1
Has abstractyes

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