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Record W4293772743 · doi:10.5509/2022953475

Democratic Breakdown through Lawfare by Constitutional Courts: The Case of Post- “ Democratic Transition” Thailand

2022· article· en· W4293772743 on OpenAlexvenueno aff
Eugénie Mérieau

Bibliographic record

VenuePacific Affairs · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyDemocratizationPolitical scienceSafeguardingAuthoritarianismPoliticsLawConstitutionConstitutional courtLiberal democracyBureaucracyPopulismState (computer science)Political economySociology

Abstract

fetched live from OpenAlex

Third-wave democracies have massively adopted mechanisms of judicial review, notably constitutional courts, considered key institutions of successful democratic transitions. By preventing abuses of the constitution and safeguarding people's rights, they act as a bulwark against the claims of potential autocrats. In Thailand, the 1997 democratic transition led to the adoption of a powerful constitutional court tasked with safeguarding democracy from the threats of populism, corruption, and authoritarianism. Yet since its inception, the court's record has been puzzling. It has dissolved most, if not all, of the pro-democracy, anti-military political parties, dismissed all elected prime ministers, and paved the way for two military coups. In short, against established theories linking constitutional courts to democratization, the introduction of constitutional review in Thailand has led to democratic breakdown. To make sense of this puzzle, this article will investigate three variables of the court—strategic interests, ideologies, and institutional design—within the larger bureaucratic structure of the Thai state, to account for the anti-democratic behaviour of Thailand's Constitutional Court. This piece considers materials in Thai and English.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.263
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations4
Published2022
Admission routes1
Has abstractyes

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