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Record W4387639983 · doi:10.1177/13540688231205533

Liberalism and illiberalism in Myanmar’s National League for Democracy

2023· article· en· W4387639983 on OpenAlexaff
Roman David, Aung Kaung Myat, Ian Holliday

Bibliographic record

VenueParty Politics · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsMcGill University
FundersLingnan University
KeywordsOpposition (politics)DemocracyParliamentDemocratizationLeaguePolitical scienceLiberalismPolitical economyPoliticsLiberal democracyPublic administrationLawSociology

Abstract

fetched live from OpenAlex

The National League for Democracy (NLD) was largely synonymous with Myanmar’s semi-democratic intermezzo in 2016–21. For 2 years after the military coup in 2021, it resumed the role of major opposition party performed from 1988 to 2015. Although it was dissolved by the military junta in 2023, it remains a dominant political force inside the country. This article examines the commitment of NLD leaders and voters to liberal agendas. It reviews existing literature, draws on our dataset of Facebook posts by NLD members of parliament, analyses our 2017 survey, and triangulates it with 2020 World Values Survey data. It argues that the NLD was a relatively liberal force in Myanmar’s democratisation in the 2010s, though its liberal commitments were coupled with rising illiberal values. It is thus possible that even if the NLD were reconstituted and re-elected under a future democratic settlement, that democracy would not be liberal.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

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 studies0.0030.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.059
GPT teacher head0.364
Teacher spread0.305 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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