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Record W2761480774 · doi:10.24043/isj.36

State size and democratization in hybrid regimes: the Chinese island cities of Macau and Hong Kong

2017· article· en· W2761480774 on OpenAlexvenueno aff
Ying‐ho Kwong, Mathew Y. H. Wong

Bibliographic record

VenueIsland Studies Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsDemocratizationState (computer science)GeographyCity-stateEconomic geographyPolitical scienceEconomyArchaeologyEconomicsDemocracyComputer sciencePolitics

Abstract

fetched live from OpenAlex

The effect of state size on level of democratization has been a topic of interest to political scientists. However, studies have largely focused on democratic regimes, leaving unexplored the implications of state size for the regime persistence of hybrid regimes. This article compares two Chinese island cities with hybrid regimes through political analysis supplemented by interviews, and argues that a smaller regime is more likely to be authoritarian than a larger one. The case of Macau shows that the very small size of a 'microstate' helps central authorities to exercise political control, stifle political pluralism, and monopolize opinions, all of which strengthen regime persistence. In contrast, the case of Hong Kong shows that a merely 'small state', a larger political entity, creates political polarization, encourages political competition, and diversifies opinions, resulting in a more confrontational state-society relationship. This paper contributes to the literature by examining the effect of state size on regime persistence in hybrid regimes and explaining political development in Macau and Hong Kong from an alternative geopolitical perspective.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.313
Teacher spread0.295 · 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 teacher head, not a consensus.

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

Citations29
Published2017
Admission routes1
Has abstractyes

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