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Record W2247685015

The Impact of Authoritarian Rule on the Success of Global City Branding Efforts: Dubai, Singapore, and Mumbai

2013· article· en· W2247685015 on OpenAlexvenueno aff
Abigail Struxness

Bibliographic record

VenueSound Ideas (University of Puget Sound) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsAuthoritarianismCompetitor analysisGovernment (linguistics)GlobalizationAppealPolitical economyNeoliberalism (international relations)PoliticsState (computer science)Competition (biology)Face (sociological concept)Political scienceBusinessEconomyMarket economyEconomicsDemocracySociologyMarketingLaw
DOInot available

Abstract

fetched live from OpenAlex

With forces of globalization and a neoliberal commitment to open markets, cities in the developing world face increased competition with each other and implement branding to differentiate themselves from their competitors. City brands must appeal to tourists, investors, and residents alike, simultaneously demonstrating that the city is modern enough to be integrated into the global economy, but culturally unique enough to stand apart from rival cities. This thesis investigates how city governments use branding to communicate their commitment to neoliberal principles and their desire to become a respected global city. Using the case studies of Dubai, Singapore, and Mumbai, I find that an authoritarian government can effectively implement cohesive branding to convince the rest of the world that theirs is a true global city. This is because authoritarian governments have the consolidated control necessary to swiftly and effectively implement specific aspects of neoliberal policy favorable to a global city image. These findings contribute to a larger political economy debate regarding the most effective implementation of political institutions to promote economic development, suggesting that a strong state government is necessary in implementing comprehensive policy changes.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.277
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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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