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Record W1973576501 · doi:10.1016/j.polsoc.2008.07.001

“We All Know A Democracy When We See One”: (Neo)liberal orthodoxy in the ‘democratisation’ and ‘good governance’ project

2008· article· en· W1973576501 on OpenAlexaff
Alison J. Ayers

Bibliographic record

VenuePolicy and Society · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsSimon Fraser University
FundersNational Endowment for DemocracyStyrelsen för Internationellt UtvecklingssamarbeteUnited States Agency for International Development
KeywordsDemocratizationDemocracyOrthodoxyPolitical economyPolitical scienceLiberal democracyDemocracy promotionSociologyCorporate governancePublic administrationPoliticsLawEconomics

Abstract

fetched live from OpenAlex

Abstract ‘Democratisation’ and ‘good governance’ have come to constitute a fundamental aspect of Western interventions in Latin America, Asia, Africa and the former Eastern bloc, particularly in the post-Cold War period. Despite a vast literature on ‘democratisation,’ there has been a paucity of analysis which interrogates the great-power-defined agendas of democratisation. The naturalism of a particular vision or model of democracy is such that its promotion is rarely questioned or critically interrogated. Yet democracy is an essentially contested concept and universalistic claims around the Western (neo)liberal notion of democracy are being increasingly challenged. The article interrogates therefore the notion(s) of democracy articulated by the dominant social agents associated with the democratisation project, through specific reference to Africa. It contends that an orthodox notion can be identified. The orthodoxy constitutes a (neo)liberal, procedural notion of democracy, a claim substantiated through interrogation of the orthodoxy and the detailing of the extent to which the orthodox notion is informed by (neo)liberal theory and practice. The article concludes that ‘democratisation’ and ‘governance’ interventions are to be understood as a current manifestation of the liberal project.

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 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 score0.665
Threshold uncertainty score0.987

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 studies0.0010.001
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 head0.066
GPT teacher head0.338
Teacher spread0.271 · 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.

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

Citations22
Published2008
Admission routes1
Has abstractyes

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