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Record W2536733056 · doi:10.1177/0020715216673694

Appropriating democratic discourse in North Africa

2016· article· en· W2536733056 on OpenAlexvenueno aff
Brandon Gorman

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyAppropriationPolityPoliticsPolitical economyIdeologySociologyGlobeState (computer science)Political scienceLawEpistemology

Abstract

fetched live from OpenAlex

Political actors across the globe often use the language of democracy, but they do not all use the same language. Drawing on content analysis of 1935 speeches given between 2000 and 2010, this study examines how five North African autocrats appropriated the global discursive form of democracy by altering its content. These leaders proposed that the special circumstances of each country preclude any one-size-fits-all global definition of democracy, whose imposition in their countries, they claim, would be inappropriate, ineffective, or dangerous. Through their speeches, these rulers redefined democracy by engaging in active ideological work, weaving together discourses that combined global norms, state interests, and local values. This suggests that, in addition to being a benchmark by which to measure modes of governance, ‘democracy’ is also a language game played between actors on a global stage. By synthesizing theoretical frameworks drawn from world polity and social movement studies traditions, this study shows that peripheral actors may adapt global discourses purposefully and strategically rather than encountering them as passive participants in a purely mimetic cultural diffusion process. This has implications for a wide range of global norms that are open to appropriation by local actors drawing on domestic and external political developments and experiences.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.083
GPT teacher head0.424
Teacher spread0.341 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

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