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Record W2977879050 · doi:10.1111/spsr.12371

Consociationalism and Centripetalism: Friends or Foes?

2019· article· en· W2977879050 on OpenAlexfundno aff
Matthijs Bogaards

Bibliographic record

VenueSwiss Political Science Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
FundersMcMaster University
KeywordsRepresentation (politics)DemocracyPolitical scienceEthnic groupPolitical economyPower (physics)Power sharingEthnic conflictProportional representationWork (physics)SociologyLawPolitics

Abstract

fetched live from OpenAlex

Abstract Two schools dominate the literature on democracy in divided societies: consociationalism and centripetalism. The first advocates group representation and power sharing while the second recommends institutions that promote multi‐ethnic parties. Although often presented as mutually exclusive choices, in reality many new democracies display a mix. Drawing on the experiences of Bosnia and Herzegovina, Burundi, Fiji, Lebanon, Malaysia, and Northern Ireland, this article examines the empirical and theoretical relationship between centripetalism and consociationalism. The aim is to explore the conditions under which they reinforce each other (friends) or work at cross‐purposes (foes). A better understanding of the interaction between consociational and centripetal elements in post‐conflict societies not only yields a more nuanced picture of institutional dynamics, but also holds lessons for institutional design.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.012
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.371
Teacher spread0.344 · 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 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

Citations53
Published2019
Admission routes1
Has abstractyes

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