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Record W3091510571 · doi:10.1111/sena.12326

Understanding Power‐Sharing Performance: A Lifecycle Approach

2020· article· en· W3091510571 on OpenAlexaff
Allison McCulloch, Joanne McEvoy

Bibliographic record

VenueStudies in Ethnicity and Nationalism · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsBrandon University
Fundersnot available
KeywordsPower sharingPower (physics)Corporate governanceEthnic groupThrough-the-lens meteringBusinessProcess managementLens (geology)Political scienceEngineeringFinanceLaw

Abstract

fetched live from OpenAlex

Abstract Power‐sharing is a leading institutional strategy for the management of ethnic conflict. Yet its performance is uneven. It often delivers a peace dividend: stopping violence, avoiding minority exclusion, and reducing group‐based insecurity. Its decision‐making efficiency and governance record, however, have weaker evaluations. We conceptualize ‘the power‐sharing lifecycle’ to better understand the reasons for this uneven record. Exploring power‐sharing performance through a lifecycle lens helps illuminate the experiences of – and potential for – power‐sharing in the post‐uprisings Arab world and beyond.

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)0.011
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0030.013
Scholarly communication0.0110.021
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.456
GPT teacher head0.416
Teacher spread0.040 · 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 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

Citations24
Published2020
Admission routes1
Has abstractyes

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