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Record W3166421697 · doi:10.6000/1929-4409.2021.10.124

Power Sharing as a Tool for Resolving Electoral Violence: Revisiting the Zimbabwean Experience

2021· article· en· W3166421697 on OpenAlexvenueno aff
Happy Mathew Tirivangasi, Louis Nyahunda

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsnot available
Fundersnot available
KeywordsAutocracyAuthoritarianismPower sharingMonopolyPower (physics)Opposition (politics)Political economyPolitical sciencePoliticsPosition (finance)DictatorEconomicsSociologyLawDemocracyMarket economy

Abstract

fetched live from OpenAlex

This paper uses Hartzell and Hoddie’s four dimensions of power-sharing to analyse the implementation of the 2008 power-sharing in Zimbabwe and its impact on electoral violence. It interrogates the resolving of the Zimbabwean electoral violence through the use of power-sharing deal between the opposition and the ruling party. The theoretical explanations why electoral violence would occur in a country ruled by an authoritarian leadership suggests that, autocratic governments use electoral violence as a way of influencing the electoral outcome. The other position suggests that the weaker political party is the one responsible for electoral violence as it enjoys the monopoly of being the victim. This study dispels the notion that power-sharing has any impact on resolving electoral violence permanently, we argue that the resolving election dispute through power-sharing does not resolve the differences between warring parties rather, it gives temporary peace. The findings of this study support the position of the electoral authoritarian theoretical perspective that autocratic government will use violence and all the means necessary to ensure that they return the power.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.116
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.065
GPT teacher head0.405
Teacher spread0.340 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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