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Record W4403036520 · doi:10.1080/13510347.2024.2405856

Between the ballot and the bullet: rebel-to-party transformations and the structure of the competitive field

2024· article· en· W4403036520 on OpenAlexafffund
Cheng Xu, Jacques Bertrand

Bibliographic record

VenueDemocratization · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUnited States Institute of Peace
KeywordsBallotPolitical scienceField (mathematics)LawLaw and economicsSociologyPoliticsVoting

Abstract

fetched live from OpenAlex

When rebel groups transition to electoral parties and participate in the democratic process, the prospects of peace are often fragile. We argue that rebel parties’ capacity to effectively participate in the electoral arena and contribute to post-conflict stability is contingent on the nature and legacies of the wartime competitive field. Where rebels and politicians shared claims of representation over their constituents in wartime, we argue that elections-related violence is likely in postwar elections when the rebels transition towards political parties. These former rebel parties challenges established electoral holds of political actors who previously represented the community at the ballot box while collaborating with insurgents. The transformation from wartime allies to direct electoral competition creates new incentives for violence, especially where violence is already normalized. Conversely, where established politicians maintain hegemonic representation of their constituency, they create strong barriers to entry for former insurgents in the electoral realm. As a result, the incentives for violence are much reduced. We analyse the Moro Islamic Liberation Front’s transformation into the United Bangsamoro Justice Party after the Comprehensive Agreement on the Bangsamoro.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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