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Persistence of Civil Wars

2010· article· en· W3122953018 on OpenAlexfundno aff
Daron Acemoğlu

Bibliographic record

VenueCINECA IRIS Institutial Research Information System (University of Genoa) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsnot available
FundersMinistero dell’Istruzione, dell’Università e della RicercaEinaudi Institute for Economics and FinanceCanadian Institute for Advanced ResearchOffice of the Dean for Research, Princeton UniversityNational Science Foundation
KeywordsEconomic rentSpanish Civil WarPersistence (discontinuity)Government (linguistics)Political economyPolitical scienceAction (physics)EconomicsDevelopment economicsLaw and economicsLawMarket economyEngineering

Abstract

fetched live from OpenAlex

A notable feature of post-World War II civil wars is their very long average duration. We provide a theory of the persistence of civil wars. The civilian government can successfully defeat rebellious factions only by creating a relatively strong army. In weakly-institutionalized polities this opens the way for excessive influence or coups by the military. Civilian governments whose rents are largely unaffected by civil wars then choose small and weak armies that are incapable of ending insurrections. Our framework also shows that when civilian governments need to take more decisive action against rebels, they may be forced to build over-sized armies, beyond the size necessary for fighting the insurrection, as a commitment to not reforming the military in the future.

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)0.002
metaresearch head score (Gemma)0.022
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.089
GPT teacher head0.327
Teacher spread0.239 · 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

Citations74
Published2010
Admission routes1
Has abstractyes

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