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Record W2187194306 · doi:10.20495/tak.39.4_584

Armed Rebellion in Collapsed States

2002· article· en· W2187194306 on OpenAlexaff
William Reno

Bibliographic record

VenueTōnan Ajia Kenkyū/Tonan ajia kenkyu · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHIV, TB, and STIs Epidemiology
Canadian institutionsScience North
Fundersnot available
KeywordsIdeologySierra leoneBureaucracyState (computer science)MilitarizationElitePolitical economyPower (physics)InsurgencyPolitical scienceSociologyLawAgrarian societyPoliticsHistoryEthnology

Abstract

fetched live from OpenAlex

Standard theories of insurgency hold that marginalization from centers of power provide insurgents with social space to develop coherent organizational and ideological challenges to authority. Insurgents in recent cases of state collapse, however, do not develop ideological or organizational alternatives. This is due to the particular nature of state collapse, especially where rulers had used informal institutional networks to control populations. As formal bureaucratic institutions collapse, remnants of patronage networks coopt would-be ideological fighters. Strongmen use armed fighters to control fragments of the old patronage economy. This empowers enterprising fighters interested in personal wealth at the expense of ideologues. This dynamic is illustrated with reference to vigilante groups in Nigeria, especially the Bakassi Boys of Anambra State, which initially develop as anti-corruption and antiregime fighters, then become incorporated into the strategies of the politicians whom they fight. The course of internal warfare in Sierra Leone and former Yugoslavia provide further illustration of this process.

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)0.005
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0060.006
Scholarly communication0.0020.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.052
GPT teacher head0.321
Teacher spread0.269 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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