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Record W2732200314

States of Violence: Ethnicity, Politics, and Pastoral Conflict in East Africa

2016· article· en· W2732200314 on OpenAlexaff
John G. Galaty

Bibliographic record

VenueGeographical research forum/Geography research forum · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsGrievancePastoralismEthnic groupEthnic conflictPoliticsArgument (complex analysis)State (computer science)LegitimacyPolitical scienceEthnic violencePolitical economySettlement (finance)Customary landCompetition (biology)Development economicsSociologyGeographyLand tenureLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

Focusing on cases of strife in pastoral regions of Kenya, this paper examines the relative emphasis that should be given to the endogenous dynamics of ethnicity and resource competition or the exogenous influences of the state in stimulating local conflict. Despite strong historical continuity in the definition of ethnic fronts of grievance and friction, the institutional framework for the exercise of local jorce, and the immediate factors that trigger conflicts, the paper suggests that ethnic and community-level dynamics today are framed, constrained, and engendered by the predicaments of legitimacy and power faced by the contemporary African state, especially in its problematic relation to regions and the cultural diversity they represent. Based on three cases of pastoral conflict (land conflicts, ethnic displacement, and raiding) in Kenya, the argument is made that pastoralists are involved most in conflict as ethnic actors when their interests are conjoined with the politics of patronage. When insecurity of the state and local pastoralists is diminished, collaboration in managing local rights and resources will increase.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.345
Teacher spread0.293 · 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.

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

Citations5
Published2016
Admission routes1
Has abstractyes

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