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Laissez Fear: Assessing the Impact of Government Involvement in the Economy on Ethnic Violence

2008· article· en· W2097052953 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Studies Quarterly · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsMcGill University
FundersCanada Research Chairs
KeywordsEthnic groupEconomic rentGovernment (linguistics)Competition (biology)EconomicsEthnic conflictEthnic violencePolitical sciencePolitical economyDevelopment economicsMarket economy

Abstract

fetched live from OpenAlex

Does government involvement in the economy promote ethnic peace, or does it contribute to ethnic violence? Two theories, grievances and opportunity, suggest that government involvement in the economy reduces ethnic violence. We present an alternative security-based logic that focuses on the role of economic rents in political competition. Our theory of insecurity predicts that free market economies reduce violent ethnic conflict by reducing fear and insecurity. We present statistical analyses, using data from the Minorities at Risk project and the Index of Economic Freedom, showing that government involvement in the economy increases ethnic rebellion. Our results suggest that the overall size of the public sector is less important than government interference with the market allocation mechanism. We conclude by discussing the policy implications of our findings.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.759
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.103
GPT teacher head0.431
Teacher spread0.328 · 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