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Record W2734665746 · doi:10.13169/statecrime.6.1.0156

The Pacification of Peru and the Production of a Neoliberal Populist Order

2017· article· en· W2734665746 on OpenAlexaff
Maritza Felices Luna

Bibliographic record

VenueState Crime Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAuthoritarianismNeoliberalism (international relations)Political economyDemocracyPoliticsLanguage changeArticulation (sociology)Order (exchange)Social orderPopulismPolitical scienceState (computer science)Corporate governanceEconomic systemDevelopment economicsSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

This article analyses the security, governance and economic reforms carried out by Fujimori in the 1990s as strategies of pacification seeking to restore a capitalist social order disturbed by the economic and social turmoil of the 1970s and 1980s. First, I show how different forms of state violence were intrinsically connected to the pacification process. Then, I argue that the social order produced resulted from the articulation of populism and authoritarianism with neoliberalism. Subsequently, I contend that crimes, harms and violence continue within the current democratic configuration precisely because pacification is an ongoing process seeking to maintain an order which is intrinsically exploitative, creates favourable conditions for economic crimes and corruption and resorts to repressive violence when challenged. I conclude by suggesting that the social, political and economic landscapes that provided the impetus for pacification have been transformed through the new social order, further weakening already frail democratic institutions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.027
GPT teacher head0.319
Teacher spread0.291 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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