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Record W2740215347 · doi:10.1177/0308275x17719988

Cannibal states, empty bellies: Protest, history and political imagination in post-Dayton Bosnia

2017· article· en· W2740215347 on OpenAlexaff
Larisa Kurtović, Azra Hromadžić

Bibliographic record

VenueCritique of Anthropology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicBalkans: History, Politics, Society
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPoliticsSovereigntySociologyPolitical economyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In February 2014, Bosnia-Herzegovina witnessed its largest and most dramatic wave of civic protests since the end of the 1992–1995 war and the signing of Dayton Peace Accords. Confrontations with the police and the destruction of dozens of government buildings subsequently gave way to the formation of plenums – town hall assemblies – where protesters collectively articulated their grievances against the country's corrupt and deeply unpopular political authorities. The plenums emphasized Bosnia's pressing problems of widespread unemployment, rising poverty and corruption, and in so doing sidelined the ossified nationalist rhetoric and identity politics. This article analyzes the main representations of protests, and the sociopolitical and economic pressures that helped usher in this massive public uprising. We demonstrate how protesters sought to break out of the impasses of post-Dayton ethnic politics by actively recuperating and representing alternative visions of participatory politics and popular sovereignty associated with socialist-era imaginaries and embodied in the plenum. We argue that these efforts signal the emergence of a new kind of prefigurative politics that provide alternative practices of political organization, decision-making, and sociability in Bosnia and beyond.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0210.030
Scholarly communication0.0090.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.372
Teacher spread0.348 · 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 designNot applicable
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

Citations62
Published2017
Admission routes1
Has abstractyes

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