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Record W2107292640 · doi:10.1093/afraf/ads018

The big fish won't fry themselves: Criminal accountability for post-election violence in Kenya

2012· article· en· W2107292640 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.

Bibliographic record

VenueAfrican Affairs · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsSocial Sciences and Humanities Research Council
Fundersnot available
KeywordsAccountabilityTribunalPolitical scienceGovernment (linguistics)ConstitutionLawCriminal justiceEconomic JusticeCriminologySociology

Abstract

fetched live from OpenAlex

This article examines the demand for criminal accountability for the atrocities committed after Kenya's contested December 2007 elections. It explains why, despite strong popular desire for accountability through prosecutions and the threat of and actual International Criminal Court (ICC) involvement, the government has failed to take concrete steps to try those believed primarily responsible. The article argues that the fundamental reason why the government has not initiated systematic prosecutions in regular domestic courts – or created, as promised, a hybrid national/international tribunal – is that those in charge of establishing these processes are, in many cases, those whom it would prosecute or their close allies. A hybrid tribunal now seems unlikely and credible national trials are an improbable alternative, though there are some reasons to be more optimistic following the new constitution of 2010. For the time being only international justice, which is beyond the government's reach, can achieve a breakthrough in criminal accountability, albeit in a very limited way.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.972

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 studies0.0010.000
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 head0.027
GPT teacher head0.306
Teacher spread0.279 · 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