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Record W2007916882 · doi:10.1353/dss.2005.0052

When the Killers Go Home: Local Justice in Rwanda

2005· article· en· W2007916882 on OpenAlexaboutno aff
Phil Clark

Bibliographic record

VenueDissent · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeSociologyCriminologyLawPolitical science

Abstract

fetched live from OpenAlex

The international community ignored the 1994 genocide in Rwanda, when nearly one million Tutsi and moderate Hutu were macheted to death, many by their own friends and neighbors, and it was almost entirely absent on the most momentous day in Rwanda since the genocide. Two Western media agencies, BBC Radio and the Canadian television network CTV, together provided a total of three and a half minutes' coverage when, on May 5, 2003, more than twenty thousand confessed genocide perpetrators were provisionally released into their hometowns, after spending nearly a decade in prison. I had expected to fight my way through hordes of journalists to talk to the detainees before they boarded buses, returning to the same communities where they committed their crimes. Instead, I walked unimpeded into the Kinyinya "solidarity camp" on the outskirts of Kigali, one of eighteen civic education centers around Rwanda, where, for three months between leaving prison and being released into the community, around a thousand confessed génocidaires received instruction from government officials on how to be good citizens in the post-genocide society.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0260.006
Scholarly communication0.0050.004
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.021
GPT teacher head0.293
Teacher spread0.272 · 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 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

Citations16
Published2005
Admission routes1
Has abstractyes

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