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Record W1985925077 · doi:10.3138/gsi.8.1.04

The Nuba People: Out of Sight, Out of Mind

2014· article· en· W1985925077 on OpenAlexvenueno aff
Rebecca Tinsley

Bibliographic record

VenueGenocide Studies International · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsIndictmentGenocideHuman rightsPower (physics)LawIslamPolitical sciencePunishment (psychology)International communityTreatyHistoryPolitics

Abstract

fetched live from OpenAlex

Despite the improved international architecture for the prediction, prevention, and punishment of mass atrocities since the Rwandan Genocide 20 years ago, the fate of Sudan’s Nuba people has been overlooked. Since May 2011, the Nuba have been under attack by the Sudanese regime, which has been using the same tactics it employed to devastating effect during the 1990s. However, problematic Arab-Islamic views of the Nuba go back centuries, to the slave trade. The international community’s attention to continuing human rights abuses in the Nuba Mountains has been inconsistent and easily deflected onto low-level hostilities between South Sudan and Sudan. Meanwhile, Sudan has rallied regional leaders, defying the International Criminal Court’s indictment of President al-Bashir. The United States and United Kingdom, guarantors of the 2005 Comprehensive Peace Agreement (CPA), have declined to press Khartoum to fulfill its obligations under the CPA, to enact constitutional reform, or to cease bombing the Nuba for fear that a Sudanese Arab Spring might bring unknown actors to power in Khartoum.

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)0.002
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0150.014
Scholarly communication0.0070.013
Open science0.0010.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0060.001

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 head0.028
GPT teacher head0.352
Teacher spread0.323 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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