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Record W4390734012 · doi:10.1080/13629387.2023.2221179

Incoherent and strategic: the NIF/NCP minority policies in Sudan

2024· article· en· W4390734012 on OpenAlexafffund
Dalal Daoud

Bibliographic record

VenueThe Journal of North African Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIslamEthnic groupOpposition (politics)IdeologyPolitical sciencePopulationPolitical economyLawMuslim communityPower (physics)Development economicsSociologyPoliticsGeographyDemographyEconomics

Abstract

fetched live from OpenAlex

When the National Islamic Front (NIF) regime came to power in Sudan in1989, the international community was alarmed. Among other things, the treatment of Sudan’s minorities was a chief concern. For instance, in his ten-hour visit to Sudan in 1993, Pope John Paul II warned against imposing Islamic law on the country’s large Christian population. The concerns about the NIF regime’s treatment of minorities were due to its ideological background, since particular interpretations of Islamic law discriminate against minorities. The paper examines the regime’s policies toward the largest ethnic minorities in Sudan. It illustrates that the regime’s treatment of minorities lacked coherence toward both Christian and Muslim ethnic groups. Furthermore, it demonstrates that the regime’s minority policies were the result of shifts in alliances that followed internal divisions within the regime. As the Islamist leadership fractured, the ruling faction sought to coopt new allies, including ethnic groups, to strengthen its position in the face of relentless opposition from ousted Islamists. The paper draws on material collected through fieldwork as well as secondary sources to make its claims.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.965

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 studies0.0000.001
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 head0.084
GPT teacher head0.364
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2024
Admission routes2
Has abstractyes

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