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Record W2742191265 · doi:10.1080/02589001.2017.1361016

How Islam intersects ethnicity and social status in the Sahel

2017· article· en· W2742191265 on OpenAlexafffund
Cédric Jourde

Bibliographic record

VenueJournal of Contemporary African Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Studies and Geopolitics
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIslamEthnic groupSolidarityPoliticsCasteSociologyGender studiesPolitical sciencePolitical economyGeographyAnthropologyLaw

Abstract

fetched live from OpenAlex

Groups, movements and political parties that directly invoke Islam as their raison d’être constitute key players in the Sahel. Analysts rightfully take this Islamic dimension quite seriously as they try to understand the dynamics of security in the region. In doing so, however, it is important not to forget other forms of solidarity which intersect with Islam. Ethnicity and social status (‘caste’) are categories that impact in various ways the mobilisation efforts made on behalf of Islam. Drawing examples from Mali, Senegal, Mauritania and Nigeria, this paper presents three configurations in which these identities intersect: representations of untrustworthy ‘ethnic others’; the ethnicization of Islam; and intra-ethnic debates.

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)0.002
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.013
Scholarly communication0.0060.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.119
GPT teacher head0.375
Teacher spread0.255 · 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

Citations11
Published2017
Admission routes2
Has abstractyes

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