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Record W1513680697 · doi:10.1080/00083968.2015.1031147

Retour sur les catégorisations ethno-linguistiques au Soudan: entre construction allogène, appropriation autochtone et perpétuel réajustement

2015· article· fr· W1513680697 on OpenAlexvenueno aff
Catherine Miller

Bibliographic record

VenueCanadian Journal of African Studies / Revue canadienne des études africaines · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesContext (archaeology)AppropriationSociologyEthnologyColonialismPolitical sciencePhilosophyHistoryLinguistics

Abstract

fetched live from OpenAlex

This article concerns the resilience of the ethno-linguistic categories in Sudan and analyses the role played by the linguistic classifications established by modern comparative linguistics. As well as a somewhat conventional review of the ethno-linguistic classifications seen as “colonial inventions” by postcolonial studies, it calls for a contextualised analysis of the development of these categories and in particular of their use and socio-political impact from the colonial period to today in a context where the widespread competition for access to power and resources is being settled to a great extent by the possibility of being recognised as an autonomous ethnic entity.

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)0.006
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0090.027
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.100
GPT teacher head0.302
Teacher spread0.202 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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