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Record W4406858338 · doi:10.1080/13629387.2024.2392503

The sounds of decolonization: folk music and Arab nationalism in North Africa

2025· article· en· W4406858338 on OpenAlexaboutno aff
Benjamin Jones

Bibliographic record

VenueThe Journal of North African Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismDecolonizationPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

In 1959, the American writer Paul Bowles began an ambitious project to document the folk music of Morocco. At roughly the same time, a Canadian ethnographer named Roxanne Carlisle started her own recording project in newly independent Sudan. Now held at the Library of Congress, the two archives resulting from these projects reflect the intertwined histories of Orientalism, Arabization, and indigenous resistance in the post-colonial period. Far from being the simple documents of folklore which their creators envisioned, they show how music became a key locus in the struggle between local artists at the periphery and officials at the centre to define the nation and its cultural identity. Caught in the middle of this discursive battle, Bowles and Carlisle applied their own Orientalist ideas to the music they encountered, resulting in recordings and representations far removed from the original social context of North African music. Attending to these conflicts around folk and popular music reveals the fraught, sometimes violent, cultural tensions of postcolonial nationalist projects which standard political histories often ignore.

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 score0.036
Threshold uncertainty score0.072

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 studies0.0150.014
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.292
Teacher spread0.256 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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