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Record W4308404212 · doi:10.1515/ijsl-2022-0042

“In the Middle East, it’s cool to ‘Sing Moroccan’”: ideologies of slang and contested meanings of Arabic popular music on social media

2022· article· en· W4308404212 on OpenAlexaff
Atiqa Hachimi

Bibliographic record

VenueInternational Journal of the Sociology of Language · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsSlangCommodificationIdeologySociologyMusicalPopular musicGender studiesLinguisticsLiteraturePoliticsPolitical scienceLawArt

Abstract

fetched live from OpenAlex

Abstract Against the background of the marginalization of North African in relation to Middle Eastern Arabic vernaculars, this paper considers the ways in which popular music has propelled the commodification of Moroccan Arabic and made it a site of deep contestation. It centers on a controversial love song written and performed in Moroccan Arabic by Middle Eastern musicians, specifically their use of sātˁa , a derogatory youth slang term for “girl.” Drawing on in-depth stance-taking analysis of Moroccans’ digital metapragmatic discourse, it argues that metapragmatic debates position some Moroccan musical genres as authentic and some speakers and places as illegitimate representatives of the nation, thus enregistering certain ways of speaking with deviant social types and musical genres. This study has broader implications for the resignification of historically marginalized linguistic varieties in a more globally connected world, including the tensions this creates between the commodification of language and local constructions of sociocultural authenticity and legitimacy.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.033
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0010.000
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 head0.156
GPT teacher head0.430
Teacher spread0.275 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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