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Record W4414478289 · doi:10.3390/languages10100246

Stylizing Tamazight (Berber)-Influenced Moroccan Arabic in a Moroccan Stand-Up Comedy

2025· article· en· W4414478289 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguages · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Linguistics, Cultural Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStylized factRepertoireContext (archaeology)ArabicComedyOrder (exchange)Expression (computer science)

Abstract

fetched live from OpenAlex

Elaborating on the concept of heteroglossic stylization, this paper examines how a Moroccan comedian—Zakaria Ouarssam—stylizes Tamazight (Berber)-influenced Moroccan Arabic (MA) in order to evoke comedic personae associated with the country’s Middle Atlas region. Our analysis focuses on Ouarssam’s on-stage performances to document the complex multilingual repertoire that allows him to (i) create contrasts between a supposedly unmarked MA and a stylized Tamazight-influenced MA and (ii) evoke comedic stances that associate the latter with stereotypes of his home region. Particular attention is given to Ouarssam’s use of code switching between Tamazight-influenced MA and untranslated Tamazight as a novel and potentially boundary-pushing practice when considered in the context of its live performance on national television. The paper argues that Ouarssam’s stylized performances contribute to the construction and valorization of an alternative expression of Amazigh and regional pride, even as they reproduce certain linguistic hierarchies and ideologies.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.268
Teacher spread0.257 · 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