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Record W3130824996 · doi:10.1002/j.cyo2.20201401.0001

Slamming the “Continuing” Moroccan Revolution: Noussayba Lahlou's Bittersweet Verses

2020· article· en· W3130824996 on OpenAlexaff
Maha Tazi

Bibliographic record

VenueCyberOrient · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicNorth African History and Literature
Canadian institutionsConcordia University
Fundersnot available
KeywordsResistance (ecology)PoetryPoliticsEconomic JusticeLanguage changeGender studiesOfficerLawPolitical scienceSociologyLiteratureArt

Abstract

fetched live from OpenAlex

Abstract In this article, I am interested in looking at women's current mobilization techniques in Post-Arab Spring North Africa. To do so, I draw from the existing literature on the case of Egypt which identifies women's contemporary resistance in creative disobedience patterns – that is women's art activism that advocates, concomitantly, for social justice and gender equality. In my attempt to fill an existing gap in the literature, I investigate the existence of such resistance patterns in Morocco, as well as their main characteristics and country specificities. Because (slam) poetry is a traditionally resistant genre in the Arab region, I take as a case study Noussayba Lahlou's slam poetry to explore the political potential of women's slams to advocate for women's rights and sociopolitical liberties in post-Arab Spring Morocco. To do so, I conducted a virtual interview with the artist by administering a structured online questionnaire, alongside a content analysis of eight of her most recent and salient slams. A 24-years-old slam poet from Morocco, Noussayba's revolutionary verses tackle widespread regime abuse and corruption, alongside women's rights and many other social woes in the country.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score1.000

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)0.0010.000

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 head0.020
GPT teacher head0.177
Teacher spread0.157 · 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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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