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Record W4280488324 · doi:10.4324/9780429292927

North American Muslim Women Artists Talk Back

2022· book· en· W4280488324 on OpenAlexaboutno aff
Kenza Oumlil

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicHispanic-African Historical Relations
Canadian institutionsnot available
Fundersnot available
KeywordsArtHistoryGender studiesSociology

Abstract

fetched live from OpenAlex

This book focuses on the ways in which North American Muslim women artists "talk back" to dominant discourses about Muslim identity and work to counter mainstream stereotypes and representations. It examines the possibilities of constructing discourses of resistance to domination. Against a backdrop of dominant media representations of oppressed and passive Muslim women, the media interventions of the exceptional women artists whose voices are showcased in this book, demonstrate that Muslim women are diverse and autonomous agents who have, historically, and continue contemporarily, to fight against all forms of injustice including those that seek to circumscribe their realities and experiences. To explore expressions and articulations of alternative discourses, this book analyzes the media texts of exceptional women artists: the stand-up comedy of Palestinian-American Maysoon Zayid, the cinematic interventions of Iranian-American Shirin Neshat, and the television comedy of Pakistani-Canadian Zarqa Nawaz. Using a methodology consisting of a textual analysis grounded in the theoretical framework of postcolonial theory and informed by gender studies and alternative media research, the analysis is supplemented with semi-structured interviews with the artists. This book is suitable for scholars and students in Gender Studies, Media Studies, Cultural Studies, Sociology, and Politics.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2780.007

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 head0.198
Teacher spread0.177 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

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