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Record W1981742373 · doi:10.1163/187398611x571355

A New-Look for Muslim Women in the Canadian Media: CBC's Little Mosque on the Prairie

2011· article· en· W1981742373 on OpenAlexaboutno aff
Sarah Khan, Mahmoud M. A. Eid

Bibliographic record

VenueMiddle East Journal of Culture and Communication · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsOrientalismIslamMainstreamSociologyMulticulturalismGender studiesFraming (construction)Stereotype (UML)Media studiesIslamophobiaLawHistoryPolitical scienceTheologyPsychologySocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract The coverage of Muslim women in Western media has long been using Orientalist stereotypes and portrayals of Muslims as outsiders. Even though racist stereotypes exist in Canada, Canadian legislation and the media are attempting to portray an idealistic form of multiculturalism. Recently, Canadian mainstream media have refrained from stereotypical representations of Muslims, especially women, and shifted toward non-Orientalist representations. CBC's Little Mosque on the Prairie (LMP), a satirical Canadian comedy sitcom, is one of the first such instances. LMP criticizes and refutes negative stereotypes, portraying Muslims as ordinary Canadians with problems and lifestyles that are shared across Canada. A qualitative and quantitative content analysis of the first season's eight episodes investigates how Muslim women have been portrayed in LMP, drawing on Luhmann's (1987) theory on representation of society, Millar's (1793) observations about women in society, Hall's (1997) Other, Said's (1978) Orientalism, Kristeva's (1991) theories on foreigners, and Bhabha's (1994) Third Space. Findings demonstrate that Muslim women on CBC are not oppressed or stereotyped; instead, they participate normally in Canadian culture and the workplace and are not considered outsiders. Muslim women in Canada exist in Third Spaces that allow Canadian and Islamic practices to merge, resulting in a uniquely Canadian artifact like LMP.

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)0.000
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 score0.366
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.080
GPT teacher head0.283
Teacher spread0.204 · 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

Citations23
Published2011
Admission routes1
Has abstractyes

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