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Record W4241831398 · doi:10.22215/rera.v11i1.253

Neoliberalism and Gender Equality: Canadian Newspapers’ Representations of the Ban of Face Coverings at Citizenship Ceremonies

2017· article· en· W4241831398 on OpenAlexaffvenueabout
Ivana Previsic

Bibliographic record

VenueReview of European and Russian Affairs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCitizenshipOppressionGender studiesNewspaperIdeal (ethics)SociologyNeoliberalism (international relations)Face (sociological concept)InequalityPolitical scienceTolerationLawPoliticsSocial science

Abstract

fetched live from OpenAlex

In late 2011, Canada’s Conservative government banned face coverings for those taking oath at citizenship ceremonies. The ban was unequivocally interpreted by the press to be targeting veil-wearing Muslim women. This paper analyzes newspaper coverage in the month following the announcement of the policy. It argues that most commentators conceptualized citizenship to be a neoliberal tool of rescuing veiled Muslim women from their male oppressors and making them more like the equal/neoliberal “us” and/or as a reward for those who already are or will become equal/neoliberal. Most non-Muslim commentators constructed gender oppression as the reason for which veiled women should (not) become citizens. Gender equality in Canada was represented as a key national value and inequality was erased or minimized and presented as a Muslim problem. In attempting to deflect these arguments, most Muslim commentators silenced gender inequality among Muslims by arguing that veiled Muslim women choose the practice and by relegating gender oppression to Western societies, thereby constructing veiled Muslim women as ideal neoliberal subjects worthy of Canadian citizenship.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.044
GPT teacher head0.314
Teacher spread0.270 · 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 designTheoretical or conceptual
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

Citations1
Published2017
Admission routes3
Has abstractyes

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