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Record W2753101445 · doi:10.22215/cjers.v9i2.2490

The Politics of Face Coverings and Masks in Russia, France, and Quebec

2015· article· en· W2753101445 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFeminism, Gender, and Intersectionality
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoliticsFace (sociological concept)PresidencyGovernment (linguistics)Power (physics)Political scienceLawClothingSociologyPolitical economySocial science

Abstract

fetched live from OpenAlex

Since 2004, governments in a number of countries have initiated tense political debates over the question of whether religious symbols should be permitted in public places. Frequently, such debates have focussed on the head and face coverings worn by many observant Muslim women, as has been explored by a rich scholarly literature. However, relatively little has been written about the specific reasons why these laws have been adopted, and few cross-national comparisons have been made. This paper will examine the following cases: first, the law against wearing face coverings in France, adopted during Nicolas Sarkozy’s presidency in 2010; and second, the extensive debates about access to government services for people wearing religious clothing in Québèc (Canada). Finally, the paper will examine the distinct case of Russia, where high court decisions have revealed a reversal in the authorities’ former tolerance of the wearing of head coverings in public places. Three variables help to explain why these laws came upon the political agenda in these admittedly very different countries. First, all three adopted previous measures to limit citizens’ ability to don face coverings during political protests; second, these countries’ choices influenced each other, showing the importance that global influences can play in policy formation; and finally, political leaders attempted to use laws on face and head coverings as a strategy to reinforce their power.
 Full text available at: https://doi.org/10.22215/rera.v9i2.230

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.941

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 head0.059
GPT teacher head0.307
Teacher spread0.247 · 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