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Record W3207879926 · doi:10.7202/1082059ar

Lost in Translation? Bill 21, International Human Rights, and the Margin of Appreciation

2021· article· en· W3207879926 on OpenAlexvenueaboutno aff
Frédéric Megret

Bibliographic record

VenueMcGill Law Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsMargin of appreciationHuman rightsJurisprudenceContext (archaeology)LawMargin (machine learning)Political scienceInvocationLaw and economicsSociologyFundamental rightsHistory

Abstract

fetched live from OpenAlex

The adoption of Bill 21, which bans religious symbols for civil servants in Quebec, has stirred considerable debate politically and constitutionally in the province and in the rest of Canada. Neglected, however, has been a more in-depth analysis of how international human rights law often serves as an implicit frame of reference for many of the debates surrounding Bill 21. This essay focuses, in particular, on the invocation of the case law of the European Court of Human Rights, which seems to have validated bans of religious symbols in various contexts. It gives an overview of that jurisprudence and specifies the parameters within which it operates, emphasizing the complexity of translating a supranational case law into a domestic debate. It argues that whilst Quebec is less alone in banning religious symbols than is sometimes argued, the European case law needs to be handled carefully. In particular, the essay emphasizes the importance of the so-called “margin of appreciation” as heavily impacting the outcome in those cases. Although the margin suggests that there is national leeway in adopting bans based on certain national traditions and specificities, it hardly opens the door to all bans. Rather, the margin emphasizes the significance of divergences between states parties on an issue and respect for procedural safeguards. The essay concludes with some thoughts on how importing human rights arguments out of context can be perilous, but also about how the margin itself may be problematic.

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 score0.986
Threshold uncertainty score0.999

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 head0.025
GPT teacher head0.302
Teacher spread0.277 · 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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueMcGill Law JournalSame topicAmerican Constitutional Law and PoliticsFrench-language works237,207