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Record W4294946013 · doi:10.1177/14737795211071100

Religious-based discrimination in the commercial context on the basis of sexual orientation: A comparative perspective

2022· article· en· W4294946013 on OpenAlexaboutno aff
Anthony Gray

Bibliographic record

VenueCommon Law World Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtLawJurisdictionStatutory lawSexual orientationContext (archaeology)Political sciencePerspective (graphical)SociologyPosition (finance)EconomicsGender studies

Abstract

fetched live from OpenAlex

This paper considers how three jurisdictions, Canada, the United States and the United Kingdom, have sought to reconcile freedom of religion with equality rights, particularly in the commercial context, and particularly in relation to sexual orientation. The recent decisions of the United Kingdom Supreme Court and United States Supreme Court form the backdrop for that discussion. It is argued that the former made piecemeal, and misleading, use of American case law, and a fuller consideration of that jurisdiction’s position was warranted, and would have led to a different view of the recent American decision. It argues that the United Kingdom Supreme Court was in error in viewing a message on a cake ordered from a baker as an example of the baker's expression, leading it to an incorrect conclusion at odds with statutory mandates in the commercial sphere around refusals of service. Both high court decisions risk undermining progress on the equality front.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0060.018
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.095
GPT teacher head0.398
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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