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Record W2982351217 · doi:10.1017/glj.2019.77

Solidarity in Diversity? State Responses to Religious Diversity in Liberal and Non-Liberal Perspectives

2019· article· en· W2982351217 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGerman Law Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Freedom and Discrimination
Canadian institutionsnot available
FundersHumboldt-Universität zu BerlinNational University of Singapore
KeywordsSolidarityDiversity (politics)Political scienceSecularismState (computer science)SociologyLiberal democracyLiberalismEnvironmental ethicsLawDemocracyPolitics

Abstract

fetched live from OpenAlex

Abstract This Article introduces the German Law Journal’s Special Issue on “Solidarity in Diversity? State Responses to Religious Diversity in Liberal and Non-Liberal Perspectives”. The major countries in comparative focus are Germany and Singapore, both self-avowedly secular countries that face the challenge of religious diversity: Singapore, from inception, and Germany, through more recent developments. A key issue the Article raises concerns liberal approaches towards regulating religion; it argues that the liberal model, taking Germany as an example, may serve as a productive starting point for comparative analysis, as the liberal focus on individual religious freedom impacts managing religious diversity, shapes national cultural identity, models of secularism and social solidarity. This is compared with non-liberal approaches, as exemplified in Singapore practice, where a more communitarian outlook underpin more interventionist approaches whereby public interests and the common good tend to be prioritized over individual freedom. The comparative angles offered in this Special Issue is furthermore buttressed in several articles in this Special Issue that make comparisons to other jurisdictions-United States and Canada. This introductory Article offers a brief overview to the various contributions to this Special Issue and identifies unifying themes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.965

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.017
GPT teacher head0.298
Teacher spread0.282 · 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