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Record W4231848657 · doi:10.1093/jcs/cst142

Notes on Church-State Affairs

2014· article· en· W4231848657 on OpenAlexaboutno aff
D. W. Hendon, J. Hines

Bibliographic record

VenueJournal of Church and State · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)LawPolitical scienceJudaismIslamShariaInheritance (genetic algorithm)Government (linguistics)PopulationGenocideThe HolocaustSociologyHistoryDemography

Abstract

fetched live from OpenAlex

Muslims and Jews protested an advertisement critical of halal and kosher slaughter of animals, which was emailed to approximately two hundred legislators. Jewish critics were particularly offended by the use of references to the Holocaust, which they said amounted to the trivialization of genocide. The Sultan of Brunei said that a new Sharia Penal Code will come into effect in stages starting in April. Sharia courts mainly deal with marriage and inheritance and only apply to the 70 percent of the population that is Muslim. Canada announced plans to give $1.2 million to promote religious liberty. Of that, $553,643 will go to promote dialogue and conflict mediation in Jos, Nigeria, and other parts of Nigeria's Plateau State, which has seen violence between Muslims and Christians, and $672,000 will go to train government officials and community leaders in Eastern Europe, Central Asia, and the South Caucasus. The Coalition Avenir Québec, the third largest party in Quebec, announced its support for a ban on religious symbols in the public sector, something that is already supported by the Parti Québécois. If approved, the policy would allow crosses, yarmulkes, and turbans for lesser officials but not for high-ranking ones.

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.088
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0880.015

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 head0.288
Teacher spread0.271 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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