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Record W4255388684 · doi:10.1093/jcs/csu098

Notes on Church-State Affairs

2014· article· en· W4255388684 on OpenAlexaboutno aff
D. W. Hendon, B. Norton

Bibliographic record

VenueJournal of Church and State · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)ClassicsLibrary sciencePolitical scienceArtComputer scienceAlgorithm

Abstract

fetched live from OpenAlex

St. Mark's Anglican Church in Melbourne became the first Anglican church to apologize to the Lesbian, Gay, Bisexual and Transgender (LGBT) community for past hurts caused by church teachings. Anthony Venn-Brown, a Christian gay activist, spoke and accepted the apology. He said that, while it did not right all past wrongs, it did represent “the potential for healing and reconciliation” within the Anglican community. Deputy Prime Minister Sok An and U.S. diplomat Jeff Dingle participated in a ceremony marking the return of three Hindu statues to the Koh Ker Temple in Siem Reap Province. The statues had been looted during the Cambodian civil war and wound up in the United States, but the auction houses Sotheby's and Christie's and the Norton Simon Museum of California returned them as a gesture of goodwill. The National Assembly of Quebec passed a law legalizing euthanasia for the terminally ill. The law says that a person of sound mind who is experiencing unbearable physical and psychological pain can request a lethal injection. The status of the law, however, is unclear since the federal government creates the criminal code and that code bans euthanasia. The Quebec law does not use the term euthanasia and instead refers to “medical aid to the dying.” Other places that have legalized euthanasia are the Netherlands, Belgium, and Luxembourg.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.184
Threshold uncertainty score0.615

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0100.001
Scholarly communication0.0050.003
Open science0.0020.004
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.1840.041

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 head0.315
Teacher spread0.298 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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