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Record W4211149777 · doi:10.1177/14407833211072566

LGBTQ+ non-discrimination and religious freedom in the context of government-funded faith-based education, social welfare, health care, and aged care

2022· article· en· W4211149777 on OpenAlexaff
Douglas Ezzy, Lori G. Beaman, Angela Dwyer, Bronwyn Fielder, Angus McLeay, Simon Rice, Louise Richardson‐Self

Bibliographic record

VenueJournal of sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsUniversity of Ottawa
FundersAustralian Research Council
KeywordsFaithSociologyDisadvantageGovernment (linguistics)Context (archaeology)Health careSocial WelfareHarmWelfarePoliticsPolitical scienceGender studiesLawPublic administration

Abstract

fetched live from OpenAlex

Anti-discrimination laws around the world have explicitly protected LGBTQ+ people from discrimination with various levels of exceptions for religion. Some conservative religious organisations in Australia are advocating to be allowed to discriminate against LGBTQ+ people in certain organisations they manage. The political debate in Australia has focused on religiously affiliated organisations that provide services in education, social welfare, health care, and aged care. We argue that religious exceptions allowing discrimination should be narrow because they cause considerable harm, reinforce, disadvantage and because LGBTQ+ people are deserving of respect and rights. We draw on a national representative survey to demonstrate that the views of some conservative religious lobby groups do not represent the views of the majority of religious people in Australia or the views of the majority of Christian people.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

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 studies0.0070.010
Scholarly communication0.0030.002
Open science0.0000.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.306
Teacher spread0.292 · 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 designObservational
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

Citations13
Published2022
Admission routes1
Has abstractyes

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