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Record W2979892931 · doi:10.15365/joce.2203032019

Homophobia in Catholic schools: An exploration of teachers’ rights and experiences in Canada and Australia

2019· article· en· W2979892931 on OpenAlexaffabout
Tonya D. Callaghan, Lisa van Leent

Bibliographic record

VenueJournal of Catholic Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLesbianTransgenderGender studiesSociologyHomosexualityQualitative researchBorder crossingHeteronormativityPedagogyPolitical scienceQueerSocial scienceLawPolitics

Abstract

fetched live from OpenAlex

Little is known about the experiences of non-heterosexual educators in Catholic schools. This international comparative analysis reveals previously unreported data from Australian and Canadian qualitative studies that examine the experiences of lesbian, gay, bisexual, transgender and intersex (LGBTI) teachers, and LGBTI Allies from Australia and Canada who are currently teaching or have taught in Catholic schools. Bringing their work together for the first time, the two lead researchers compare their investigations and reveal disheartening similarities with religiously inspired homophobia despite differing legal and policy contexts of the two countries. These two studies reveal that LGBTI teachers, and LGBTI Allies, rely on their personal beliefs and local school community culture and policies to understand their equality rights and this has significant implications for the field of education.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0320.014
Scholarly communication0.0060.003
Open science0.0020.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.351
Teacher spread0.311 · 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 designQualitative
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

Citations14
Published2019
Admission routes2
Has abstractyes

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