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Record W4313249675 · doi:10.1111/soc4.13065

Highly religious young Catholics in Northern Ireland: Renewing the Catholic landscape?

2022· article· en· W4313249675 on OpenAlexfundno aff
Gladys Ganiel

Bibliographic record

VenueSociology Compass · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
FundersDurham UniversityQueen's UniversitySt Mary's University
KeywordsReligiosityFaithSociologyNorthern irelandOpenness to experienceGender studiesSocializationSociology of religionEthnologyLawPolitical scienceSocial scienceSocial psychologyTheologyPsychology

Abstract

fetched live from OpenAlex

Abstract This article explores findings from a 2022 survey of students associated with the Catholic Chaplaincy at Queen's University, Belfast. It is the first study to investigate the beliefs, practices, and experiences of highly religious young Catholics in Northern Ireland. It presents survey findings on beliefs, practices, and influences on faith; dynamics of increased religiosity; and views on Church teachings on same sex relationships, euthanasia, sexual relationships, and abortion. Women are more likely to disagree with Church teachings on these issues than men. The survey confirms the importance of family socialization but finds that a substantial minority experience religious change at university. Respondents prioritize renewal but disagree on how to prompt it: some advocate greater ‘openness’ to women, LGBTQ+, and others perceived as marginalized; and others feel ‘evangelization’ should be emphasized. ‘Post‐secular Catholicism’ is used as a foundation for reflections on religious persistence among Northern Ireland's young Catholics, raising questions about their potential role in renewing Ireland's Catholic landscape in light of the synodal process underway in the Church.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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