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Record W4283750672 · doi:10.1017/s1740355322000195

Giving Up on the Church of England in the Time of Pandemic: Individual Differences in Responses of Non-ministering Members to Online Worship and Offline Services

2022· article· en· W4283750672 on OpenAlexaboutno aff
Andrew Village, Leslie J. Francis

Bibliographic record

VenueJournal of Anglican Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsWorshipCoronavirus disease 2019 (COVID-19)Quarter (Canadian coin)Pandemic2019-20 coronavirus outbreakAdvertisingReligious studiesHistoryPolitical scienceLawMedicineBusinessVirologyPhilosophyInternal medicineArchaeology

Abstract

fetched live from OpenAlex

Abstract This study draws on data provided to the Covid-19 & Church-21 Survey by 826 ‘non-ministering’ Anglicans living in England in order to explore why some people gave up worshipping online or in church during the Covid-19 lockdown in 2021. Nearly a quarter of the participants had given up online worship, attending offline services in church, or both: 15 per cent had given up on online worship, 13 per cent had given up on going to church, and 5 per cent had given up on both. Giving up was significantly correlated with negative experience of services. Those under the age of forty and Anglo-Catholics were most likely to give up online worship. Women and extraverts were most likely to give up on socially distanced services in church. The results indicate the sorts of people who might drift from the church post-pandemic and what the Church could concentrate on to prevent this process.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.134
GPT teacher head0.322
Teacher spread0.188 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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