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Record W4388262619 · doi:10.1111/pech.12646

Virtual prayers and real violence: Religion as a resource in challenging times

2023· article· en· W4388262619 on OpenAlexafffund
Michelle LeBaron, Maged Senbel

Bibliographic record

VenuePeace &amp Change · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDynamismPsychological interventionSociologyResource (disambiguation)The artsIntervention (counseling)Coronavirus disease 2019 (COVID-19)EpistemologySocial psychologyPsychologyPolitical scienceComputer scienceLawMedicine

Abstract

fetched live from OpenAlex

Abstract This article examines how to better understand and respond to conflicts with religious dimensions in times of social upheaval. Through different lenses, we highlight the dynamism and multidimensionality of religions, and how conflict transformation scholar/practitioners need to respond. We argue for applying analytical, practical, and arts‐based tools that acknowledge the lived experiences of parties, and the various ways that religion and conflict intertwine. These tools prime analysts and negotiators for imagining a wider range of intervention resources, and for de‐escalating often‐inflammatory media coverage. Using examples of restrictions and reactions related to the COVID‐19 pandemic, we demonstrate the application of an inclusive worldview approach featuring arts tools to improve interventions in conflicts with religious dimensions.

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)0.006
metaresearch head score (Gemma)0.011
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 score0.012
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.035
Scholarly communication0.0120.010
Open science0.0010.016
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.048
GPT teacher head0.327
Teacher spread0.280 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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