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Record W4210557380 · doi:10.1177/07439156221081485

Ritual Revision During a Crisis: The Case of Indian Religious Rituals During the COVID-19 Pandemic

2022· article· en· W4210557380 on OpenAlexaff
Vikram Kapoor, Russell W. Belk, Christina Goulding

Bibliographic record

VenueJournal of Public Policy & Marketing · 2022
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsYork University
Fundersnot available
KeywordsHinduismFaithAgency (philosophy)SociologyCoronavirus disease 2019 (COVID-19)FeelingPandemicAestheticsSocial scienceSocial psychologyPsychologyEpistemologyReligious studies

Abstract

fetched live from OpenAlex

Rituals, particularly religious rituals, may play a significant role in times of crises. Often, these rituals undergo revision to adapt to the changing needs of the time. This article investigates recent unofficially revised Hindu religious rituals as performed during the COVID-19 pandemic. The multifarious creative interplay between Hindu tradition and change is illustrated through four cases: the religious festival of Durga Puja, the devotional songs or bhajans, the ritual of lighting lamps or diyas, and the fire rituals or havans. The authors offer a systematic discourse analysis of online news articles and YouTube posts that illuminate several aspects of ritual revision during unsettled times. They focus on the changes that were made to ritual elements: who controlled these alterations, how these modifications were made, and what potential benefits these revisions offered to the community of ritual participants. The authors highlight public policy implications regarding the involvement of diverse social actors, the creation of faith in science, the creation of feelings of unity and agency, and the amplification of local ritual modifications on a national scale.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.359
Teacher spread0.323 · 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 teacher head, not a consensus.

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

Citations26
Published2022
Admission routes1
Has abstractyes

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