Ritual Revision During a Crisis: The Case of Indian Religious Rituals During the COVID-19 Pandemic
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.023 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".