(Re)Capturing the Spirit of Ramadan: Techno-Religious Practices in the Time of COVID-19
Bibliographic record
Abstract
Ramadan is an important and blessed month for Muslims around the world. It is both a time of spiritual contemplation as well as an opportunity for reinvigorating communal bonds. The COVID-19 pandemic, however, disrupted many of the rituals and traditions of Ramadan. In this exploratory study, we present findings from 22 young Muslims' experiences with Ramadan and fasting during the pandemic. Our article sheds light on the techno-religious practices and information strategies used to mitigate isolation, share information, and celebrate Ramadan. We examine the sociotechnical configurations of religious rituals and highlight the resilience of these rituals even in the midst of a global pandemic. Our paper contributes to CSCW scholarship on technology appropriation and non-use as they relate to religious practices in the face of exogenous shocks such as the pandemic, and how design can better cater to the religious lives of individuals and communities.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".