Online Religion and Religion Online: Reform Judaism and Web-Based Communication
Bibliographic record
Abstract
This study examines the online communication practices of American congregations associated with the Union for Reform Judaism (URJ), the governing body of American and Canadian Reform congregations, through a content analysis of 252 American URJ congregational Web sites. Web site content was grouped into two categories, “religion online” and “online religion.” Religion online content promotes the organization and provides organizational information, including information related to organizational identity building, community outreach, and encouraging civic and social action. Online religion content allows the user to engage in spiritual activity via the Internet (Helland, 2000 Helland, C. (2000). Religion online/online religion and virtual communitas. In J. Hadden & D. Cowan (Eds.), Religion on the Internet: Research prospects and promises (pp. 205–224). New York, NY: Elsevier Science. [Google Scholar]; Farrell, 2011 Farrell, J. (2011). The divine online: Civic organizing, identity building, and Internet fluency among different religious groups. Journal of Media & Religion, 10, 73–90. doi:10.1080/15348423.2011.572438.[Taylor & Francis Online] , [Google Scholar]). ANOVA and MANOVA analyses were used to determine significant differences in content based on congregation size. Results revealed larger congregations were more likely to use Web sites for organizational identity building, mobilization of civic and social action, and the practice of “online religion,” lending support to the existence of a size-based digital divide among URJ congregations.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".