Bibliographic record
Abstract
Abstract Invented in 1989 and popularly accessible since the mid-1990s, the World Wide Web has always hosted a wide variety of religious content, ranging from early text-based discussion forums to live-stream video, and from rudimentary online communities to cross-platform social media activism. Known colloquially as “religion in cyberspace,” these computer-mediated, faith-based environments raise important questions in terms of how religious discourse is enacted and religious ritual performed. More than that, they challenge whether the notion of physical place will remain paramount in religious life, or if it can be displaced as believers and adherents shift aspects of their activity to electronically mediated communication space. Although initial enthusiasm for the Internet and its presumed potential led some scholars to predict large-scale uploading of religious life, there are a number of reasons to conclude that offline religious practice will continue to be important in the lives of believers despite any online activity they may pursue. That said, there are also significant ways in which online religious activity has encouraged adherents to reimagine the nature of sacred space, to envision new ways of understanding religious practice, and to enact new forms of religious community.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 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".