An Examination of Virtual Rituals Found in Online Gaming Communities
Bibliographic record
Abstract
learing one's schedule for the day to indulge in well-deserved relaxation or entertainment is neither delinquency or a sin; nor are the myriad of personal retreats into fantasy that people so often employ in order to escape reality and find solace.Virtual multi-user environments operate without halts (barring system or network failures), offering support and capturing the imaginations of a diverse group of users around the world thereby transforming individuals into a community.Virtual communities provide an entirely new type of existence complete with the abilities to build relationships, find employment, raise a family, or even control a universe.Within these worlds, political systems are created (from tyrannies to communes), laws are enforced, economies thrive or fall, individuals may openly join groups or wander alone, and personas develop.What was once considered nothing more than pure fantasy becomes more than a hobby or fascinating pastime; it becomes one's entire life.Although there have been considerations of such issues as the representation of religious values in video-games,1 or prevalent religious imagery and communities found in online multi-user-dungeons,2 there has not yet been sufficient realization of how emergent rituals in online games can be used for detailed religious studies.The emergence of in-game virtual religious rituals exceeds the original program boundaries of most virtual environments.Developed by the end-users and often incorporating religious symbols and styles from a variety of sources, these virtual rituals allow opportunities to study a developing process of expressed ritual style.Due to 1. See "The Values in Video Games."Religion and Ethics Newsweekly.Kim Lawton.PBS.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".