Distinguishing Ritual from Theatre
Bibliographic record
Abstract
This paper begins by analyzing Richard Schechner’s distinguishing features of ritual and theatrical performances, specifically regarding audience participation, audience belief, and intention of the performance to determine if these are truly accurate predictors of ritual and theatre. Specifically, the question of “belief” is raised. The ways in which audiences suspend disbelief in different types of performances is questioned and alternative ways of approaching (dis)belief in performance theory are proposed. Schechner’s efficacy/entertainment theory is updated using affect theory and performative utterances, thereby bringing emotional immediacy and authenticity into Schechner’s model. Building from the emotional significance of different performance types, this thesis posits that the lasting effects of ritual and theatre differ due to the disparity between the respective emotional affects of ritual and theatre performances. The research suggests that in some cases, ritual performance has the power to indoctrinate audiences that theatrical performance usually does not. The Eight Model Plays of Cultural Revolution China and City Christian Church Toronto’s baptism and Sunday service rituals serve as case studies through which this expanded theory of performance is tested.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".