Bibliographic record
Abstract
This poster will focus on the participatory play Revelations by Toronto-based theatre creators Anahita Dehbonehie, Griffin McInnes and Aidan Morishita-Miki presented as part of Kingston’s Kick & Push Festival in the summer of 2020. The show used game mechanics to have us prepare for the apocalypse- but not the one we were living in the height of the COVID-19 pandemic, but the potential future nuclear apocalypse. The first half of the show involves the audience communicating with the other groups who are all isolated in their own households via walkie-talkie. The audience then came together in a park downtown to determine who would win the game and “survive” the apocalypse by escaping via boat, car, or on foot (ultimately decided by the roll of dice). At its core, this show asked what we value more, the individual or the collective. This is a piece of participatory theatre and participation is, by definition, not something you can do alone. And yet when we look at the inspiration for this show we see so much individualism. Doomsday preppers create bunkers for themselves and their loved ones, preparing for the day when a natural disaster, economic collapse, or nuclear war means that it’s everyone for themselves. In its sim, Revelations asks us to confront our own approach to the end of the world; it offers us valuable lessons in collective care that can be applied easily to our real world.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".