“At War with Commercial Entertainment Mediocrity”: Interview with High Performance Rodeo Founder and Curator Michael Green
Bibliographic record
Abstract
Michael Green: Well, the more I think about it, the more it seems to me that it was born of frustration, really. In our [One Yellow Rabbit’s] third or fourth year or whenever it was that we did the first festival, we had just been thrown out of the third theatre — the third facility — that we had upgraded ourselves to be able to have an audience come and see a show. The first place was the back space at the Off Centre Centre gallery, which is where One Yellow Rabbit was born — that and [Calgary nightclub] Ten Foot Henry’s. Then, we had graduated from there — they were losing the space, the building was being sold — and so we had to find another place. The second place [the ION Centre] was an old auto repair garage on the 17th Avenue, and we shared that place with [performer] David Cassel’s companies for about a year or two anyway. We had a falling out with David Cassel, so we decided to take ourselves elsewhere and then we found another place. It was the second — no, it was the third floor of a building that’s still there and it’s called the SkyRoom. It’s a club, but it was called the SkyRoom during the prohibition. It was a booze can, and so there was a beautiful hardwood floor and amazing recessed details in the plaster ceiling. So we did our best to bring it back to maybe what it might have looked like and then started doing theatre in there.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.037 | 0.016 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.023 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".