Bibliographic record
Abstract
This talk reports on a performance of the planetarium event Singing the stars with sculptures, which was performed at the H.R. Macmillan Planetarium in Vancouver and the Seneca College Planetarium in Ontario. Subsequent performances were done at the Art Gallery of Ontario, P.S.1, New York City, the 10th International Sculpture Conference, Toronto, and The National Gallery of Canada. It was reviewed in the Village Voice, Arts Canada, The New Art Examiner, Vanguard Magazine, and CBC Radio: Out of the belly of Vancouver’s H.R. Macmillan Planetarium, the star-making machine rises to the star chamber, carrying three musicians with their instruments, and three sculptures. Atop each sculpture is an overhanging frame of five wooden bars, which acts as a musical score. Lights go down over the planetarium audience. Stars move across the sky. Only the constellations and the luminous bars atop the sculptures are visible. Swept up by the grandeur of the constellations, the musicians look up through the bars atop their sculptures and give a concert playing the stars. The concert is inspired by a story from my book, Singing the Stars. A village of people has lost the power of night, which once resided within them. The people attempt to lure the night back with the help of sculptures, which will enable them to play and sing the stars. They hope that, lured by the music, the night will come close to their faces, and bits of darkness will fall into their ears, eyes and mouths and gradually fill up their bodies with the night sky.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.292 | 0.139 |
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".