Space-ifesto 2012 (A Manifesto Toward Conditions and the Proliferation of Culture in a BETTER CANADA)
Bibliographic record
Abstract
OCCUPY SPACE ALWAYS START BACKWARDS: (TO BE READ ALOUD) To the civil servant, the city counselor, and MP! To our friends, supporters, benefactors. To the courageous follower (you know who you are!) You are making space for ART: Cheers to you! To the women and men who make space on the fringes for the masses who like Fringes. To the festival organizers, the fundraiser, the arts administrator, WE, THE ARTISTS, Thank you! To the theatre managers who in this day and age might be wishing for a “found space”, To the architects who thought about the city, the people, and what would happen inside, To function first! (with no disrespect to form). To large washrooms, with twice as many stalls for women, To soft lighting that makes you look good, To artists paying artists. Let this never be a bad thing, To designers who deal in magic, To postage stamp size studio spaces, To the agora, where it all began, and to the faithful technician, devoted, sitting watch. THREE CHEERS TO THE THEATRE AND ALL ITS PARTS!! LONG LIVE THE THEATRE!!! Hip Hip, Hurrah! Hip Hip, HURRAH!! Hip Hip, HURRAH!!!
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) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".