Operation Desert, Windsor, Ontario
Bibliographic record
Abstract
Build Me Up/Tear Me Down: Provisional Structures and Contested Zones includes the work of twelve international and Canadian artists who examine the city as a constantly changing arena of architectural and social activity. Buildings seem so permanent that we often forget that they are really temporary structures, held together by social, political, and cultural activities. \n \nFrom photographs of trailers by Windsor-based photographer Brenda Francis Pelkey to the breathtaking image of the World Trade Centre disaster by New York artist Carolee Schneemann, this exhibition provides a range of perspectives on the ephemeral nature of the built environment. Several artists, including Vienna-based Sabine Bitter and Helmut Weber and Helge Mooshammer and Peter Mörtenböck from the UK, came to Windsor earlier in the year to create new work about our region. Other artists, including William Christenberry, who is from Washington D.C., and the mysterious Object Orange, a Detroit collective, photograph abandoned buildings in various states of decay. Botto and Bruno, from Turin, Italy, and Vancouver’s Jayce Salloum, examine the provisional structures of street culture, disaffected youth, and the homeless.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.424 | 0.098 |
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".