Impermanence and Entropy: Collaborative Efforts Installing Contemporary Art
Bibliographic record
Abstract
Contemporary art exhibitions Increasingly include artworks that vary in size and weight, are ephemeral in nature, organic in expression, sometimes deceptively frail, purposefully disorganized, or obsessively detailed. The ways in which curators, conservators, registrars, and exhibition designers are engaging in active collaboration with artists to realize complex conceptual installations are illuminated in these case studies from Tempo, an exhibition organized by The Museum of Modern Art in 2002. This article discusses how the museum's standards of exhibition preparation and installation, as well as conservation treatments and maintenance, were adapted. A simple shipment of material introduced a need to understand international trade law; ubiquitous technology provided a crash course on consumer-driven obsolescence; and the artist's intent, as well as notions of authorship, inspired inquiry into the relationship between the museum and the artist. Despite long-standing tradition in approaches to installation planning and display, The Museum of Modern Art staff embraced the challenges and recognized the effectiveness of working collaboratively.
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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".