Bibliographic record
Abstract
BACKGROUND In 2010 Williams gave a keynote for Changing the Climate: Utopia, Dystopia and Catastophe at Monash University, which led her to ask why science fiction was so successful in film and literature, but was under-represented in the visual arts. This became one of two major research questions informing this exhibition, the other being to counter superstitious narratives (especially prevalent on the web) on the year 2102 by asking how artists envisage the world in 100 years. Research involved an international search for artists not illustrating literary ideas but working through the language of the visual arts to speculate on visions of the future. It became clear that most artists are pessimistic, especially in relation to climate change, hence a subsidiary theme of the research became an investigation of how art could convey resilient, though not necessarily utopian, images of the future and thereby enable reflection and debate across a number of sectors. CONTRIBUTION Art that conveys effective ideas about the future, like the best science fiction, is really an art about the conditions of the present and their unforeseen consequences. In researching this exhibition Williams found most artists had a fairly dystopian perspective of the future, making it difficult to find utopian views. She sees this as not about a pessimistic attitude, but rather that dystopian imagery forms a critique of the conditions of the present. SIGNIFICANCE The exhibition included 43 artworks from 24 artists from Australia, the USA, Germany, France, Canada and Japan as well as an innovative installation of 17 works by major architects speculating on the future of cities. A substantial catalogue with essays by Andrew Milner, Jane Mullett and Linda Williams was published by RMIT Galley, Australian Institute of Architects and the Japan Foundation [ISBN 9780980771022]. The show was widely reviewed (e.g. ABC Radio National Future Tense 15 Dec 2011; The Age 14 Jan 2012 and ArchitectureAU).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".