Bibliographic record
Abstract
"Curator Meryl Ryan brought together the works of nine contemporary Australian artists including Dr Lisa Anderson, Jorg Schmeisser and Alison Lester to address the Arctic and Antarctic through personal experience of place. Cold Front was held in conjunction with an exhibition of photographs by Frank Hurley and Herbert Ponting whose seminal images of Antarctica can be found in every public photography collection. Cold Front added knowledge of both Antarctica and the Arctic through new, contemporary renderings. Duxbury reflected on climate change and its effects, extending her earlier explorations with new media. Her three pieces addressed the Artic through a variety of media with the titles Lost (for) Words, a theme which could be interpreted in a number of ways - to represent her experience of the Arctic as 'a place that was so stunningly beautiful it left me Lost for Words'; to relate to the effects of climate change (which leave us speechless) and to the indigenous population - the Inuit of Baffin Island - with whom she stayed for 4 days, finding their language incomprehensible. The Romanised text, based on Pitman shorthand, includes few vowels but many letters used rarely in English - k, q and j. Duxbury was aware that global warming might leave them without snow, for which they have 24 words, and these words would become redundant. 'Loss of words equals loss of culture'. Duxbury had not created wax tablets previously and used a shelf with its associations, being left on a shelf, redundant, unwanted, out-of-date. She used paraffin wax, which is derived from petroleum, the very material that is causing climate change and the ice to melt.<br />The text in, Lost (for) Words-account, is a palimpsest of historical narratives of the difficulties of penetrating the ice of the North-West Passage. The single words in each frame that have 'melted' from the surrounding voices spell out nostalgia for the ice and snow. Over 4,500 people saw the exhibition."<br />
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".