Bibliographic record
Abstract
Terra is a solo photographic landscape history of Western Australia. At its core is the evidence, demonstrated through a series of photographic narratives, of the destruction of landscape since colonisation as a cultural act (hence the pun in the title). The dead and dying towns, the denuded terrain, the wreckage strewn across that landscape belong to a history that is gormless and ingenuous, brutish and pitiless, surreptitious, dishonest and inevitable. There are two compelling processes available to historians: one is to tell a story that has so far been lost or otherwise hidden. The other is to shift people’s perspectives so that old ways of thinking are discarded. This exhibition employs both. The panoramas explore the deep time of a landscape shaped by ice ages and fluctuating sea levels. The images depict events that indirectly play into the history of destruction, refusing to reveal meaning but implying that even acts of minor significance are inextricable from others that have dramatic repercussions. The works are created with film. Analogue cameras impose limitations upon the photographer, obliging him or her to calculate and compose, but the images can also have a rawness and vitality that digital work cannot achieve. John Toohey is currently a PhD candidate in Art History at Concordia University, Montreal, Canada, where he lived from 2012 to 2018. His thesis examines landscape history through Edwardian postcards. He has an M.A in Art History and an Honours Degree in History. His experience combines photography and landscape and social history, and recently includes the production of audiowalks, engaging listeners, readers and viewers in appreciating the hidden traces of the city around them. Toohey has exhibited and published his photographs in Australia and overseas and his work is held in national collections. His books and articles have had international success. In 2019 he won the Lawrence Wilson Art Writing Prize on Ailsa Lee-Brown’s portrait by Adelaide Perry. His book, Strange Encounters, will be published in the UK in early 2024.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.556 | 0.209 |
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".