Bibliographic record
Abstract
Abstract The photographic image has been a loyal companion to environmental movements far and wide, yet a closer look at the contemporaneous appearance of photography and industrialism complicates that dependence. This article examines contemporary artistic representations of postindustrial landscapes through their entanglement with the history and materiality of photography. Drawing on elemental media theory as well as the history of science, it traces two key moments in the history of photography through two material components: bitumen and uranium. By suggesting the visual and the material as integrated concepts, the article probes a double materiality—that of the landscape and its deterioration as a result of chemical production or mining, and that of the image itself. The analysis is anchored in concrete sites where photographic materialities are made and unmade: Canada’s Athabasca tar sands region, through Warren Cariou’s photographic series Petrographs (2014–); the former uranium mining territories of Gessenwiese and Kanigsberg, as seen in Susanne Kriemann’s long-term project P(ech) B(lende) (2014–19); and a chemically contaminated lake that served as a wastewater deposit for a film factory, as depicted in Alexandra Navratil’s video Silbersee (2015). These projects question photography’s geochemical origins and its attendant labor and exhaustion, and they come to serve a renewed aesthetics in contemporary postindustrial landscape imagery that grapples with the medium’s own contradictions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".