Bibliographic record
Abstract
How does an international award-winning photographer and documentary-maker help us understand our transfigured planet? Edward Burtynsky charts his own trajectory, from exploring the Canadian wilderness as a child, to his development as an artist responding to the last century's explosion of industry and technology, which has resulted in immense disruption to our planet. Almost every landscape on earth is now scarred and manipulated by our insatiable appetite for progress. Across the course of more than four decades, Burtynsky has used his images, taken on vast geological scales, to both document and question the effects our rapid and widespread changes have on our collective home. His career has mirrored our concerns. In the 1980s, he captured landscapes rendered bare through the extractive processes of industrialization – mines, quarries and railways. In the 1990s, he documented the unseen and forgotten end-product of our consumption: abandoned cities of waste, metal, plastic and tires – the detritus of modernity. As we passed a new millennium the focus shifted from photographing vast oil-fields and refineries to our manipulation and depletion of water. As we continue through the Anthropocene – an era defined by our destruction and engineering of Earth's natural resources and processes – the author continues to believe in the power of images as poetry and narrative. Such images force us to confront our role in a world buckling under the weight of our economic and consumptive overdrive.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.181 | 0.114 |
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".