Beyond Fortress Conservation: Postcards of Biodiversity and Justice
Bibliographic record
Abstract
Since the late nineteenth century, visual culture has played an active role in naturalizing fortress conservation—a colonial model that began with the founding of Yellowstone National Park in 1872 and still shapes biodiversity and land policies around the world. Just as fortress conservation created a sharp divide between wilderness and human society, visual images—historically and today—traffic in tropes of untouched land to disavow Indigenous presence and to marginalize other ways of protecting nature. For the 2022 Venice Biennale, we worked together to create an exhibit of twenty-two postcards reflecting on the global legacies of fortress conservation. Even though our project is grounded in a critique of visual culture, we also believe that critique is not enough. The postcards document actual practices on the ground to show surprising, everyday examples of contemporary conservation. Challenging conventional myths, the photographs and accompanying texts layer history and critique with stories of sustenance and survival. For this essay, we share some examples from the show and also extend our analysis to connect the postcards to broader narratives of environmental history and visual culture. Ranging from the American West to the transnational Arctic and India, we trace connections across vast distances and explain how grassroots visual culture offers vistas beyond fortress conservation.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".