Technologies of Quiescence: Measuring Biodiversity, “Intactness,” and Extractive Industry in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Debates over the environmental costs of industrial resource extraction in Alberta, Canada—home to a petrochemical industry that plays an outsize economic and political role—are reaching a fever pitch in response to government regulations on industry, data on climate change threats, and social movements pushing for environmental protection. Away from the news headlines, scientists are developing new metrics and models to calculate biodiversity loss and other outcomes of industrial environmental contamination. But these data are not only used to provide evidence of environmental harm. Practitioners of settler science like the Alberta Biodiversity Monitoring Institute employ such data in combination with the metaphor of environmental “intactness,” generating colonial mythologies of terra nullius anew, and enabling industrial extraction to continue. This paper theorizes a technology of settler colonial concealment. It shows how settler technologies of quiescence operate through the strategic use of scientific metrics, thereby concealing evidence of colonial harm and promoting a fiction of environmental “intactness” in a province that is home to one of the most environmentally destructive industries in the world.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it