Bibliographic record
Abstract
Canada is one of the world’s largest petrostates, owing to large shale oil deposits, also known as tar sands, which can be found within its borders. In recent decades, as the price of crude oil has increased dramatically, corporations and the Canadian state have worked together to open the oil deposits in Northern Canada for extraction and transportation. Despite a stated commitment to environmental sustainability by the United States and Canadian governments, both have endorsed tar sands extraction and transport. Government and corporate entities have tried to reframe tar sands as “ethical oil,” yet all steps in the process involved pose tremendous ecological, social, economic, and cultural threats to First Nations communities in Canada, landowners in the Midwest and Texas, local ecosystems, and the global climate. This practice is part of a long-standing pattern of appropriating and using public and First Nations land for economic development. We argue that tar sands production on First Nations land is a practice of resource colonialism: the theft and appropriation of land belonging to indigenous people in order to access natural resources. By branding tar sands as “ethical oil” and labeling production companies as “sustainable,” the public and private sectors bound up in the extractive economy claim to provide an essential public service while misdirecting attention away from acts of colonialism that make these resources available. In this article, we examine the ways in which corporate and state entities use the discourse of sustainability as a cover for continued resource colonialism.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.037 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".