167“In the Tar Sands – Going Down”: Literary Responses to the Canadian Oil Industry
Bibliographic record
Abstract
Since 1992, when Amitav Ghosh lamented the absence of literary responses to the oil industry and its impact on the environment, the situation has radically changed. In addition to the rich body of petro-literature that has emerged in the past 25 years, petrocriticism has now developed into a distinct field within ecocriticism, as the numerous publications and conferences engaged with literary reflections of the oil industry testify. In Canada, where the Athabasca Oil/Tar Sands in Alberta are one of the largest fracking sites worldwide, the pervasiveness of the oil business and society’s dependence on it have become a particularly prominent theme in literature and the arts. Agreeing with ecocritics like Evi Zemanek and David Kerridge that different genres can perform different tasks, my essay will focus on the rich generic landscape of Canadian petro-literature, including not only the novel, poetry and drama, but also the short story and the graphic novel. I shall first provide a more general introduction to forms and facets of Canadian petro-literature and then focus, in more detail, on selected examples to demonstrate their distinct aesthetic and ecocritical potential.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.064 | 0.035 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 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".