Bibliographic record
Abstract
As already implied by their controversial name, the oil/tar sands in Northern Alberta continue to be a red-hot issue of colossal importance for the Canadian economy. While it is true that the oil industry plays a crucial role in installing the province’s prosperity, the development in Alberta’s far north comes at a high price, including ecological degradation, pollution of waterways, violation of human rights and increasing violence. The industry has found a way to promote and justify the large-scale development in order to be publicly accepted. However, literature, too, has found a voice to raise public awareness about the large-scale development happening in Alberta’s backyard. Exploring the potential of dramatic expression with regard to this conflict-ridden environmental site, this chapter focuses on two contemporary Canadian plays (Hardhats and Stolen Hearts: A Tar Sands Show, Theatre Network; and Highway 63: The Fort Mac Show, Architect Theatre) in which oil workers, waitresses, a Métis man, dancers, businessmen, investors, homeless people and environmentalists of Fort McMurray are given a voice. Representing an explosive mixture of fast money, hard work, masculinity, alienation, superficiality and violence, these protagonists provide a provocative and multi-vocal insight into their everyday, crazy boomtown life. Following the work of Jon Gordon (Unsustainable Oil, 2015), the protagonists’ willingness to accept sacrifices in the name of progress and their struggle between the temptations of fast money and their responsibility for their natural and social environment is given special attention. The chapter highlights the importance of literature in a highly polarised discussion and points at the interrelationship between dramatic forms and (our own) nature.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".