Pandemonium of Hope: Oil, Aspiration, and the Good Life in Alberta
Bibliographic record
Abstract
For people living in Alberta, Canada’s largest oil producing province, oil is a key symbolic element in imagining what a good life is. A Pandemonium of Hope explores how oil companies, government agencies, and community organizations in Alberta use oil to describe a specific set of morals and values. In Alberta, labour, land, and aspiration are bound by a world in which religious meaning making and ideas of the good life are entangled with oil. Oil culture shapes how both the past and the future of Alberta are imagined. This dissertation discusses how oil and the good life are bound through the four case studies: Imperial Oil’s description of its own virtue in its public relations, narratively aligning itself with the Christian colonial project of settlement in western Canada; spaces that the Alberta government calls “Energy Heritage” sites and how they have used historical narratives of extraction to articulate Albertan values; the corporate culture of Calgary and its philosophies about energy; and The Calgary Stampede rodeo as a culminating spectacle in which the goodness associated with oil labour, extractive land use, and assertive aspiration is articulated as specifically ‘western.’
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 | 0.002 |
| Science and technology studies | 0.025 | 0.019 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".