Bibliographic record
Abstract
For over 130 years, Imperial Oil dominated Canada’s oil industry. From Petrolia to Turner Valley, Imperial was always nearby and ready to take charge. Their 1947 discovery of crude oil in Leduc, Alberta transformed the industry and the country. But from 1899 onwards, two-thirds of the company was owned by an American giant, making Imperial Oil one of the largest foreign-controlled multinationals in Canada. Imperial Standard is the first full-scale history of Imperial Oil. It illuminates Imperial’s longstanding connections to Standard Oil of New Jersey, also known as Exxon Mobil. Although this relationship was often beneficial to Imperial, allowing them access to technology and capital, it also came at a cost. During the energy crises of the 1970s and 80s, Imperial was assailed as the embodiment of foreign control of Canada’s natural resources, and in the 1990s it followed Exxon’s lead in resisting charges that the oil industry contributes to climate change. Graham D. Taylor draws on an extensive collection of primary sources, including both the Imperial Oil and Exxon Mobil archives, to explore the complex relationship between the two companies. This groundbreaking history provides unprecedented insight into one of Canada’s most influential oil companies as well as the industry itself.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.926 | 0.915 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".