Bibliographic record
Abstract
When the Calgary Petroleum Products's Dingman No. 1 Well began operation in Turner Valley on May 14, 1914, it unleashed a spectacular frenzy of greed and excess. In a fever of free-market capitalism over 500 oil companies were created, selling fortunes on paper to eager investors. But fewer than fifty ever drilled for oil, and the Alberta oil industry suddenly began to look like one big swindle. The public, and investors, demanded answers. Enter George Edward Buck, a charismatic revival preacher and self-proclaimed oil tycoon who made himself and his company the centre of every conversation while he salted his wells and misled investors. Far from the only person to profit from the sensational publicity of the Turner Valley Boom, Buck became the public face of all unscrupulous businessmen and an international scapegoat to preserve the integrity of Alberta oil. The Boom is a history of the Turner Valley era that rescues the miscreants and charlatans from obscurity. Industry historian Paul Chastko returns the larger-than-life promoters, wildcatters and oil evangelists to the story. He shows the ways that Albertans, determined to overcome the obstacles of economics, geography, geology, and the market, made a conscious choice to pursue petroleum development and created an oil culture that continues to this day.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.013 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.062 | 0.007 |
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".