Bibliographic record
Abstract
At the beginning of the last century, no city on the continent was growing faster or was more aggressive than Winnipeg. No year in the city’s history epitomized this energy more that 1912, when Winnipeg was on the crest of a period of unprecedented prosperity. In just forty years, it had grown from a village on the banks of the Red River to become the third largest city in Canada. In the previous decade alone, its population had tripled to nearly 170,000 and it now dominated the economy and society of western Canada. As Canada’s most cosmopolitan and ethnically diverse centre, with most of its population under the age of forty, it was also the country’s liveliest city, full of bustle and optimism. In Winnipeg 1912 Jim Blanchard guides readers on a tour through this golden year when, as the Chicago Tribune proclaimed, “all roads lead to Winnipeg.” Beginning early New Year’s Day, as the city’s high society rang in 1912 at the Royal Alexandra Hotel, he visits the public and private side of the “Chicago of the North.” He looks into the opulent mansions of the city’s new elite and into its political backrooms, as well as into the crowded homes of Winnipeg’s immigrant North End. From the excited crowds at the summer Exhibition to the turbulent floor of the Grain Exchange, Blanchard gives us a vivid picture of daily life in this fast-paced city of new millionaires and newly arrived immigrants. Richly illustrated with more than seventy period photographs, Winnipeg 1912 captures a time and place that left a lasting impression on Canadian history and culture.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.417 | 0.099 |
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".