Bibliographic record
Abstract
University as a freshman in September 1939, the same month that Canada went to war against Hitler's Germany.At first no one knew what to call the war.Between 1914 and 1918 Elizabeth's parents' generation had participated in what was known as "The Great War."As Elizabeth notes here, her generation came to know the conflicts as World War I and World War II.World War II finally ended in 1945 with the defeat of Germany and its principal ally, Imperial Japan.Wars are strange, surreal times in the affairs of nations.For some, usually soldiers but often civilians, they are characterized by fighting, destruction, death, and misery, as well as service and heroism.Behind the lines, (everyone who resided in North America during the world wars was effectively shielded from fighting and bombing) life went on.Children laughed in their mothers' arms; boys and girls danced and dated; dads went off to work; weekends were spent at the cottage; and on campus, the literature students read their Shakespeare and Jane Austen and argued about Plato and Socrates.The fighting was a long way away, to be read about in the newspapers, heard about on the radio, viewed in gritty black and white newsreels at the cinema.In the first eight months of World War II, Elizabeth's first year at McGill, there wasn't even all that much fighting, just the defeat of Poland, a nasty war in Finland, skirmishes on the sea and in the air.It all got serious in April 1940 when Hitler unleashed his blitzkrieg assault on Western Europe.The fall of France, Dunkirk, the Battle of Britain, the invasion of Russia, Pearl Harbour: by the time Elizabeth transferred from McGill to the University of Toronto in 1942, there was no doubt that Canada was involved in what came to be called "total" war.By the end of it more than one million Canadians had served in the Canadian army, navy, and air force.About half of the country's gross national product had been diverted to the war effort.Much had changed about life on the home front, including the awful
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.618 | 0.414 |
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".