Souvenir of the dedication of the Brant War Memorial, Thursday, May-twenty-fifth, 1933.
Bibliographic record
Abstract
Record of Participation of Brant County in the World War Killed, died of wounds or Ihrouali service Missing or prisoners Officers -Infantry, Cavalry, Artillery.Engineer, Tanks Medical Officers Royal Air Force Officers Chaplains 701 58 227 24 68 14 ||OUNTY of Brant, including the City of Brantford and Town of Paris, had, in the eventful year 1914, a population of approximately 44,000.During the four years following, from that population, 5.571 donned the khaki of the army or the blue of the navy.Not all of these took the voyage overseas, for some of them did not pass the test after going to the training camps at Valcartier.Niagara, and Borden, but the number who did go to England, and after thorough training, to France, was large, and Brant can well claim to have set a Canadian per capita record in enlistments.Nor was it alone in such enlistments that Brant gloried.From the first of the war to the last.Brant County men were in the thick of the fighting.As British reservists, there were Brant representatives in the retreat from Mons, one of the most heroic fights ever staged by the British army.They were found ready and not wanting when the need came at the second battle of Ypres, to foil the German drive for the French coast ports.Local men were also members of the Fourth Battalion which saved the day by a counter- attack on the Germans who had taken advantage of the debacle of French colonial troops, when they fled before the mysterious wave of green gas which swept over their trenches near Ypres, in Belgiumthe first time that the enemj had used the arts of the chemist in an endeavor to sweep away the forces which held them back from world domination.Local men were like- wise through all the struggles on the western front in which the Canadians participated, and men from Brant were found in as widely separated fighting fields as Saloniki and Mesopotamia, Palestine and Italy.Vladivostbck and the sc\cn seas.The casualties which Branl suffered were in keeping with the enlistments and the.stern fighting in which the Canadians engaged.In all, 701 from «•<?--£«* County of Brant Honor Roll Those Who Gave Their Lives in the Great War : 1914 -1918 "duke e( decorum est pro patria mori" Nursing Sister
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.350 | 0.130 |
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".