FILLING THE RANKS: RECRUITING, TRAINING AND REINFORCEMENTS IN THE CANADIAN EXPEDITIONARY FORCE 1914-1918
Bibliographic record
Abstract
This dissertation deals with the evolution of manpower management in the Canadian Expeditionary Force from 1914 to 1918: recruiting, entry-level training and the provision o f reinforcements from Canada to England and England to France. The central theme is the increasing professionalism in the Canadian Forces with the development of an efficient and comprehensive system of recruiting, training and reinforcing units at the 'front.- This work argues that from first to last, the government did not appreciate the need to husband manpower although the Canadian Forces made continual efforts to manage the pool by altering recruiting criteria and seeking alternative sources for recruits. Training was based on British army programs that were well-suited to conditions on the Western Front. However, training in Canada was largely a waste of time because of obsolete equipment and by the end of the war, depot units were responsible only for recruiting and forwarding men to the reserve units. Initially the reinforcement structure was based on British army policies but these did not accommodate the structure of the Canadian Forces. However, with the creation of the Ministry of the Overseas Military Forces of Canada, was rationalized and modified to suit Canada’s needs. This dissertation relies on extensive primary sources in both Canada and Great Britain to conclude that by 1918, Canada had developed an efficient and comprehensive system for managing the national manpower pool. The dissertation also notes profound changes in both the state and society. This dissertation was published in 2 volumes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".