Bibliographic record
Abstract
There were bound to be serious problems in achieving the massive expansion of Canada's wartime navy at breakneck speed and in the midst of chaotic conditions at home and abroad.Numbers tell the story: the tiny force of 2,700 regular and reserve officers and men at war's outbreak grew to 71,500 by January 1944, and to 87,000 a year later, plus 5,000 members of the Womens' Royal Canadian Naval Service.By 1944, some 85 per cent of the navy were hostilities-only members of the Royal Canadian Naval Volunteer Reserve (VRs) who had joined to fight the war.Their predominance resulted in what's been aptly described as a "citizens' navy."Unlike the RN and USN, which were able to build on large cadres of regular personnel and seasoned reservists, the Canadian navy's spectacular growth was very largely achieved by hastily training civilians who had had little or no marine experience.The exponential growth in manpower on the basis of such a small cadre and the consequent challenges in competing with a massive training burden were only two facets of the Royal Canadian Navy's expansion.A marine industrial base had to be improvised from a peacetime sector that had never been large and had shrunk severely in the Great Depression, all while warships were actually being built on emergency schedules, and somehow equipped with weapons, sensors and ammunition and, then, supported to meet gruelling operational schedules.The context for these extreme pressures was the unforgiving Atlantic campaign in which the RCN was involved right from the start of hostilities.The fact that the navy had to face the double challenge of fighting a war while trying to grow from a tiny professional cadre was underlined by a permanent force officer in a post-war interview (p.6), when he contrasted the RCN's problems in trying to achieve competence with its largely green sailors with the experience of the Canadian Army, which was able to train and develop for some three years before facing prolonged combat.Richard Mayne is a member of the naval historical team at National Defence Headquarters and a naval reserve officer.The focus of his engrossing study is the interplay between the naval
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.047 | 0.016 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 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".