Bypassing the Chain of Command: The Political Origins of the RCNâs Equipment Crisis of 1943
Bibliographic record
Abstract
At the behest of Angus L. Macdonald, the Minister of National Defence for Naval Services, John Joseph Connolly conducted a secret investigation in October 1943 into the state of equipment on Canadian warships. Connolly, who was Macdonald’s executive assistant, traveled to St. John’s, Londonderry and London where he discovered that the Royal Canadian Navy (RCN) was far behind its allies in the modernization of its escort fleet. Canadian ships lacked gyroscopic compasses, hedgehog, effective radar and asdic, as well as other technical gear that was essential in the Battle of the Atlantic. These deficiencies should not have come as a surprise. Inadequate equipment on RCN ships had already become obvious during the intense convoy battles of 1941, and had been confirmed yet again by those of 1942. Insufficient training and manning policies also played their part in Canadian problems at sea. However, it was to be the technical aspects that Macdonald focused upon once Connolly returned from overseas, leading not only to a disruptive feud with the naval staff, but also, in their way, to the eventual replacement of Vice Admiral Percy W. Nelles as the Chief of the Naval Staff (CNS) in January 1944.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".