Run Silent, Run Cheap: Deciding on the Oberon-class Submarines, 1960–68
Bibliographic record
Abstract
During the looming crisis of the early Cold War, the Supreme Allied Commander Atlantic of the North Atlantic Treaty Organization wanted Canada to procure a subsurface capability of equal quality, if not quantity, to that of other Allied nations. Even though Canada played with acquiring nuclear submarine technologies and several new conventionally powered hunter-killer submarines, politicians were more interested in cutting costs and using as few funds as possible to cover as many roles as possible. Canada opted to purchase three operational submarines to help fill anti-submarine warfare roles, but the Oberon-class boats that were ultimately chosen by the end of the 1960s were entirely obsolete and were by that time the only choice available to Canada’s politicians: Canada’s dithering had cost its navy its best options for subsurface capabilities. This paper recounts in detail the depths to which federal dithering on the submarine issue of the 1960s sank, a process that in turn nearly scuttled Canada’s submarine program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".