(Mis)aligning politicians and admirals: The problems of long‐term procurement in the Canadian Surface Combatant project 1994‐2021
Bibliographic record
Abstract
Abstract Popular depictions of the largest single procurement project in Canadian history—the Canadian Surface Combatant (CSC) project—characterize it as a bureaucratic failure. What began in 2008 as a $26.2B project has expanded to at least $77.3B, and $2B has already been spent without having produced a single vessel. Unlike other major Canadian aircraft, helicopter, and submarine contracts over the past four decades, however, participants in the CSC have lauded the technical merits of the procurement process. This article argues that successful procurement in this area requires: (a) clear (naval) doctrine supporting why a specific (weapons) platform or system is needed; and (b) government acceptance of that doctrine. When these two imperatives are aligned, procurement should proceed relatively smoothly. However, such smooth procurement is highly unlikely when major systems purchases involve long time periods and shifts in elected governments, policy goals, or (naval) doctrine undermine previous understandings and agreements.
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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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.056 | 0.019 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".