An Analysis of the Canadian Military-Naval Industry in the Period 2010-2018
Bibliographic record
Abstract
Canadian military naval industry has historically suffered from cycles of high investment during periods of conflict and cuts in peacetime. After years of scrapping, the government turned to the sector through the initiative of the National Shipbuilding Strategy (2010), which is an ambitious attempt to modernize the navy. Taking this scenario into account, the main purpose of this paper is to understand the role of the State as a promoter of the interactions between the relevant actors and the rules of this industry. To do so, the analysis will be based on the Structure-Conduct-Performance (SCP) paradigm, allowing a better understanding of the dynamics of the industry and a clearer identification of its important variables. Setting up a case study, this research uses official data, documents, reports and academic papers. the time frame covers the period 2010-2018, due to the launch of the Canadian shipbuilding strategy, which is a milestone for the revitalization and operation of the Canadian naval industry. This policy changed the components of the country’s military naval industry.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".