A Multi-Criteria Analysis of High Speed Rail System in Canada
Bibliographic record
Abstract
High-speed rail (HSR) has drawn attention worldwide as a potential solution to the transportation and mobility issues of the twenty-first century. For the past thirty years, several feasibility studies and discussions have advocated building one or more HSR systems in Canada. Quite a few studies have highlighted the benefits of HSR for Canada's economy, reducing traffic, and enhancing connectivity between cities. However, Canada's size, population density and high costs involved in construction and operation, etc. pose significant challenges to HSR implementation. This paper analyzes the feasibility of HSR in Canada using multiple criteria, such as geography, demography, financing, investment, and regulatory policies and arrives at a recommendation. The objective of this paper is to present various factors and trade-offs to gain better understanding of HSR planning in Canada, thereby adoption of a distinctive and holistic approach. This paper provides a ready-to-go and comprehensive assessment for policymakers, stakeholders, and researchers regarding HSR viability by enabling informed decision-making aiming towards potential operations of this transportation system.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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 | 0.000 |
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".