The Cascadia Corridor (Northwest of the United States): A limited territorial anchorage for a growing interurban rail service
Bibliographic record
Abstract
The Northwest Corridor is part of the Cascadia Region, stretching from Portland, Oregon, through Seattle, Washington, to Vancouver, British Columbia in Canada. The Amtrak Cascades service is a high-speed rail service in which the managing states (Washington, Oregon) are heavily involved, in coordination with Amtrak and the freight company BNSF, which owns the infrastructure. It is important to understand why this corridor modernization programme is considered a model of its kind, both by Amtrak Cascades officials and by the federal government. This article therefore analyses US rail geography through the case study of the Cascades corridor and questions the process of territorialization of rail policies. The Cascades Corridor is a relevant case study for looking at a mixed-use corridor (freight and passengers) supported by highly committed public stakeholders despite the institutional and budgetary isolation of intercity rail transport. This analysis reveals a successful experience, welcomed by all public and private stakeholders, of modernizing an existing rail corridor, but only a partial territorialization process that does not take sufficient account of stations and station districts and ignores the metropolitan planning dimension of the transport project with regard to Seattle and Portland.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".