Bibliographic record
Abstract
The station governance and parking practices of 19 commuter rail services in the United States and Canada are summarized. Unique or innovative approaches to address ownership and management issues are described. Unlike most urban transit systems, commuter rail authorities often do not control stations or parking. Wide-ranging practices exist, from outright facility ownership and control by the authority to no ownership or control. Many agencies and the private sector, including freight railroads with several services, are involved in ownership and management. Older, more established systems have the most complex ownership arrangements and operating practices. The authority, municipalities, and private sector of many systems are involved in the ownership and management of station buildings and parking facilities. Many authorities continue to provide ticket agents at stations, and a fee is typically charged for parking, which is often collected by the municipality. Passenger platforms are generally owned and maintained by the authority. Newer commuter rail services have less complex practices. Sometimes the authority is not involved with the station building or parking, although it typically owns and maintains the platforms. Many newer services also use technology more extensively, including ticket vending machines, to reduce the need for station personnel. Parking at the newer systems is generally provided free of charge, although various ownership and operating arrangements exist. Several systems have developed innovative approaches to address parking capacity issues. Partnerships with municipal governments, private companies, and community organizations to share parking are also used to reduce agency expenditures for new parking.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".