Bibliographic record
Abstract
The purpose of the synthesis was to report the state of the practice to aid transit agencies and other entities in deciding how to develop successful wayside rail track worker protection practices. The topic panel directed the consultant to conduct in-depth telephone interviews and site visits with selected transit agencies’ staffs to provide a comprehensive look at how representative agencies provide successful wayside worker safety programs, covering multiple items. The goal was to aid streetcar, light and heavy rail providers, and other stakeholders in deciding how to proceed in developing and/or revising track worker protection practices. A review of the relevant literature was conducted to identify available and relevant documents and resources drawn from the FTA, GAO, and NTSB reports; FRA regulations and APTA standards resources; as well as numerous state, regional, and local agency issued publications. Thirty-nine publications are listed. It was determined that in-depth case studies for SF-15 would provide more thorough synthesis reporting of subject areas at select agencies and be more beneficial and useful to other transit agencies than cursory synthesis survey reporting of numerous subject areas across a larger number of agencies. The transit agencies studies were part of a Track Safety Task Force formed by New York City Transit as a result of track worker fatalities to evaluate safety culture, identify deficiencies and strengths, and develop recommendations for improvement. This task force was later joined by the Toronto Transit Commission in a Track Level Safety Team and charged with further improvements for workers at track level. Other systems soon formed or reconstituted “Rules Committees.” Thus, these five transit agencies afforded the SF-15 panel with a range of modal, operational demographic, size, and historical context from which to look at proven practices and processes in implementing wayside rail track worker protection.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".