Update from C³RS Lessons Learned Team: Four Demonstration Pilots
Bibliographic record
Abstract
The Federal Railroad Administration (FRA) believes that, in addition to process and technology innovations, human-factors-based solutions can significantly contribute to improving safety in the railroad industry. To test this assumption, FRA implemented the Confidential Close Call Reporting System (C3 RS), which includes the following: Confidential reporting; Root-cause analysis problem solving by a Peer Review Team (PRT) comprising labor, management, and FRA representatives; Implementation and review of corrective actions, some locally and others with the help of a Support Team made up of senior managers; Tracking the results of change; and Reporting the results of change to employees. Demonstration pilot sites are currently at Union Pacific Railroad (UP), Canadian Pacific Railway (CP), New Jersey Transit (NJT), and Amtrak. FRA is sponsoring a rigorous evaluation of C³RS functioning with regard to three important aspects: 1. What conditions are necessary to implement C³RS successfully? 2. What is the impact of C³RS on safety and safety culture? 3. What factors help to sustain C³RS over time? The evaluation is organized into baseline, midterm, and follow-up time periods at each site. Two sets of findings are presented here. The first set consists of baseline findings at one demonstration site (Site A), using the following data sources: (1) interviews with workers, managers, and other stakeholders and (2) other project documents, such as meeting notes and newsletters. The second set consists of findings across all demonstration sites and is based on interviews from all sites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.010 |
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 teacher head, 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".