What a difference a quarter-century makes: commercial motor vehicle and driver safety in the United States, 1984-2009
Bibliographic record
Abstract
In the past 25 years, the highway freight and passenger industries in the United States have experienced considerable structural changes. The removal of economic barriers to market entry and an increased demand for high-reliability and point-to-point delivery of freight and passengers has led to an explosion in the number of motor carriers to provide these services. During the same period, the legal and regulatory atmosphere has also evolved. Although the foundations for motor carrier safety regulations were established in 1935 legislation, the Motor Carrier Act of 1984 defined a motor (CMV) and on the Act's 25th anniversary, it is appropriate to review some of the safety outcomes that it helped to set in motion. This paper begins with a summary of key laws and regulations concerning vehicle, driver, and motor carrier operational matters. Next, it illustrates a variety of long-term trends in operational inputs and safety outcomes. Finally, it offers a view toward the next evolutionary stages in commercial vehicle safety technologies and safety regulation. (a) For the covering entry of this conference, please see ITRD abstract no. E219320.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".