THE VIEW FROM THE WINDSHIELD: A LAW ENFORCEMENT PERSPECTIVE ON INTERSECTION SAFETY
Bibliographic record
Abstract
This report has been produced by the Institute for Police Research, the educational division of the International Union of Police Associations. The I.U.P.A. represents an estimated 100,000 law enforcement officers throughout the United States, Puerto Rico, the U.S. Virgin Islands, and Canada. Members come from all aspects of law enforcement, municipal police, deputy sheriffs, county police, state police, federal officers, institutional officers (university and hospital police), corrections officers, and law enforcement support personnel. The information is a composite of ideas and analysis obtained from numerous conversations with officers with a broad variety of direct field experience. The role of law enforcement in intersection safety must be considered in two parts. The first, relates to ensuring that the public obeys laws. The second, relates to the effect intersections have on emergency response to calls for service and other emergencies. In all cases, it should be kept in mind that the vast majority of law enforcement agencies throughout the country suffer from chronic personnel shortages. It should be clearly noted that this is not intended to be a technical treatise on the design and engineering of intersections. Engineers and designers look at roads and their intersections on computer screens and blue prints. The men and women in law enforcement look at them through their windshields. We therefore bring you the view from the cruiser in the hope that as you seek solutions to intersection safety problems, you give credence to the practical experience of those closest to the problem.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.034 | 0.043 |
| Scholarly communication | 0.024 | 0.023 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".