A Multiagency Effort to Reduce Bicyclist Fatalities and Serious Injuries in New York City
Bibliographic record
Abstract
In the summer of 2005, responding to an apparent increase in the number of bicyclist fatalities in New York City (NYC), a coalition of bicycling advocacy groups, clubs, racing organizations, and working cyclists presented a six-point Bike Safety Action Plan to NYC's Department of Transportation (DOT) and Police Department (NYPD).Leading the list of desired action steps was the coalition's request for a comprehensive study of bicyclist fatalities.The requested report was to be modeled on a bicycling casualty study completed by the city of Toronto in the late 1990s, 1 considered by many advocates to be the most comprehensive municipal study to improve bicycling conditions to date.Advocates asked that the city's health department play a role in the study.One year later, in September 2006, four NYC agencies with a shared interest in promoting safe bicycling-the Department of Health and Mental Hygiene (DOHMH), Department of Parks and Recreation, DOT, and NYPD-released a joint report to the public entitled Bicyclist Fatalities and Serious Injuries in New York City: 1996City: -2005. 2 . 2 The report provided a comprehensive examination of bicyclist fatalities and serious injuries, drawing on multiple data sources including police accident reports, accident scene investigations, and medical examiner files.As part of the report, the city announced an aggressive package of action steps to increase bicycling and promote safety.Details of the investigation, proposed action steps, and subsequent efforts are described in this article.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".