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Record W2061816667 · doi:10.2105/ajph.2006.107375

SPORTS UTILITY VEHICLES AND VULNERABLE ROAD USERS

2007· letter· en· W2061816667 on OpenAlexaff
Ediriweera Desapriya, Ian Pike, Kate Turcotte

Bibliographic record

VenueAmerican Journal of Public Health · 2007
Typeletter
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsPedestrianTruckInjury preventionEnvironmental healthPoison controlOccupational safety and healthSuicide preventionMedicineHuman factors and ergonomicsMedical emergencyTransport engineeringBusinessEngineering

Abstract

fetched live from OpenAlex

We read with interest the article by Robertson,1 and we certainly agree that the sports utility vehicles (SUVs) pose an increased risk to small car occupants as well as vulnerable road users, such as pedestrians, cyclists, older persons, and children.2 In many developing countries, pedestrians, cyclists, rickshaw operators, and moped users represent the majority of road users. These countries rarely have the resources to physically separate such road users from car traffic. Many developing countries have no sidewalks or bicycle paths and those that do exist are heavily obstructed by trees, trash, drainage ditches, and vendors selling goods. Pedestrian injuries are a leading cause of global death and injury burden, accounting for 65% of the 1.2 million annual road deaths.3 Collisions between pedestrians and vehicles present a major challenge for public health, trauma and emergency medicine, and traffic safety professionals. Yet, in spite of the size of the pedestrian injury problem, research has concentrated almost exclusively on increasing the survival rates for vehicle occupants.4 A man waits for his identification wristband to be scanned during a mock evacuation drill May 23, 2006 in New Orleans, Louisiana. The two-day drill is being held in New Orleans and Baton Rouge in order to help the area prepare for the upcoming hurricane season. Photograph by Mario Tama. Courtesy of Getty Images. Recent US and United Arab Emirates studies have reported that increased numbers of SUVs and pickup trucks were associated with pedestrian deaths and a higher pedestrian injury severity score,5,6 and SUVs were 4 times as likely to be associated with fatal injury for the 5- to 9-year-old age group.7 Method of transportation is an important determinant of public health, affecting physical activity levels, social and economic opportunities, and general well-being.8 Extensive literature on the various health benefits of physical activity has illustrated the need to understand the determinants, risks, and barriers of physical activity. Vehicle danger is a disincentive to active lifestyles in that reducing the risks of fatal traffic injury for pedestrians and cyclists is an important part of any strategy to encourage walking and cycling to combat childhood obesity. Walking and cycling are essential modes of travel for many people living in low- and middle-income countries. Safe walking and cycling should be promoted, because their environmental, economic, and health benefits are significant.9 Potential reduction in the costs of treating heart disease if adults walked regularly has been calculated in the United States, saving US$5.6 billion annually if 10% of adults began a regular walking program.10 Safety standards for vehicle front-end construction, which would make vehicles less hazardous to pedestrians and cyclists, may be as important as standards that affect vehicle occupants; however, political obstacles have made such standards difficult to implement.1,2,5,7

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.023
GPT teacher head0.261
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations4
Published2007
Admission routes1
Has abstractyes

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