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Record W2033276660 · doi:10.1080/15389588.2014.935356

Detailed Analysis of Pedestrian Casualty Collisions in Victoria, Australia

2014· article· en· W2033276660 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTraffic Injury Prevention · 2014
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianCoronerInjury preventionPoison controlMedicineOccupational safety and healthSuicide preventionMedical emergencyDemographyPopulationQuarter (Canadian coin)Human factors and ergonomicsGeographyEnvironmental healthEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Pedestrian road trauma is significant in Australia and requires in-depth understanding to improve or inform new countermeasures. Analyses on single data sources can be limited. This study investigated demographic, behavioral, environmental, and collision characteristics of pedestrian injury in Victoria, Australia, over a 5-year period using multiple data sources. METHODS: Victorian state police, hospital presentation, hospital admission, and coronial data sets were analyzed and compared for the years 2004 to 2008. RESULTS: Analyses identified 3,702 police-recorded pedestrian casualties (deaths and injuries, of which 256 were deaths), 5,008 pedestrian traffic-related hospital presentations, and 2,802 pedestrian admissions. Trend analyses showed significant increases in police casualty and hospitalization rates per 100,000 population. Age groups most commonly involved were those aged 18-24 especially on weekends, 75+ especially on weekday days, and 13- to 17-year-olds especially at school commute times. Proportionally more cases were male in all data sets. One quarter of coroner-examined deaths involved alcohol and one third involved drugs. Two thirds of police-recorded casualties occurred on weekdays, and 45% of weekend casualties occurred at night. Most casualties occurred in urban areas (95%), in lower-speed zones (78%); however, 79% of rural casualties occurred in high-speed zones, of which more were fatal. Over half did not occur at intersections. The most common injuries were fractures as well as multiple injuries, which together with intracranial injuries, were most common among fatalities (50 and 34%, respectively). Serious injury was more likely in older pedestrians, in males, in rural areas, in 60-80 km/h zones, in areas with poor lighting, while crossing a carriageway, not at an intersection, and when struck by a heavy vehicle. CONCLUSIONS: Findings indicate pedestrian serious injury rates are increasing and identify targets for countermeasures. Inherent limitations present in each relevant data collection require mutliple data sets to be explored and results contrasted. Jurisdictions seeking to determine pedestrian injury risk factors should aim to link police and hospital data for a complete analysis.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.278
Teacher spread0.262 · 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