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Record W2130871585 · doi:10.1093/geront/41.6.751

Traffic-Related Fatalities Among Older Drivers and Passengers

2001· article· en· W2130871585 on OpenAlexaff
Michel Bédard, M. J. Stones, Gordon Guyatt, John P. Hirdes

Bibliographic record

VenueThe Gerontologist · 2001
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsLakehead Psychiatric Hospital
Fundersnot available
KeywordsInjury preventionOccupational safety and healthSuicide preventionDemographyHuman factors and ergonomicsPoison controlOlder peopleGerontologyGeographyEnvironmental healthTransport engineeringPsychologyMedicineEngineeringSociology

Abstract

fetched live from OpenAlex

PURPOSE OF THE STUDY: This study was initiated to forecast the number of older drivers and passengers who may be fatally injured in traffic crashes in future years. DESIGN AND METHODS: The study was based on data from the U.S. Fatality Analysis Reporting System covering the period from 1975 to 1998. Projections were based on least squares regression models. RESULTS: About 35,000 drivers and passengers died in traffic crashes each year from 1975 to 1998. Older adults (65 and older) accounted for 10% of all fatalities in 1975, 17% in 1998, and a projected 27% by 2015, the same proportion predicted for drivers and passengers aged younger than 30. On the basis of these projections, the number of fatally injured women and men aged 65 and older will increase respectively by 373% and 271% between 1975 and 2015. IMPLICATIONS: If current trends continue, the number of fatalities among older drivers and passengers and those aged younger than 30, may be equivalent early in this century. These projections call for further research into conditions that may lead to crashes involving older drivers and for the development and implementation of initiatives to curb traffic-related fatalities among older adults.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.363
Teacher spread0.317 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations35
Published2001
Admission routes1
Has abstractyes

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