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Record W2739570418

Implications of Stagnant Reporting Thresholds for Motor Vehicle Collisions

2011· article· en· W2739570418 on OpenAlexaboutno aff
Trevor Hanson, James Christie, Eric Hildebrand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsCollisionEnforcementProperty (philosophy)Inclusion (mineral)Law enforcementBusinessComputer securityPolitical scienceLawComputer sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

Each Canadian province and territory has laws requiring the reporting of vehicle collisions to enforcement agencies when there has been an injury, fatality or property damage of a specified extent. In most jurisdictions, including New Brunswick, the reporting threshold for Property Damage Only (PDO) collisions is $1,000 in total collision damage; however, the Canadian Council of Motor Transport Administrators (CCMTA) recently endorsed moving to a $2,000 reporting threshold for inclusion of PDO collisions in the National Collision Database. The collision reporting threshold was last adjusted in New Brunswick in 1993 (up from $400 in place since 1980). This paper explored the impact of the static $1000 reporting threshold on the inclusion of collisions in the New Brunswick collision database from 1994 – 2008 in terms of current and constant (1994) dollars, as well as implications for the availability of collision data in moving to a $2,000 or $4,000 threshold. Recommendations include developing uniform, objective criteria for assessing PDO collision severity.

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)0.107
metaresearch head score (Gemma)0.371
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1070.371
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.011
Science and technology studies0.0030.003
Scholarly communication0.0060.007
Open science0.0060.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.061
GPT teacher head0.261
Teacher spread0.200 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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