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Record W2119891811 · doi:10.1080/15389580701682114

A New Look at NHTSA's Evaluation of the 1984 Charlottesville Sobriety Checkpoint Program: Implications for Current Checkpoint Issues

2008· article· en· W2119891811 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.

fundA Canadian funder is recorded on the work.
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 · 2008
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
FundersMemorial University of NewfoundlandUniversity of Virginia
KeywordsSobrietyTest (biology)Computer securityEngineeringForensic engineeringPsychologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Currently, the implementation of sobriety checkpoint programs, which have been demonstrated to be effective in reducing alcohol-related crashes, is limited by the belief that they require large consignments of police officers and result in few arrests. However, one of the earliest evaluations of a checkpoint program in Charlottesville, Virginia, demonstrated that effective checkpoints could be mounted in which police officers made as many arrests as officers on regular patrols. That study was printed by the NHTSA but was not published in a peer-reviewed journal. Because of its significance to current issues in the staffing of and procedures for checkpoint operations, this article reanalyzes the results of that study and describes the procedures implemented in checkpoints. METHODS: A before-and-after control design was used to measure the change in nighttime crashes from three baseline years to the program year. Two analyses were conducted: the first on the percentage of all crashes occurring at night in the test city--Charlottesville--and the second on the percentage of all nighttime crashes in the state of Virginia that occurred in the test city. In addition, three waves of random-digit-dialing telephone surveys were conducted: one before and two during the checkpoint program in the test city, and the comparison city, Blacksburg. Finally, the number of impaired-driving arrests per officer hour at the checkpoints was compared with the number of arrests per hour by officers on regular patrol and the effect on arrests of the use of passive sensors was determined. RESULTS: The monthly percentage of nighttime crashes in Charlottesville was reduced by 17% (p = 000) in relation to the baseline level. The percentage of nighttime crashes in the state of Virginia that occurred in Charlottesville was reduced by 11% (p = .013) from baseline levels. Drivers arrested at checkpoints had lower BACs than those arrested by the regular patrols; however, the conviction rates were the same. The arrest per officer hour did not differ significantly between the two types of enforcement operations. Awareness of the checkpoint activity was high (72%) among nighttime at-risk drivers in the test city. Half reported seeing a checkpoint operation, and a quarter reported being interviewed. Use of a passive alcohol sensor by officers at the checkpoint increased arrests by almost a factor of three. CONCLUSIONS: The results of the evaluation suggest that small-scale sobriety checkpoints can be implemented as part of the regular enforcement program in moderate-sized jurisdictions and that they can be as efficient in producing arrests as standard enforcement patrols, particularly if passive alcohol sensors are used.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.044
GPT teacher head0.324
Teacher spread0.280 · 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