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Record W2542789015

A SURVEY OF UNLICENSED DRIVING OFFENDERS

2002· article· en· W2542789015 on OpenAlexaboutno aff
Barry C. Watson

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsLaw enforcementEnforcementSample (material)Driving under the influenceDrunk drivingPsychologyComputer securityQuarter (Canadian coin)Human factors and ergonomicsPoison controlCriminologyLawPolitical scienceComputer scienceMedical emergencyMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper reports the findings of a survey of 309 unlicensed driving offenders interviewed at the Brisbane Magistrates Court. A wide range of offenders participated in the study, including: disqualified and cancelled drivers; expired licence holders; drivers without a current or appropriate licence; and those who had never been licensed. The results suggest that unlicensed drivers should not be viewed as a homogenous group. Significant differences exist between offender types in terms of their socio-demographic characteristics; driving history; whether they were aware of being unlicensed; and their behaviour while unlicensed. Among some offenders, unlicensed driving appears to be indicative of a more general pattern of non-conformity; almost two-thirds of the disqualified and never licensed drivers had prior criminal convictions. While many offenders limited their driving while unlicensed, others continued to drive frequently. Moreover, almost one-third of the sample continued to drive unlicensed after being detected by the police. While there was some evidence that offenders attempted to drive more cautiously while unlicensed, this was not consistent with other aspects of their behaviour. For example, almost one-quarter of the offenders admitted driving at some time when they thought they were over the legal alcohol limit. The results highlight the need to enhance current policies and practices to counter unlicensed driving. In particular, there is a need to examine current enforcement practices since over one third of the participants reported being pulled over by the Police while driving unlicensed and not having their licence checked.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.276
Teacher spread0.222 · 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

Citations13
Published2002
Admission routes1
Has abstractyes

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