Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".