"It is no accident that this is called an accident"- vehicular negligence : a socio-legal study of crime, law, and public safety
Bibliographic record
Abstract
Criminality takes many forms; a homicide may be defined as criminal activity, as would identity theft--both acts are criminal, yet the responses garnered are quite different. What makes the response for these two acts different? Perhaps societal reaction and tolerance towards these behaviours. Why is it that popular socio-legal discourse takes the position that societal reaction is the result of the information it receives? The focus of my research was to determine whether language affects perception and whether this impacts police and judicial practice. The focus was on the discourse of legal and popular language used to describe motor vehicle incidents that encompass a criminal component of injury and or fatality. I examined the impact of terminology on public and legal perception, as well as societal reactions and tolerance, which were the underlying issues of examination. However, in order to understand reaction and tolerance, I found it important to study the factors that contributed towards public and legal perception. The method of analysis was to examine the terminology used to depict and deliver the news of such incidents. For the purposes of this investigation vehicular negligence is defined as any act or behaviour that contravenes the British Columbia Motor Vehicle Act or is a Criminal Code of Canada offence related to the operation of a motor vehicle. Under the law, a negligent act does not require mens rea, which literally means to have a guilty mind. Therefore, in order to be considered guilty, a person does not necessarily need to have the mental culpability of forecasting or have the intention of inflicting harm. I restricted my area of focus to the region of British Columbia for two primary reasons. First, British Columbia has a higher than average injury and fatality rate resulting from motor vehicle incidents when compared to other provinces in Canada. Second, the area of focus was limited to this province as the result of my direct personal experiences in this provincial context. The parameters of my case study, as indicated above, included only those incidents of vehicular negligence that resulted in bodily injury and or fatality. The form of negligence assessed was not restricted to a specific type of act; rather it included any act that would be considered negligent behaviour on the roads, including but not limited to, driving in excess of the posted speed limit, impaired driving, carelessness, hit and runs, and so forth. My interest was to examine the ways in which these acts are perceived and addressed in public (media) and legal (court) discourse. Focusing on five randomly selected cases involving vehicular negligence, thematic analysis of face-to-face interviews, discourse analysis, and autoethnography were the primary methodologies used for the investigation. At present, there is no shortage of literature examining the cause and effect of specific behaviours in relation to motor vehicle incidents. The shortcoming, however, is that the focus of the literature is primarily centred on the consequences of drunk driving as it relates to the mismanagement of vehicles and the subsequent legal and civil litigations. Some of the literature also addresses social and health costs related to the severity of vehicle negligent incidents. However, there is a dearth of research examining the role of public and legal perceptions as they pertain to vehicular negligence and the impacts on the way in which vehicular negligent incidents are addressed within the courts. The results of this research indicated that terminology does in fact have an impact on perception, and thus negligent incidents on the roads should be referred using terms that are accurate descriptions. Terms such as accidents construe an incorrect understanding of the implications from these types of acts that are a leading health and safety epidemic globally.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".