"It is no accident that this is called an accident"- vehicular negligence : a socio-legal study of crime, law, and public safety
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,013 | 0,027 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».