Comparing Western Australia and South Australia public high school’s cyberbullying policies – is there a need for a legislative change
Notice bibliographique
Résumé
The internet provides some of the most effective means of communication. Cyberbullying occurs when the internet is used to bully another person. Along with the positive aspects of the internet, cyberbullying is certainly one of the most negative aspects, especially with regard to school students. Victims of cyberbullying may be able to obtain legal sanctions, however, this usually occurs after the harm is done. In Australia, some states such as South Australia have recognised the need for preventive strategies by requiring schools to have an anti-bullying plan in place. Other countries, like Ontario, Canada have implemented similar preventative strategies in their legislation. One way to reduce cyberbullying in schools is to create an anti-bullying culture within the school. The implementation of a cyberbullying policy that promotes a positive school culture, prevention and intervention strategies, support systems, clear definitions and reporting procedures, aid in creating this culture. An effective school cyberbullying policy will aid in the promotion of an anti-bullying school culture and thus lead to a reduction in bullying and cyberbullying behaviours. This thesis argues that Western Australia should follow South Australia and Ontario in implementing legislation to require high schools to have a cyberbullying policy. This argument will be tested by answering two research questions: First, whether the cyberbullying policy is more prevalent, robust and openly displayed in South Australian public high schools compared with Western Australian public high schools; and second, what lessons can be drawn from legislation pertaining to cyberbullying in schools in Ontario and South Australia. The research finding suggests that Western Australian public high schools do not have and do not openly promote policies pertaining to cyberbullying, whereas South Australian public high schools do. The research found that 88% of South Australian public high schools openly display their bullying policy, in comparison to only 51% of Western Australian public high schools. South Australia also has a state-wide bullying prevention program and legislation regarding the implementation of policies regarding bullying and harassment in schools. Legislation from Ontario provides a different perspective regarding the implementation of bullying and cyberbullying policies in schools. Ontario’s Education Act is more extensive than the legislation in South Australia with regards to cyberbullying in schools, as it includes definitions of bullying and cyberbullying, the rights and responsibilities of teachers, principals, and the school board to prevent and address bullying in schools, as well as encouraging a positive and inclusive school experience, and promoting strong and respectful relationships within the school and the community. Given that the existence of a cyberbullying policy in high school is an important tool in preventing and dealing efficiently with cyberbullying, these findings support the thesis argument that there is a need for similar legislation like the Education Act in Ontario, to be implemented in Western Australia.
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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 | 0,002 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».