Notice bibliographique
Résumé
In recent years, the term ‘cyberbullying’ has become relatively common in the media, often cited as a contributor to several high-profile suicides of young adolescents. A review of the literature published in 2010 (1) showed that no articles referenced ‘cyberbullying’ before 2004, confirming its recent emergence. There is no universally accepted definition; however, most definitions describe a repeated activity conducted via electronic means with an intent to cause psychological torment. Cyberbullying can take many forms. It can include harassment (insults or threats), spreading rumours, impersonation, outing and trickery (gaining an individual's trust and then using online media to distribute their secrets) or exclusion (excluding an individual from activities). These activities can be performed via e-mail, instant messaging, text message, social networking sites such as Facebook or Tumblr, and other websites (2). The prevalence of cyberbullying and cyberbullying victimization is difficult to accurately determine. The variable definitions and the typical challenges of accounting for self-reported activities contribute to this difficulty. A study conducted in the United States involving nearly 4000 students in grades 6 to 8 showed that in the preceding two months, 11% of the students had been cyberbully victims, 4% reported acting as cyberbullies, and 7% had been both a cyberbully and a cyberbully victim (3). In a Canadian study published in 2010 involving >2000 students in grades 6, 7, 10 and 11, 25% reported experiencing a cyberbullying event in the previous three months. Eight percent reported acting as a cyberbully, and 25% reported being both a cyberbully and cyberbully victim. The authors postulated that the rates were higher in their study because they did not describe the activity as ‘cyberbullying’, but instead asked about specific behaviours (name calling, threatening, spreading rumours, etc) (4). Cyberbullying differs from traditional bullying in several key ways. Perhaps the most obvious is that it requires some degree of technical expertise – children who are not ‘plugged in’, either through computer, cell phone or video games, do not partake in cyberbullying, either as bullies or victims. Cyberbullying also provides anonymity to the bully not possible with traditional bullying. Because of this, bullies cannot see the reactions of their victims and studies have shown that they feel less remorse (5). Cyberbullying is opportunistic because it causes harm with no physical interaction, little planning and small chance of being caught. Despite this, 40% to 50% of cyberbully victims report knowing who their tormentor is (3). Cyberbullying can be more pervasive than traditional bullying. While traditional bullying is generally limited to school and home is a reprieve, victims of cyberbullying can be reached anywhere, anytime, and the potential audience is huge. This is compounded by the fact that there is a lack of supervision. With traditional bullying, teachers are regarded as enforcers. With cyberbullying, there is no clear authority, and children express reluctance to tell adults for fear of losing computer privileges or being labelled as an informer (6). Studies have also shown that there is a large amount of overlap among traditional bullying and cyberbullying behaviours. Children who act as cyberbullies report high rates of being a traditional bully, and are also traditional and cyberbully victims. Cyberbully victims report high rates of traditional victimization, but are also involved in traditional bullying and cyberbullying activities (3,7). The relationship between traditional bullying and cyberbullying is not well understood, but what is clear about children involved in cyberbullying is that they report high rates of Internet use. Juvonen and Gross (8) found that cyberbully victims were significantly more likely to be heavy Internet users (>3 h/day) than noncyberbully victims (OR 1.45). A study by Mishna et al (4) published in 2012 found that cyberbullies, cyberbully victims and cyberbully/victims were significantly more likely to use the computer for >2 h/day versus students who were not involved in cyberbullying activities. Affected children have reported varying rates of informing authorities regarding cyberbullying (2% to 40% would tell a teacher). When asked if they would inform a friend, studies have reported rates of 13% to 74%. When asked about telling a parent, rates vary from 9% to 57%. Anywhere from 9% to 25% of children reported they would not tell anyone about being cyberbullied. Approximately 50% of children report using prevention tactics such as blocking a screen name, changing passwords or restricting their buddy list (6,8,9). Cyberbullying behaviour has negative effects on both the victim and the bully. The negative effects increase with the frequency, duration and severity of cyberbullying. Victims who endure frequent cyberbullying can experience a decline in academic performance, begin ‘acting out’ and some report difficulties at home. These children are at increased risk for depression, anxiety and externalized negative behaviours, as well as an increased risk for suicide (10,11). As previously mentioned, cyberbullies feel a lack of remorse and have more behavioural difficulties (police contact, property damage, school absenteeism, low grades) than children who are not involved in cyberbullying (5,12). One study has shown that children who act as cyberbullies are also at increased risk for suicide, although they score lower on measures of suicidal ideation than their victims (11). Children who are both a cyberbully and a cyberbully victim are at risk for the emotional difficulties associated with being a victim, as well as the behavioural difficulties associated with being a bully (13). To help identify at-risk children, health care professionals need to ensure that they ask their patients if they are experiencing cyberbullying, being careful to specify the actual behaviours (name calling, spreading rumours, outing and trickery, etc) Affected children should be screened for comorbid disorders. Parents should be counselled about the negative effects of cyberbullying and instructed on safer Internet use. Parents have a critical role in providing online education for their children. Parents should be encouraged to keep computers with Internet access in open areas, monitor the child's online activities and behaviour, encourage their children to never reveal passwords or secrets, and never open a message from someone they do not know. Parents should remind their children not to believe everything they read, and the entire family should be encouraged to spend time together away from the online world. Parents can also model appropriate use of technology and teach children that posting harmful content about others is not appropriate (14). In Canada, there are currently no laws specifically addressing cyberbullying. A Cybercrime Working Group established in 2012 identified several sections of the Criminal Code that could allow charges relating to cyberbullying, but noted that the Code needed to be modernized to include messages sent via electronic means. The Working Group also recommended a new criminal offense relating to the nonconsensual distribution of intimate images be created. These changes were included in Bill C-13, Protecting Canadians from Online Crime Act, which was introduced in 2013. The bill criminalizes the nonconsensual distribution of intimate images, and updates terminology regarding telecommunications technologies by removing reference to radio, telegram and telephone. This allows for harassment charges to be filed when messages are sent via any electronic means (15). There are privacy concerns regarding Bill C-13 because it also deals with lawful access legislation. The bill, among other things, would allow police to request personal information from Internet service providers without a warrant through a ‘preservation demand’ (15). The Canadian Bar Association has recommended that a preservation demand be allowed only in exigent circumstances, and only for a short period of time until a warrant can be obtained. Overall, the Canadian Bar Association has recommended that the bill be split into two: a bill specific to cyberbullying, and another specific to lawful access. This would enable timely passage of the bill on cyberbullying while allowing for debate and changes to protect privacy in the lawful-access bill (16). This has not occurred, and Bill C-13 remains before the government. It has not yet become law. Cyberbullying is public, pervasive and provides anonymity not observed with traditional bullying. Studies are increasingly showing the negative effects of cyberbullying on both the bully and the victim. While it is possible to be charged with some aspects of cyberbullying under the Criminal Code of Canada, the Code has not yet been modernized to reflect the information technology era. Health care professionals need to be informed about the manner in which cyberbullying can occur, the negative effects of it, and be prepared to counsel parents on how to prevent it. The author thanks Andrea Wilson-Peebles for a detailed review of the manuscript.
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 | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,006 |
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 ».