Cyber Bullying in Chinese Web Forums: An Examination of Nature and Extent
Notice bibliographique
Résumé
IntroductionAdolescent school violence is a common and significant problem in many countries across the globe (Arseneault, Walsh, Trzesniewski, Newcombe, Caspi, & Moffitt, 2006; Beran & Li, 2005, 2007; Erdur-Baker, 2010; Frost, 1991; Hazler, Hoover, & Oliver, 1992; Ma, 2001; Olweus, 1993; Sharp, Thompson, & Arora, 2000; Wang, Iannotti, & Nansel, 2009). Often, violence among youths involves some component of bullying, wherein individuals repeatedly experience some negative action by another young person who attempts to disrupt, injure, or otherwise cause discomfort for their victim (Olweus, 1993). The impact of bullying can be quite severe, often causing depression and health concerns for victims (Kaltiala-Heino, Rimpela, Marttunen, Rimpela, & Rantanen, 1999; Klomek et al., 2008; Kumpulainen & Rasanen, 2000; Nansel, Overpeck, Haynie, Ruan, & Scheidt, 2003; Nansel et al., 2001; van der Wal, de Wit, & Hirasing, 2003), and attempted suicide (Klomek, Marrocco, Kleinman, Schonfeld, & Gould, 2007; Klomek et al., 2009). In fact, some researchers argue that bullying is a major public health concern requiring significant research and resources (Nansel, Overpeck, Pilla, Ruan, Simons- Morton, & Scheidt, 2001).As the Internet and computer-mediated communications technologies are increasingly inexpensive and available, the opportunities for individuals to engage in bullying via electronic methods, or cyber bullying, has increased significantly (Beran & Li, 2005, 2007; Finkelhor, Mitchell, & Wolack 2000; Hinduja & Patchin, 2008, 2009; Snider & Borel, 2004; Wolack, Mitchell, & Finkelhor, 2006; Ybarra 2004). Research on cyber bullying has primarily focused on student populations in the United States and Canada, due to several high profile incidents where cyber bullying was related to incidents of suicide among youth (Beran & Li, 2005, 2007; Finkelhor et al., 2000; Hinduja & Patchin, 2008, 2009; Li, 2006; Marcum, 2008; Wolack et al., 2006; Ybarra, 2004). These studies indicate that there is significant emotional and mental health concerns generated by cyber bullying experiences (e.g. Hinduja & Patchin 2008; van der Wal et al., 2003; Ybarra 2004). Few researchers have, however, actively examined the content of bullying messages to consider the frequency of multiple forms of bullying, and the tenor of the messages posted by bullies to understand how messages are developed and targeted (Hinduja & Patchin, 2008, 2009). As a consequence, it is unclear how the process and experience of bullying occurs.Considering the significant challenges posed by cyber bullying, researchers across the globe are beginning to examine this phenomenon (Erdur-Baker, 2010; Erdur-Baker & Kavsut, 2007; Li, 2008; McLoughlin, Meyricke, & Burgess, 2009; Wolack et al., 2006). Studies utilizing US populations suggest that cyber bullying is a common problem among juvenile populations, though prevalence rates vary depending on the sample and definition of bullying used (Marcum, 2010; Hinduja & Patchin, 2008; Wolack et al., 2006). Similar research has found cyber bullying to be a growing problem in Australia (McLoughlin et al., 2009), Canada (Beran & Li, 2005, 2007), and Turkey (Erdur-Baker, 2010; Erdur- Baker & Kavsut, 2007). Few researchers have, however, examined the issue of cyber bullying in developing nations, particularly Asia (Huang & Chou, 2010; Li, 2008). In fact, China is the most populace nation in the developing world, and has experienced an explosion in Internet use over the last decade (Central Intelligence Agency, 2010). In fact, one of the only studies examining cyber bullying in China found that 33 percent of children had experienced cyber bullying, while a very small percentage actually engaged in cyber bullying themselves (Li, 2008). Chinese students appear more likely to report victimization experiences to teachers or adults suggesting that adults are more likely to intervene on behalf of a victim (Li, 2008). …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».