Anti-bullying laws including sexual orientation associated with fewer suicides
Windy City Times
Sexual minority youth have a higher prevalence of bullying and attempted suicide than non-sexual minority youth.
New research from the Williams Institute at UCLA School of Law and the Centers for Disease Control and Prevention ( CDC ) found that anti-bullying laws that explicitly protect youth based on sexual orientation are associated with fewer suicide attempts among all youth, regardless of sexual orientation.
In addition, enumeration of sexual orientation was associated with fewer experiences of stressors, such as feeling unsafe at school and being physically forced to have sexual intercourse.
While fewer youth attempted suicide in states with sexual orientation-inclusive anti-bullying laws, more sexual minority youth experience bullying and other stressors, and they are more likely than non-sexual minority youth to experience suicide ideation and attempts—whether or not their state has explicit sexual orientation protections.
COULD WORKPLACE BULLYING BECOME YOUR NEXT SAFETY ISSUE?
By Holly Foxworth, Axiom Medical
Gone are the days of considering bullying, harassment, and violence only the problems of your human resource department. They are now your next safety issue in the workplace!
As explained at the 2018 Safety Leadership Conference, what ends as a violent act starts out slowly as incivility, or the intent to harm a worker. Negative interactions or jabs at someone could be brushed off as a cultural norm at the workplace.
Unfortunately, this can escalate to hazing or harassment, leading to a physical act.
A deep learning-based method to detect cyberbullying on Twitter
by Ingrid Fadelli , Tech Xplore
Researchers at King Saud University, in Saudi Arabia, have developed a new approach to detect cyberbullying on Twitter using deep learning called OCDD. In contrast with other deep-learning approaches, which extract features from tweets and feed them to a classifier, their method represents a tweet as a set of word vectors.
In recent years, cyberbullying on social media has become a huge and widely discussed issue. Cyberbullying entails the use of online communication channels to bully other users by sending intimidating, threatening or abusive messages. This can have psychological and sometimes life-threatening consequences for the victims.
Researchers worldwide have been trying to develop new ways to detect cyberbullying, manage it and reduce its prevalence on social media. Many deep learning approaches to identify cyberbullying work by analyzing textual and user features. However, these techniques come with several limitations, which can significantly reduce their performance.
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