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Essay submissions to standardized tests like the ACT occasionally includereferences to bullying, self-harm, violence, and other forms of disturbingcontent. Graders must take great care to identify cases like these and decidewhether to alert authorities on behalf of students who may be in danger. Thereis a growing need for robust computer systems to support human decision-makersby automatically flagging potential instances of disturbing content. This paperdescribes MTLHealth, a disturbing content detection pipeline built aroundrecent advances from computational linguistics, particularly pre-trainedlanguage model Transformer networks.

MTLHealth: A Deep Learning System for Detecting Disturbing Content in Student Essays