The document discusses an intervention called edu Intervention that aims to raise high school graduation rates by identifying students most at risk of leaving school early. It does this by using data from the National Center for Education Statistics tracking over 26,000 attributes of 30,000 students to determine factors correlated with leaving, such as poor grades, disliking school, and leaving to work. A logistic regression is used to calculate probabilities of students leaving school based on identifiable factors like absences, math scores, number of schools attended, suspensions, and skipping class. The model is validated as being highly effective at identifying at-risk students.