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Out of School and Off Track: The Overuse of Suspensions in American Middle and High Schools
Analyzing data from over 26,000 U.S. middle and high schools, the report reveals profound disparities in suspension rates when disaggregating data by race/ethnicity, gender, and disability status. The report identifies districts with the largest number of "hotspot" schools (suspending 25 percent or more of their total student body), suggests alternatives that are already in use, and highlights civil rights concerns
Fundamental Principles and Rights At Work: Value, Viability, Incidence and Importance as Elements For Economic Progress and Social Justice
Working Paper prepared for the ILO by Maria Luz Vega Ruiz and Daniel Martinez, focusing on the rights at work in Latin America and the Caribbean
Personalized Automatic Estimation of Self-reported Pain Intensity from Facial Expressions
Pain is a personal, subjective experience that is commonly evaluated through
visual analog scales (VAS). While this is often convenient and useful,
automatic pain detection systems can reduce pain score acquisition efforts in
large-scale studies by estimating it directly from the participants' facial
expressions. In this paper, we propose a novel two-stage learning approach for
VAS estimation: first, our algorithm employs Recurrent Neural Networks (RNNs)
to automatically estimate Prkachin and Solomon Pain Intensity (PSPI) levels
from face images. The estimated scores are then fed into the personalized
Hidden Conditional Random Fields (HCRFs), used to estimate the VAS, provided by
each person. Personalization of the model is performed using a newly introduced
facial expressiveness score, unique for each person. To the best of our
knowledge, this is the first approach to automatically estimate VAS from face
images. We show the benefits of the proposed personalized over traditional
non-personalized approach on a benchmark dataset for pain analysis from face
images.Comment: Computer Vision and Pattern Recognition Conference, The 1st
International Workshop on Deep Affective Learning and Context Modelin
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