Gender differences in under-reporting hiring discrimination in Korea: a machine learning approach.

Journal: Epidemiology and health
Published Date: Nov 17, 2021

Abstract

OBJECTIVES: This study was conducted to examine gender differences in under-reporting hiring discrimination by building a prediction model for workers who responded "not applicable (NA)" to a question about hiring discrimination despite being eligible to answer.

Authors

  • Jaehong Yoon
    Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
  • Ji-Hwan Kim
    Department of Public Health Sciences, Graduate School of Korea University, Seoul, Korea.
  • Yeonseung Chung
    Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  • Jinsu Park
    Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  • Glorian Sorensen
    Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Seung-Sup Kim
    Department of Public Health Sciences, Graduate School of Korea University, Seoul, Korea.

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