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A predictive psychological health model for women performance at work

发表日期 March 21, 2023 (DOI: https://doi.org/10.54985/peeref.2303p4437930)

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作者

Femi Johnson1 , Oluwafolake Ojo1 , Adejimi Alaba1
  1. FEDERAL UNIVERSITY OF AGRICULTURE, ABEOKUTA

会议/活动

1st Annual ACM Celebration of Women in Computing in Africa: AfricaCWIC 2022, May 2022 (虚拟会议)

海报摘要

Employers have faced a significant issue in choosing employees for particular work roles. As a result of the perception that certain job positions are more commonly fit for one gender than another that has developed over time, more employees are being placed in incorrect job roles without taking into account some underlying elements that may affect their productivity. As an alternative, we only provide an artificially intelligent model with a high rate of prediction to assist in the identification of these elements and address the difficulties employers face in the selection and placement of workers for job tasks.

关键词

Work performance, Ratings, Artificial intelligence

研究领域

Computer and Information Science , Medical Imaging, Bioinformatics and Genomics

参考文献

  1. Braddy, P. W., Sturm, R. E., Atwater, L., & McKee, R. A. (2020). Gender Bias Still Plagues the Workplace: Looking at Derailment Risk and Performance With Self–Other Ratings.
  2. Frin, S.; Raihan,T.; Uddin, A.I.;Uddin, M.A. (2022). Predicting Innovative Work Behaviour in an Interactive Mechanism.
  3. Vonderlin R, Schmidt B, Müller G,Biermann M,Bohus M and Lyssenko L., (2021).Health-Oriented Leadership and Mental Health From Supervisor and Employee Perspectives: A Multilevel and Multisource Approach.

基金

暂无数据

补充材料

暂无数据

附加信息

利益冲突
No competing interests were disclosed.
数据可用性声明
The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.
知识共享许可协议
Copyright © 2023 Johnson et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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引用
Johnson, F., Ojo, O., Alaba, A. A predictive psychological health model for women performance at work [not peer reviewed]. Peeref 2023 (poster).
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