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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM39657
Volume:
8 |
12 |
Dec 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The need for inclusive hiring across sectors has increased with the rapidly increasing numbers of diverse and rapidly evolving process markets. The current paper considers data-driven methods toward fair and unbiased recruitment. In fact, the goal of ensuring a level playing field among all applicants, regardless of gender, ethnicity, or background, drives this research. We examine ways to include complex algorithms to reduce unconscious biases. Bias, systems designed to anonymize applicant information, and instruments for developing inclusive job descriptions. We also evaluate data-driven tracking systems monitoring diversity metrics and areas for continuous improvement and innovative methodologies for the unbiased evaluation of governmental examination results. This paper synthesizes recent research and emerging solutions to focus attention on the importance of transparency, accountability, and inclusion in the hiring process. Practices across public and personal sectors. in the long run, this look at seeks to encourage groups to enforce actionable techniques that mirror and assist the range of the groups they serve
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Publication Date
12/14/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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