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020 ▼a 9780438168527
035 ▼a (MiAaPQ)AAI10822746
035 ▼a (MiAaPQ)umn:19181
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 150
1001 ▼a Yu, Martin C.
24510 ▼a Viewing Expert Judgment in Individual Assessments Through the Lens Model: Testing the Limits of Expert Information Processing.
260 ▼a [S.l.] : ▼b University of Minnesota., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 124 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Nathan R. Kuncel.
5021 ▼a Thesis (Ph.D.)--University of Minnesota, 2018.
520 ▼a The predictive validity of any assessment system is only as good as its implementation. Across a range of decision settings, algorithmic methods of data combination often match or outperform the judgmental accuracy of expert judges. Despite this
520 ▼a Based on archival assessment data from an international management consulting firm, this dissertation presents three related studies with an overarching goal of better understanding the processes underlying why expert judgment tends to be less a
520 ▼a Taken together, these results suggest that the suboptimal and inconsistent ways that expert assessors combine assessment information is drastically hampering their ability to make accurate evaluations of assessment candidates and to predict cand
590 ▼a School code: 0130.
650 4 ▼a Psychology.
650 4 ▼a Occupational psychology.
650 4 ▼a Organizational behavior.
690 ▼a 0621
690 ▼a 0624
690 ▼a 0703
71020 ▼a University of Minnesota. ▼b Psychology.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0130
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998506 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자