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Cited by 321

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Scientific and Social Significance of Assessing Individual Differences: “Sinking Shafts at a Few Critical Points”

Lubinski, David·2000·Annual Review of Psychology
DOI 10.1146/annurev.psych.51.1.405
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Abstract

This chapter reviews empirical findings on the importance of assessing individual differences in human behavior. Traditional dimensions of human abilities, personality, and vocational interests play critical roles in structuring a variety of important behaviors and outcomes (e.g. achieved socioeconomic status, educational choices, work performance, delinquency, health risk behaviors, and income). In the review of their importance, the construct of general intelligence is featured, but attributes that routinely add incremental validity to cognitive assessments are also discussed. Recent experimental and methodological advances for better understanding how these dimensions may contribute to other psychological frameworks are reviewed, as are ways for determining their scientific significance within domains where they are not routinely assessed. Finally, some noteworthy models are outlined that highlight the importance of assessing relatively distinct classes of individual-differences attributes simultaneously. For understanding fully complex human phenomena such as crime, eminence, and educational-vocational development, such a multifaceted approach is likely to be the most productive.

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Metadata

Authors
Lubinski, D.
Venue
Annual Review of Psychology
Publisher
Annual Reviews
Published
2000-02
Volume
51
Issue
1
Pages
405-444
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
DOI
10.1146/annurev.psych.51.1.405
OpenAlex
W2100189411
Cited by
321
References
16
FWCI
2.95
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.