IQ score and the “seduction of quantification”: Concise overview of the historical #eugenics use of #IQ and emerging new conceptualizations—#g #WJV #CHC #POT #processoverlap #schoolpsychology #schoolpsychologists #emergentproperty

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I stumbled on this relatively concise article that provides a nice (and brief) overview of the historical “bad days” of IQ test and score misuse.  Don’t let the title’s focus on epilepsy deter you from reading—the content is relevant to thinking about intelligence and IQ scores in general.  After the succinct overview of the horrible historical uses of IQ tests and scores, the article touches on contemporary theories and thinking (e.g., process overlap theory or POT; CHC cognitive abilties theory) that view the IQ score as nothing more than a statistical emergent property index—and the need to focus on broad CHC abilities from cognitive ability tests. 

Recommended reading--available as open access here. 

Click here for prior relevant post about IQ scores being emergent property scores.  Click here for WJ V authors view’s on relevance of global IQ scores.  See recent McGrew et al. (2023) article for more information and discussion.

Journal of Intelligence “Best Paper Award” for McGrew, Schneider, Decker & Bulut (2023) Psychometric network analysis of CHC measures - #psychometric #networkanalysis #intelligence #CHC #WJIV #bestpaper #schoolpsychology #schoolpsychologist

Today I (Kevin McGrew), and colleagues Joel Schneider, Scott Decker, and Okan Bulut, were pleased to learn that our recent 2023 Journal of Intelligence article listed above (open access—click link to read or download) was selected as 1 of 2 “Best Paper Awards” for 2023.  

As stated at the journal award page, “The Journal of Intelligence Best Paper Award is granted annually to highlight publications of high quality, scientific significance, and extensive influence. The evaluation committee members choose two articles of exceptional quality that were published in the journal the previous year and announce them online by the end of June.”

Below is the abstract and two figures that may pique your interest. We thank the members of the JOI evaluation committee.

Abstract

For over a century, the structure of intelligence has been dominated by factor analytic methods that presume tests are indicators of latent entities (e.g., general intelligence or g). Recently, psychometric network methods and theories (e.g., process overlap theory; dynamic mutualism) have provided alternatives to g-centric factor models. However, few studies have investigated contemporary cognitive measures using network methods. We apply a Gaussian graphical network model to the age 9–19 standardization sample of the Woodcock–Johnson Tests of Cognitive Ability—Fourth Edition. Results support the primary broad abilities from the Cattell–Horn–Carroll (CHC) theory and suggest that the working memory–attentional control complex may be central to understanding a CHC network model of intelligence. Supplementary multidimensional scaling analyses indicate the existence of possible higher-order dimensions (PPIK; triadic theory; System I-II cognitive processing) as well as separate learning and retrieval aspects of long-term memory. Overall, the network approach offers a viable alternative to factor models with a g-centric bias (i.e., bifactor models) that have led to erroneous conclusions regarding the utility of broad CHC scores in test interpretation beyond the full-scale IQ, g.

Keywords: 

CHC; Cattell–Horn–Cattell theory; intelligence; cognitive abilities; psychometric network analysis; process overlap theory; dynamic mutualism; factor analysis; general intelligence

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McGrew on #IQ scores: In what ways are a car engine, a starling bird #murmuration, and #g (general #intelligence) alike..how are they the same?

Kevin McGrew on IQ scores, borrowing from Detterman (2016) and McGrew et al., (2023)

“General intelligence (represented by a composite IQ score or the factor-analysis derived psychometirc g factor) is a fallible summary statistical (numerical) index of the efficiency of a complex system of dynamically interacting multiple brain networks.  Like the emergent statistical index of horsepower of a car engine, which does not represent a “thing” (a mechanism) in the engine, it reflects the current estimated efficiency of the processing of multiple interacting cognitive abilities and brain networks. It should not be interpreted as being the result of a single brain-based entity or mystical mental energy, as fixed, or reflecting biological/genetic destiny.  The manifest expression of this statistical emergent property index is also influenced by other non-cognitive (conative) (click for relevant article) traits and temporary states of the individual and current environmental variables” (K. McGrew, 11-07-24)

Question.  In what ways are a car engine, a starling bird murmuration, and general intelligence alike..how are they the same?  See slides and comments below for answer

 

(A starling bird murmuration)

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A Psychometric Network Analysis of CHC Intelligence Measures: Implications for Research, Theory, and Interpretation of Broad CHC Scores "Beyond g"

(Note.  I’ve made several similar posts with a similar message on several social media outlets over the last 1.5 years)

Yes.  This may be seen as a brag post (I plead the fifth). But, I really want (need?) to share this recent publication (January 2023).  Why? Because, after 40 years of scholarship, I consider this article (which is open access and can be downloaded and read freely) to be one of my 5 top peer-reviewed research publications. The article is part of a special issue (Assessment of Human Intelligence-State of the Art in the 2020s) of the Journal of Intelligence, edited by Alan Kaufman et al. Warning—it is a long article. The article is the result of collaboration with Joel Schneider, Scott Decker and Okan Bulut. 

The content of the article pushes the “edge of the envelop” regarding intelligence theories and testing via the use of exploratory psychometric network analysis (PNA) within the context of network non-g (i.e., psychometric g) models of intelligence. This approach represents an emerging paradigm shift for thinking about intelligence theories and testing. As stated by Savi et al. (2021) "factor analysis models dominated the 20th century of intelligence research, but network models will dominate the 21st."  I believe Savi et al. are more-or-less correct. I believe PNA and non-g network models can move intelligence theories and testing forward—as they have become stagnant via the repeated use of "common cause" descriptive and taxonomic-generating factor analysis methods.  Used in isolation, factor analysis-based intelligence test and theory models constrain school psychologists and other assessment professionals from moving forward (as described in the paper).  For far too long, especially in school psychology, we have been "stuck on g" factor analysis based models of test interpretation.

As stated in our article, "newer non-g emergent property theories of intelligence might lead to better intervention research for individuals who have been marginalized by society. Holden and Hart (2021) suggest that network-based non-g theories, particularly those that feature Gwm-AC mechanisms [the working memory-attentional control complex] (process overlap theory in particular) may hold promise as a vehicle for improving, and not harming, social justice and equity practices and valued outcomes for individuals in marginalized groups" (McGrew et al., 2023).  Read the original Holden and Hart article if you are interested in the social justice implications of a new way of thinking about intelligence grounded in modern network non-g conceptualizations of intelligence.

Even if the methodological material is not your cup of tea, much of the McGrew et al. (2023) introduction is relevant to assessment practitioners. Also, several sections in the discussion deal with practical implications for understanding new insights into intelligence theories, broad cluster test interpretation in general, and some strengths and weaknesses of the WJ IV CHC test and cluster scores. 

If you are not familiar with the Journal of Intelligence (JOI), I would suggest SPs take a look. It is not the Intelligence journal from ISIR. It is the "new kid on the block" and has quickly become a prestigious open access publication outlet with a top notch editorial board. Since it is open access, all articles can be downloaded, read, and shared freely—an awesome free source of emerging thinking in the field of intelligence. JOI is publishing interesting articles from a wide variety of perspectives by a diversity of scholars interested in intelligence, cognition, and related topics. It has become one of my favorite journals the past few years. 

Finally, exploratory hierarchical psychometric network analysis methods (along with traditional structural analysis methods) were applied to the WJ V norm data—these results will be in the WJ V Technical Manual (LaForte, Dailey, McGrew, 2025).

 My WJ IV conflict of interest (COI) is included in the linked PDF article.  My WJ V COI and additional COI information can be found at the MindHub web portal.