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A dynamical model of general intelligence: The positive manifold of intelligence by mutualism.
Abstract
Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biological process or capacity. In this article, a new explanation of the positive manifold based on a dynamical model is proposed, in which reciprocal causation or mutualism plays a central role. It is shown that the positive manifold emerges purely by positive beneficial interactions between cognitive processes during development. A single underlying g factor plays no role in the model. The model offers explanations of important findings in intelligence research, such as the hierarchical factor structure of intelligence, the low predictability of intelligence from early childhood performance, the integration/differentiation effect, the increase in heritability of g, and the Jensen effect, and is consistent with current explanations of the Flynn effect.
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“However, as dynamic effects can amplify over developmental time44, they are nonetheless worth understanding and addressing with care.”
From Windows of developmental sensitivity to social media (2022) · cites this paper as [44]
In the citing paper
“overall cognitive capacities including crystallized and fluid composites, despite there being distinctions between them, have modest associations with each other, and can be summarized by a higher-order common factor (general intelligence) (Lovden, Fratiglioni, Glymour, Lindenberger, & Tucker-Drob, 2020; Lubinski, 2004; van der Maas et al., 2006).”
From Early-Initiated Childhood Reading for Pleasure: Associations with Better Cognitive Performance, Mental Well-being and Brain Structure in Young Adolescence (2024) · cites this paper as van der Maas et al., 2006
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“The network approach is different; it does not assume an a priori structure of motivation factors.Instead, it uses the (bidirectional) partial correlations between variables in empirical data and in doing so clusters of variables which can be interpreted as constructs may emerge.”
From Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda (2022) · cites this paper as van der Maas et al., 2006
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Metadata
- Authors
- Van Der Maas, H. L. J., Dolan, C. V., Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J.
- Affiliations
- University of Amsterdam (NL)
- ORCID
- Venue
- Psychological Review
- Published
- 2006
- Volume
- 113
- Issue
- 4
- Pages
- 842-861
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2100107646
- Cited by
- 1,006
- References
- 125
- Citations by year
- 2026: 54 · 2025: 53 · 2024: 66 · 2023: 79 · 2022: 79 · 2021: 78 · 2020: 128 · 2019: 61 · 2018: 64 · 2017: 45 · 2016: 45 · 2015: 54 · 2014: 35 · 2013: 28 · 2012: 36
- FWCI
- 20.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- VU Research Portal (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
- Keywords
- general intelligence, dynamic modeling, mutualism, reciprocal causation, cognitive processes, hierarchical factor structure, heritability of intelligence, Flynn effect
- MeSH terms
- Humans, Intelligence, Models, Psychological, Psychology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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