Understanding the relationship between rationality and intelligence: a latent-variable approach

被引:10
|
作者
Burgoyne, Alexander P. [1 ]
Mashburn, Cody A. [1 ]
Tsukahara, Jason S. [1 ]
Hambrick, David Z. [2 ]
Engle, Randall W. [1 ]
机构
[1] Georgia Inst Technol, Atlanta, GA 30332 USA
[2] Michigan State Univ, E Lansing, MI 48824 USA
关键词
Rationality; intelligence; attention control; working memory capacity; fluid intelligence; WORKING-MEMORY CAPACITY; DUAL-PROCESS THEORIES; GENERAL FLUID INTELLIGENCE; COGNITIVE REFLECTION TEST; SHORT-TERM-MEMORY; INDIVIDUAL-DIFFERENCES; EXECUTIVE ATTENTION; HEURISTICS; JUDGMENT; BIASES;
D O I
10.1080/13546783.2021.2008003
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
A hallmark of intelligent behavior is rationality - the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a sample of 331 participants, we assessed the relationship between rationality and intelligence. There was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.
引用
收藏
页码:1 / 42
页数:42
相关论文
共 50 条
  • [41] Modeling the Diving Behavior of Whales: A Latent-Variable Approach with Feedback and Semi-Markovian Components
    Langrock, Roland
    Marques, Tiago A.
    Baird, Robin W.
    Thomas, Len
    [J]. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 2014, 19 (01) : 82 - 100
  • [42] Exposure Assessment for Pesticide Intake from Multiple Food Products: A Bayesian Latent-Variable Approach
    Chatterjee, Ayona
    Horgan, Graham
    Theobald, Chris
    [J]. RISK ANALYSIS, 2008, 28 (06) : 1727 - 1736
  • [43] Measuring human capital in South Africa across socioeconomic subgroups using a latent-variable approach
    Friderichs, Tj
    Correa, F. M.
    [J]. SOCIAL INDICATORS RESEARCH, 2022, 164 (03) : 1161 - 1185
  • [44] Heterogenous data fusion via a probabilistic latent-variable model
    Yu, K
    Tresp, V
    [J]. ORGANIC AND PERVASIVE COMPUTING - ARCS 2004, 2004, 2981 : 20 - 30
  • [45] MCMC Sampling on Latent-Variable Space of Mixture of Probabilistic PCA
    Yamazaki, Keisuke
    [J]. 6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS, 2012, : 1508 - 1513
  • [46] Tensors over Semirings for Latent-Variable Weighted Logic Programs
    Balkir, Esma
    Gildea, Daniel
    Cohen, Shay B.
    [J]. 16TH INTERNATIONAL CONFERENCE ON PARSING TECHNOLOGIES AND IWPT 2020 SHARED TASK ON PARSING INTO ENHANCED UNIVERSAL DEPENDENCIES, 2020, : 73 - 90
  • [47] ON THE EFFECTIVENESS OF TWO-STEP LEARNING FOR LATENT-VARIABLE MODELS
    Subakan, Cem
    Gasse, Maxime
    Charlin, Laurent
    [J]. PROCEEDINGS OF THE 2020 IEEE 30TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2020,
  • [48] Nonparametric estimation of non-exchangeable latent-variable models
    Bonhomme, Stephane
    Jochmans, Koen
    Robin, Jean-Marc
    [J]. JOURNAL OF ECONOMETRICS, 2017, 201 (02) : 237 - 248
  • [49] Estimating Latent-Variable Graphical Models using Moments and Likelihoods
    Chaganty, Arun Tejasvi
    Liang, Percy
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 32 (CYCLE 2), 2014, 32 : 1872 - 1880
  • [50] Latent-Variable Modelling of Ordinal Outcomes in Language Data Analysis
    Soenning, Lukas
    Krug, Manfred
    Vetter, Fabian
    Schmid, Timo
    Leucht, Anne
    Messer, Paul
    [J]. JOURNAL OF QUANTITATIVE LINGUISTICS, 2024, 31 (02) : 77 - 106