The functional intelligences proposition

Harnessing the benefits of diversity to address socio-environmental governance challenges

Solving complex problems, from biodiversity conservation to reducing inequality, requires large scale collective action among diverse stakeholders to achieve a common goal. Research relevant to meeting this challenge must model the interaction of stakeholders with diverse cognitive capabilities and the complexity of the problem faced by stakeholders to predict the success of collective action in various contexts. Here, we build a model from first principles of cognitive abilities, diversity, and socio-environmental complexity to identify the sets of conditions under which groups most effectively engage in collective action to solve governance problems. We then fit the model to small groups, U.S. states, and countries. Our model illustrates the fundamental importance of understanding the interaction between cognitive abilities, diversity, and the complexity of socio-environmental challenges faced by stakeholders today. Our results shed light on the ability of groups to solve complex problems and open new avenues of research into the interrelationship between cognition, institutions, and the environments in which they co-evolve.

Measuring Individual Differences in Measures of Autism Spectrum Disorders

Abstract. Previous research suggests that theory of mind tasks such as the Reading the Mind in the Eyes Test (RMET) are correlated with general intelligence ( g). The present study replicated and extended this research by testing correlations between g, the RMET, and two related measures, the empathy quotient (EQ) and systematizing quotient (SQ). The RMET, EQ, and SQ were all significantly correlated with g (r = .27 with RMET; r = −.15 with EQ; r = .27 with SQ). To determine if the RMET, EQ, and SQ derive their predictive power from g, a hierarchical regression examined whether the RMET, EQ, and SQ predicted feelings toward STEM and humanities after controlling for g. The EQ and SQ continued to significantly predict feelings toward STEM (β = −.20 for EQ; β = .42 for SQ) after controlling for g, and the RMET and EQ continued to significantly predict feelings toward humanities (β = .10 for RMET; β = .20 for EQ) after controlling for g, suggesting that these measures do not entirely derive their predictive power from g.

Social and general intelligence improves collective action in a common pool resource system

On a planet experiencing global environmental change, the governance of natural resources depends on sustained collective action by diverse populations. Engaging in such collective action can only build upon the foundation of human cognition in social-ecological settings. To help understand this foundation, we assess the effect of cognitive abilities on the management of a common pool resource. We present evidence that two functionally distinct cognitive abilities, general and social intelligence, improve the ability of groups to manage a common pool resource. Groups high in both forms of intelligence engage in more effective collective action that is also more consistent, despite social or ecological change. This result provides a foundation for integrating the effects of cognitive abilities with other dimensions of cognitive diversity to explain when groups will and will not sustainably govern natural resources.

The importance of cognitive diversity for sustaining the commons

Cognitive abilities underpin the capacity of individuals to build models of their environment and make decisions about how to govern resources. Here, we test the functional intelligences proposition that functionally diverse cognitive abilities within a group are critical to govern common pool resources. We assess the effect of two cognitive abilities, social and general intelligence, on group performance on a resource harvesting and management game involving either a negative or a positive disturbance to the resource base. Our results indicate that under improving conditions (positive disturbance) groups with higher general intelligence perform better. However, when conditions deteriorate (negative disturbance) groups with high competency in both general and social intelligence are less likely to deplete resources and harvest more. Thus, we propose that a functional diversity of cognitive abilities improves how effectively social groups govern common pool resources, especially when conditions deteriorate and groups need to re-evaluate and change their behaviors.

Social intelligence and general intelligence are two distinct cognitive abilities. Here, the authors show that groups of people with high competency in both social and general intelligence perform better in a resource-management task involving cooperation, and adjustment to unexpected ecological change.

Non-g Factors Predict Educational and Occupational Criteria: More than g

In a prior issue of the Journal of Intelligence, I argued that the most important scientific issue in intelligence research was to identify specific abilities with validity beyond g (i.e., variance common to mental tests) (Coyle, T.R. Predictive validity of non-g residuals of tests: More than g. Journal of Intelligence 2014, 2, 21–25.). In this Special Issue, I review my research on specific abilities related to non-g factors. The non-g factors include specific math and verbal abilities based on standardized tests (SAT, ACT, PSAT, Armed Services Vocational Aptitude Battery). I focus on two non-g factors: (a) non-g residuals, obtained after removing g from tests, and (b) ability tilt, defined as within-subject differences between math and verbal scores, yielding math tilt (math > verbal) and verbal tilt (verbal > math). In general, math residuals and tilt positively predict STEM criteria (college majors, jobs, GPAs) and negatively predict humanities criteria, whereas verbal residuals and tilt show the opposite pattern. The paper concludes with suggestions for future research, with a focus on theories of non-g factors (e.g., investment theories, Spearman’s Law of Diminishing Returns, Cognitive Differentiation-Integration Effort Model) and a magnification model of non-g factors.

Are greenhouse gas emissions and cognitive skills related? Cross-country evidence

Are greenhouse gas emissions (GHG) and cognitive skills (CS) related? We attempt to answer this question by exploring this relationship, using cross-country data for 150 countries, for the period 1997-2012. After controlling for the level of economic development, quality of political regimes, population size and a number of other controls, we document that CS robustly predict GHG. In particular, when CS at a national level increase by one standard deviation, the average annual rate of air pollution changes by nearly 1.7% (slightly less than one half of a standard deviation). This significance holds for a number of robustness checks.

Nonlinear Effects of Cognitive Ability on Economic Productivity

Abstract. Cognitive capitalism theory argues that the positive effects of cognitive ability on economic productivity should increase nonlinearly, with increases in ability amplifying increases in productivity. The theory was tested using country-level indicators of cognitive ability and productivity. Cognitive ability was based on international student assessments (e.g., Program for International Student Assessment, PISA), and productivity was based on economic inputs (e.g., scientific achievements and competitiveness) and outputs (e.g., gross domestic product). As predicted, the effects of cognitive ability on all productivity measures increased nonlinearly at higher levels of ability, suggesting that higher ability levels disproportionately boost a nation’s productivity. The findings are discussed in light of standard theories of cognitive ability (e.g., Spearman’s law of diminishing returns and differentiation theories), and suggest that interventions that boost cognitive ability can have large, amplifying effects on economic productivity.