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This chapter reviews the literature on social intelligence (SI) as it has evolved over the century since Thorndike (1920) popularized the concept. Most research on SI has been guided by an ability view, and an analogy to IQ, as exemplified by the George Washington University Social Intelligence Test, and the “behavioral” contents in Guilford’s Structure of Intellect. The assessment of SI is important for the assessment of intellectual disability (mental retardation) and the autistic spectrum, but raises the question of whether SI is a qualitatively different form of intelligence, or simply general intelligence applied in social situations. The chapter proposes an alternative knowledge view of SI as the fund of declarative and procedural knowledge which the individual brings to bear on social interactions, especially in the pursuit of important life tasks.
Theoretical models of memory retrieval have focused on processes of recollection and familiarity. Research suggests that there are still other processes involved in memory reconstruction, leading to experiences of knowing and inferring the past. Understanding these experiences, and the cognitive processes that give rise to them, seems likely to further expand our understanding of the neural substrates of memory.
Jussim's critique of social psychology's embrace of error and bias is needed and often persuasive. In opting for perceptual realism over social constructivism, however, he seems to ignore a third choice – a cognitive constructivism which has a long and distinguished history in the study of nonsocial perception, and which enables us to understand both accuracy and error.
The biological basis for electroencephalogram (EEG)/average evoked potential (AEP) correlations to intelligence measures is not yet clear. Neural transmission speed (often measured as nerve conduction velocity) and the degree of myelination surrounding neurons have been proposed as potentially important variables for individual differences in intelligence. This chapter discusses neuroimaging studies that include positron emission tomography (PET), magnetic resonance imaging (MRI), and parieto-frontal integration theory (P-FIT) model of intelligence to emphasize the importance of information flow. Structural neuroimaging studies with large samples continue to relate intelligence to brain development. A number of new functional imaging studies use sophisticated experimental designs to examine cognitive and psychometric components of intelligence. The combination of neuroimaging and genetic research is one of the most powerful new approaches to understanding the neural basis of intelligence. Studies show that regional gray matter and white matter are largely under genetic control and share common genes with intelligence.
This chapter provides an overview of existing computational (mechanistic) models of cognition in relation to the study of consciousness, on the basis of psychological and philosophical theories and data. It begins by examining some foundational issues concerning computational approaches toward consciousness. Then, various existing models and their explanations of the conscious/unconscious distinction are presented. Work in the area of computational modeling of consciousness generally assumes the sufficiency and the necessity of mechanistic explanations. The chapter looks into some details of two representative computational models, exemplifying either two systems or one-system views. Various related issues, such as the utility of computational models, explanations of psychological data, and potential applications of machine consciousness, have been touched on in the process. Based on existing psychological and philosophical evidence, existing models were compared and contrasted to some extent.
By conflating Freudian repression with thought suppression and memory reconstruction, Erdelyi defines repression so broadly that the concept loses its meaning. Worse, perhaps, he fails to provide any evidence that repression actually happens, and ignores evidence that it does not.
Wegner's many examples of illusory involuntariness do not warrant the conclusion that the experience of voluntariness is also an illusion. His arguments appear to be related to the contemporary emphasis on automaticity in social cognition and behavior; both appear to represent a revival of situationism in social psychology.
This commentary notes the emergence of a “People are Stupid” school of thought that describes social behavior as mindless, automatic, and unconscious. I trace the roots of this “school,” particularly in the link between situationism in social psychology and behaviorism in psychology at large, and suggest that social psychology should focus on the role of the mind in social interaction.
The capacity to know oneself and to know others is an inalienable a part of the human condition as is the capacity to know objects or sounds, and it deserves to be investigated no less than these other “less charged” forms.
Howard Gardner (1983, p. 243) Frames of Mind
Intelligence, as defined in standard dictionaries, has two rather different meanings. In its most familiar meaning, intelligence denotes the individual's ability to learn and reason. It is this meaning that underlies common psychometric notions such as intelligence testing, the intelligence quotient, and the like. In its less common meaning, intelligence refers to a body of information and knowledge. This second meaning is implicated in the titles of certain government organizations such as the Central Intelligence Agency in the United States and its British counterparts MI–5 and MI–6. Similarly, both meanings are invoked by the concept of social intelligence. As originally coined by E. L. Thorndike (1920), the term referred to the person's ability to understand and manage other people and to engage in adaptive social interactions. More recently, however, Cantor and Kihlstrom (1987) redefined social intelligence as the individual's fund of knowledge about the social world.
THE PSYCHOMETRIC VIEW
The psychometric view of social intelligence has its origins in E. L. Thorndike's (1920) division of intelligence into three facets: the ability to understand and manage ideas (abstract intelligence), concrete objects (mechanical intelligence), and people (social intelligence).
Statistical significance testing has its problems, but so do
the alternatives that are proposed; and the alternatives may be both
more cumbersome and less informative. Significance tests remain
legitimate aspects of the rhetoric of scientific persuasion.
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