Chapter 40
The General Factor of Personality: A Hierarchical Life History Model

Aurelio José Figueredo, Michael A. Woodley of Menie, and W. Jake Jacobs

In this chapter, we first review the theoretical orientation, content, and conclusions of a previous chapter that our group contributed to the first edition of this Handbook (Buss, 2005). The previous version of this chapter contained three major theoretical threads of reasoning that provided form and substance to our review of personality theory from an evolutionary perspective: (1) personality traits are systematically related to fitness-relevant life outcomes, and are thus subject to various selective pressures; (2) the persistence of individual differences in personality in the face of these selective pressures can be attributed to intraspecific character displacement as a consequence of the splitting of individual micro-niches under conditions of sociality; and (3) the evolutionary significance of the fitness-relevant life outcomes in these contexts, and therefore of the corresponding personality traits themselves, can best be understood within the theoretical framework of life history theory.

Anchored in a body of literature that has arisen primarily over the past 10 years or so, we now extend these approaches to consider the evolutionary significance of a newly documented phenomenon, the so-called General Factor of Personality (GFP). We review the history of the concept and most of the recent empirical literature on the topic. Finally, we review and evaluate several recent attempts to test a hierarchical model of life history strategy designed to encompass and account for the dynamics of the GFP.

Evolutionary Theories of Personality Revisited

Our chapter in the first edition of this Handbook described three classes of theory accounting for the evolution of personality and individual differences in humans. The first, theories of selective neutrality, are best exemplified by Tooby and Cosmides (1990), who suggested that humans have an innate and universally evolved psychology, and that individual differences in personality result from essentially random ontogenetic variations in the expression of universals, whereas cultural-group differences result from the specific evocation of human universals given geographic variation in evolutionarily familiar challenges (i.e., variations in parasite-load evoke different levels of collectivism-individualism as an adaptive response). In the environment of evolutionary adaptedness, psychological adaptations are complex and coordinated with one another as part of a larger integrated functional design. Tooby and Cosmides suggest that evidence for the heritability of personality supports this theory, and as such, personality variation is a result of the environment.

The second class, theories of adaptive significance, includes theories proposed by Buss (1991) and G. F. Miller (2000b) and extended by others. Buss (1991) proposed that personality is central to social interactions and individual differences in personality; specifically, the Five-Factor Model (FFM) of personality reflects distinct adaptive strategies. G. F. Miller (2000b) extended Buss's theory and suggested that individual differences in personality require both natural selection and sexual selection to explain their existence. Weiss, King, and Enns (2002) extended G. F. Miller's (2000b) theory by pointing to research indicating that fitness-enhancing characteristics are correlated with one another, the combination of which they named covitality, and suggesting that potential mates use the presence of one fitness-enhancing trait to indicate the presence of others. MacDonald (1998) proposed that individual differences in personality are based on a “continuous distribution of phenotypes that matches a continuous distribution of viable strategies” (p. 142), and assuming relative levels of fitness are equal, these differences allow individuals to occupy a variety of environmental niches.

The third class of theory, theories of frequency dependence, includes theories proposed by Wilson (1994) and Figueredo and King (2001). Wilson (1994) proposed that there are two types of individuals: generalists, individuals who can moderately adapt to a variety of niches, and specialists, those who are adapted to do well in a specific niche. Wilson suggested that individuals evaluate and choose niches based on the presumed adaptive benefit those niches offer and that an individual's fitness depends on (a) the number of individuals simultaneously occupying one's niche and (b) the traits those individuals exhibit. Figueredo and King (2001) proposed that social competition further leads to individual differences in personality, which they explained through four points. First, each of the five dimensions of the FFM has a pole (e.g., high extraversion) that enhances fitness and thus, through directional selection, leads towards an “ideal.” Frequency-dependent selection disrupts this process, however, because an overabundance of individuals at the ideal end of the pole creates a niche for individuals at the opposite end on that pole (e.g., low extraversion). Second, frequency-dependent selection pressures vary across personality dimensions depending on the traits expressed by individuals in a particular niche, leading to increased personality variation. Third, interactions between the FFM dimensions within individuals might finally lead to further observed individual differences in personality. Finally, environments with dense social interactions amplify these pressures (see Figueredo, Sefcek, et al., 2005).

Attempted Empirical Tests of Evolutionary Personality Theories

Although limited, research regarding personality in nonhuman animals indicates the existence of personality dimensions, similar to the FFM observed in humans, in many species (e.g., Gosling & John, 1999). In addition, some comparative research (e.g., between chimpanzees and humans; King & Figueredo, 1997) indicates similar personality factor structures as well. The extent to which personality traits remain stable across time and situations is debated; much of the research (e.g., Stevenson-Hinde, Stillwell-Barnes, & Zunz, 1980a, 1980b), however, suggests personality traits are relatively stable across the lifespan. Finally, the empirical evidence indicates the majority of those species in which personality has been documented are social, supporting the coral reef model of intraspecific character displacement based on niche splitting for the disruptive social selection of individual differences in personality proposed first by Figueredo (1995) and further elaborated by Figueredo and King (2001; see also Figueredo, Sefcek, et al., 2005, for a more fully developed treatment of the quantitative-ecological foundations of this theory). This association of personality with sociality was generally supported by the published data then available, with the notable exception of certain species of cephalopods, such as the octopus.

More recently, the researcher who first documented the existence of substantial individual differences among octopus personalities reported new data suggesting that intraspecific trophic specialization occasioned by social competition for resources might cause such systematic variation in individual behavior (Mather et al., 2012). Generalist species (such as Octopus vulgaris, Octopus cyanea, and Enteroctopus dofleini) appear to be composed of specialist individuals, each of whom concentrates upon a limited variety of prey, whereas the population in the aggregate is spread out ecologically over a broad range of prey. Thus, cephalopod behavioral differentiation may also serve the ultimate adaptive function of competitive release, and, as such, no longer constitutes the principal exception to this theory.

In humans, the preponderance of empirical results support the inference that personality is related to both (a) actual and completed survivorship (i.e., life expectancy) and (b) actual and completed fecundity (i.e., expected fertility). For example, regarding the relation of personality to survivorship, various studies have found that individuals higher on conscientiousness are more likely to experience increased longevity (e.g., Friedman, 2000), presumably because these individuals are more likely to engage in health-enhancing behaviors. Moreover, a meta-analysis of the literature (Friedman & Booth-Kewley, 1987) found that depression and anxiety (associated with high neuroticism) as well as anger and hostility (associated with low agreeableness) and many health problems, including coronary heart disease and asthma, are statistically related. Another such example, this time regarding the relation between personality and fecundity, was found by Eaves, Martin, Heath, Hewitt, and Neale (1990), who studied 1,000 postmenopausal women and found that highest reproductive success was associated with either high neuroticism and low extraversion or high extraversion and low neuroticism, and by Hellhammer, Hubert, Phil, Freischem, and Nieschlag (1985), who found that higher levels of self-confidence, extraversion, and social assertiveness correlate negatively with male fertility.

In addition, sexual selection affects the evolution of personality traits. Sexual selection can be divided into intrasexual competition and mate choice. The dearth of evidence regarding relations between personality and intrasexual competition precludes its discussion here, so instead we focus on evidence specific to mate choice.

There are two approaches to the relation between mate choice and personality. The first approach defines preferences as absolute and consensual, suggesting preferences are similar for all individuals. For example, across nations men and women rate kindness and understanding (possibly associated with agreeableness) and intelligence as the first and second most desired characteristics in a romantic partner, respectively (Buss, 1985, 1989). The second approach views preferences as relative to one's own personality, and individuals either positively assortatively mate, by selecting a partner who is similar, or negatively assortatively mate, by selecting a partner who is dissimilar or complementary to their own personality. Positive assortative mating has been found for a variety of characteristics, both those typically considered desirable, such as affectivity, emotional expression, and personality (Gonzaga, Carter, & Buckwalter, 2010) and those typically considered undesirable, such as Machiavelliansim (Novgorodoff, 1974). In addition, evidence for disassortative mating has been found for mating effort, intentions towards infidelity, and self-monitoring (Olderbak & Figueredo, 2012). In one recent naturalistic observational study (Figueredo et al., in press), statistically significant and generally equivalent positive assortative mating coefficients among social and romantic partners have been documented in four Western cultures on several reproductively relevant traits, including life history (LH) strategy; in a quasi-experimental follow-up (Olderbak, Wolf, & Figueredo, 2014), absolute and relative partner preferences were compared with one another and found each to be simultaneous predictors of perceived relationship satisfaction.

To be consistent with the frequency-dependent selection model of personality traits, the personality phenotype must vary inversely with its relative frequency in the population, such that rarer phenotypes have higher fitness (Tooby & Cosmides, 1990). Indirect evidence of this phenomenon can be found under circumstances where personality variation and reproductively relevant traits are related and subject to frequency-dependent selection. To demonstrate frequency-dependent selection, however, requires the explicit consideration of the fitness gains and losses of the behavioral manifestation of personality traits.

Personality Traits as Resource Allocations

LH theory proposes that different traits are desirable depending on the environmental circumstances, with individuals from stable and predictable environments more likely to develop a slow LH strategy, characterized by long-term romantic relationships, few children, and long-term planning, whereas individuals from unstable and unpredictable environments are more likely to develop a fast LH strategy, characterized by many short-term romantic relationships, many children with different partners, and short-term planning (Figueredo, Vásquez, et al., 2006). Multiple studies demonstrate the predicted relation between personality and LH strategy (e.g., Figueredo, Sefcek, et al., 2005), suggesting that the various selective pressures on personality traits might be generated as a consequence of LH evolution. This immediately raises the question of how and why personality traits should be governed by LH strategy.

Personality traits all require the expenditure of bioenergetic and material resources on the part of the individual to behaviorally enact. For example, extraversion is not just a passive “trait” that one possesses or does not possess; extraversion reflects an identifiable pattern of behavior that entails one engaging in elevated levels of social verbal and nonverbal behaviors, highly proactive social interactions, and (at least according to Eysenck, 1976) frequent sexual “philandering.” All of this “extraverted” behavior requires energy to implement. Similarly, agreeableness is not just a passive “trait” that one either has or does not have; agreeableness reflects an equally identifiable pattern of behavior that entails that one engage in elevated levels of verbal and nonverbal socially altruistic behaviors, as well as highly proactive interpersonal engagement and perception for determining the needs and desires of others to optimize the strategic allocation of one's altruistic efforts to maximally “please” and ingratiate oneself with other individuals. All of this “agreeable” behavior requires energy to implement. We can go on, but our point is made.

LH strategy regulates the allocation of the bioenergetic and material resources available to the individual, not only the level of total effort to be expended socially, but also the specific budget for allocating relative amounts of social investment across the various competing adaptive domains (as can be taxonomically partitioned by various models of personality structure, such as the FFM). Moreover, the optimality of such resource allocations must, according to evolutionary theory, ultimately serve to maximize fitness. This understanding situates the latent structure of personality solidly within the nomological network of LH strategy, providing a much-needed alternative to the mostly empirically based (rather than theoretically grounded) taxonomies that have been prevalent historically in personality psychology. This understanding also implies that an explicitly hierarchical model of both personality in specific and LH strategy in general is required.

The Principle of Brunswik-Symmetry

Recall that both higher-order and lower-order personality factors are latent hypothetical constructs (also known as latent variables when operationalized) that psychometricians typically operationalize as multivariate common factors. Hence, latent constructs are not directly observable; instead, we infer their existence from the covariance structure of their observable consequences (called manifest indicators or manifest variables, because psychometricians reconstruct the presumably underlying latent causes from the measurable effects of these hypothetical latent constructs).

As latent constructs are theoretical entities, the relations among them have historically been matters of great controversy. Personality theorists have even debated their number as well as the optimal levels of data aggregation that should be used to construct them.

One appealing solution to this conundrum is the principle of Brunswik-Symmetry (Brunswik, 1952; Wittmann, 2012), which presumes that at a deep level, all biological structures are hierarchically organized. Given that psychological phenomena must be viewed as a subset of biological phenomena, the hierarchical principle of Brunswik-Symmetry is a necessary component of personality theory. For example, the anatomical and physiological structure of the brain shows unmistakable evidence of hierarchical organization. It should therefore not be surprising if behavioral output that the brain organizes also reflects this inherently hierarchical structure. Mayr (1982) best expressed this general principle:

In such a hierarchy the members of a lower level, let us say tissues, are combined into new units (organs) that have unitary functions and emergent properties.…At each level there are different problems, different questions to be asked, and different theories to be formulated. Each of these levels has given rise to a separate branch of biology; molecules to molecular biology, cells to cytology, tissues to histology, and so forth, up to biogeography and the study of ecosystems. (p. 65)

In fact, the hierarchical principle also extends downwards through even lower levels of organization because nonliving matter also shows similar patterns of aggregation downwards through molecules, to atoms, to subatomic particles, to quarks, to (possibly) strings, to (even more speculatively) quantum-relativistic fields, and who knows what else that is even smaller.

The obvious implication of this reasoning renders moot the question of what is the “true” number of personality factors that underlie the latent structure of the empirical data. The answer depends on the level of data aggregation desired, because the structure resembles that of a Christmas tree to which one can take one's psychometric chainsaw at any of various key points along the major axis. Thus, the “true number of personality factors” construction of the problem becomes a meaningless question and is replaced by what is the optimal level of data aggregation for a particular application. This does not mean that the answer to this better-formulated question is an arbitrary or whimsical one, because the principle of Brunswik-Symmetry outlines a pragmatic strategy for specifying precisely which level of data aggregation is optimal for any given problem.

Simply put, both a predictor variable (putative cause) and a criterion variable (putative effect) in any problem are necessarily embedded in a particular level of aggregation for the construct indicated by those measures. The principle of Brunswik-Symmetry involves a mathematical proof that any given level of aggregation will optimize the correlation between predictor and criterion, as long as the level of aggregation of the given criterion matches that of its predictor. Any discrepancy between these levels inevitably reduces the magnitude of the association between predictor and criterion. Therefore, to predict a specific set of behaviors, a lower-order personality construct is optimal; to predict a more general pattern of behavior, a higher-level personality construct is optimal. Thus, the practical application of this metatheoretical principle is actually quite simple.

It is reasonable to ask if higher-order personality constructs might predict outcomes that differ from the lower-order outcomes already reviewed, or at least those outcomes themselves to different degrees. Our next section introduces several new ideas regarding the putative hierarchical structure of personality, the historical origins of the idea, and the dynamics of the theoretical and empirical links among the higher-order and the lower-order constructs, as well as the theoretical and empirical links among the lower-order constructs and each other.

A Hierarchy of Traits: The General Factor of Personality

The research reviewed above casts most of the results in terms of traditional factor models, such as the FFM, which generally decompose human personality traits into anywhere between three and six common factors. Since the writing of the first edition of this Handbook, however, a new body of data has accumulated, delineating a so-called General Factor of Personality (GFP), which some have technically defined as the first unrotated principal factor extractable from among a large array of seemingly different personality measures. GFPs have been isolated from more than 25 different personality scales and across different instruments, accounting for roughly 30% of the variance (Rushton & Irwing, 2011). A number of studies have shown that these method-independent GFPs generally correlate among themselves, indicating they are not independent or idiosyncratic with respect to specific personality inventories (Irwing, 2013; Just, 2011).

There is considerable speculation about what the GFP might be. Theories range from the idea that it is an artifact of uncontrolled social desirability bias and self-esteem, or even a statistical artifact (see Irwing, 2013, for a thorough overview of competing theories), to the idea that it corresponds to a continuum characterized by low social functioning and personality disorders at one pole and high social functioning or high social and emotional intelligence at the other (Rushton, Bons, & Hur, 2008). Evolutionary models of personality, such as those based in life history theory, have gone further by integrating the GFP into a broader life history super-factor termed Super-K, which encompasses behavioral manifestations of life history strategy and global measures of physical and mental health (this being the aforementioned covitality factor; Figueredo, Vásquez, Brumbach, & Schneider, 2004, 2007; Figueredo, Sefcek, et al., 2005; Weiss et al., 2002). The life history model posits that the high-functioning pole of GFP relates to prosocial or altruistic orientations necessary for optimum fitness under conditions of low extrinsic mortality and morbidity where organisms exist at the carrying capacity of their environment and conspecific densities are high (Figueredo & Rushton, 2009).

Before we recount the relatively brief history of the GFP in modern psychological literature, it is worth noting several of its historical antecedents; these antecedents are potentially informative regarding the reality of the GFP.

The GFP in Historical Perspective

Here we summarize four major historical and contemporary ways of thinking about personality (humoral, lexical, psychoanalytical, and archetypal), and in so doing, present evidence for the vestiges of the GFP in the early writings of all of these schools. We close this section with a discussion of the possible implications of this research for thinking about the reality of the GFP construct.

Hippocrates's Humoral Approach

The history of the GFP goes as far back as recorded thinking about temperament and personality itself. The ancient Greek physician Hippocrates (460–370 BC) proposed a “four factor” humoral model of personality based on observation and introspection, which decomposed the temperament domains into four biologically mediated archetypes: angry (choleric—associated with yellow bile), cheerful (sanguine—associated with blood), phlegmatic (stoical—associated with phlegm), and gloomy (melancholic—associated with black bile). Disequilibria among these various humors was seen as the cause of certain temperamental disorders that could be treated only by bringing the humors back into balance with one another (Garrison, 1966).

So-called good temperament was not formally operationalized as a higher-order factor, but as an optimal balance among humoral dispositions. Nevertheless, this conceptualization remarkably presages modern ideas regarding the GFP as a regulator of the public presentation of personality (e.g., Rushton et al., 2008).

Galton's Lexical Approach

The 19th century saw the origins of what could be termed the trait approach to the study of personality and cognitive ability. This approach, inaugurated by Sir Francis Galton, was predicated upon the idea that variation in personality and intelligence was associated with the existence of individual and group differences in measurable lexical (i.e., natural language) or physiological outcomes. Galton was the first to develop lexical questionnaires to probe variation in what he termed “character”:

I tried to gain an idea of the number of the more conspicuous aspects of the character by counting in an appropriate dictionary the words used to express them.…(Galton, 1884, p. 181)

It is interesting to note the sophistication of Galton's conceptualization of character, and also how poorly known and regarded his scientific intuitions are today. In the same work, he goes on to qualitatively describe a hierarchical structure among the various “shades of meaning” among lexicania, culminating with what might well be the first explicit description of a GFP-like higher-order personality factor:

I examined many pages of its index here and there as samples of the whole, and estimated that it contained fully one thousand words expressive of character, each of which has a separate shade of meaning, while each shares a large part of its meaning with some of the rest. (Galton, 1884, p. 181; italics added for emphasis)

Inspired by the work of his half-cousin Charles Darwin, especially in relation to his development of the theory of modification by descent (Darwin, 1859/1968), Galton became especially interested in the possibility that national character, far from being a fixed quantity, was in fact variable in response to selection and furthermore played a significant role, along with intelligence and vitality (general health), in determining the fates of civilizations (Galton, 1869).

Although so-called good character was not formally operationalized as a higher-order factor, either, the large proportions of shared “meaning” among the lexical items describing “character” suggest that such a common factor might exist and might be of some interpersonal utility.

Freud's Psychoanalytic Approach

Although it is true that the trait-centered or differential school of psychology instigated by Galton developed in the late 19th and early 20th centuries—most notably with the advent of the method of factor analysis (Spearman, 1904), which permitted the measurement of true trait dimensions—the psychological zeitgeist worked against this tendency. The rise of Freudian psychology saw a retreat from the trait-centered model, with its conceptual emphasis on the idea that personality is a source of behavior, toward the idea that manifestations of personality are instead contingent upon interactions between exposure to specific types of environments and various instincts and “race memories” (acquired characteristics transmitted in a Lamarckian fashion from parent to child; Freud, 1930). The Freudian approach rejected the idea that there is any intrinsic structure to personality beyond certain environmental regularities, although a minority of differential and evolutionary psychologists have sought to link Freud's notions of primal psychic drives (eros, thanatos, id, ego) and the suppressive urge (superego) with the dimensions contained within more conventional trait-centered models of personality (e.g., Brand, 1994; Nesse, 1990). It also rejected the idea of personality as a measurable and quantitative source of behavioral variation. To the Freudian, strong manifestations of personality were often regarded as deviant, the products of trauma or failed attempts to sublimate basal desires, and could only be known via a process of ultimately amelioratively guided introspection. Despite this, and following in the consilient footsteps of Freudian-sympathetic differential and evolutionary psychologists, there are some interesting parallelisms between Freud's concept of the superego—or the idea that in suppressing the “baser” urges, especially the id, which encompasses an animalistic and short-term oriented urge towards hedonic-pleasure and destruction (Freud, 1930), while simultaneously enhancing self-esteem and other emotionally satisfying mind-states, the motivation towards better and more socially desirable behavior ensues (Nesse, 1990).

Again, although the Freudian “superego” was not formally operationalized as a higher-order factor, there is a basic resonance between this Freudian aspect of the psyche and the GFP. In some contemporary theories of personality and clinical neuropsychology, this latent faculty functions as a governor or central executive in behavioral expression, regulating impulsivity and permitting socially desirable and effective manifestations of personality (Rushton et al., 2008).

Jung's Archetypal Approach

The Jungian school, which was sharply deviant with respect to the differential-psychology tradition, was another major influence on 20th-century personality psychology. Carl Gustav Jung, a one-time acolyte of Freud, proposed a major theory of personality that decomposed the psyche into three distinct domains: the ego, the personal unconscious, and the collective unconscious. The ego was synonymous with the conscious mind, whereas the personal unconscious embodied all memories, and the collective unconscious contained the collective “race memory” of mankind. Jung claimed that we processed the world via the use of archetypes, or sign systems that embodied specific systems of meanings, and proposed a number of major archetypes, the most relevant of which to the current discussion is the self, which represents a unification among different elements of the psyche, and the integration of various aspects of personality into an individuated whole (Jung, 1964).

Again, although the Jungian “self archetype” was not formally operationalized as a higher-order factor, it is interesting to note how this particular archetype is nonetheless consilient with modern conceptualizations of the GFP as a locus of integration among personality traits, and also as an effortful and conscious regulatory system regimenting the more basic components of personality in socially effective ways (Rushton et al., 2008). These parallels are evident despite the fact that Jungian thought traveled in an entirely separate direction from differential psychology in the 20th century.

The Intuitive Appeal or “Face Validity” of the GFP

These historical observations illustrate how the modern GFP was presaged across many previous attempts to define character, temperament, and personality, even when the proponents of those approaches might vehemently disagree with one another about the fundamentals. These theoretical antecedents have bearing on the potential face validity of the GFP, as they imply that the GFP is an intuitive construct, perhaps part of our “implicit personality theory,” and one that we have perhaps evolved to innately recognize as a desirable life history trait for the purposes of sexual and social selection (Figueredo, Sefcek, & Jones, 2006).

Modern Differential Psychology Constructs the GFP

Within the differential psychology tradition, the lexical approach to the measurement of personality slowly grew in popularity throughout the 20th century, until it reached ascendancy with Costa and McCrae (1992) developing the FFM of personality. The FFM had to compete with alternative ways of measuring personality, such as the physiological-centered three-factor Psychoticism, Extraversion, Neuroticism (PEN) model, which assumes personality dimensions and physiological processes relate fundamentally (e.g., Eysenck & Eysenck, 1976).

In the latter half of the 20th century and the first decade of the 21st, the debates revolved primarily around the “correct” structure of personality, with many proposing models that decomposed personality into different and alternative personality domains (e.g., 16 factors—Cattell, 1946; 7 factors—Cloninger & Gilligan, 1987; and 6 factors—Ashton et al., 2004; Brand, 1994). Debates about higher-order personality factors rarely entertained the idea of a general factor of personality, although Digman (1997) proposed a model that reduced personality to two correlated higher-order factors (DeYoung, Peterson, & Higgins, 2002).

Rushton (1985) was among the earliest modern thinkers to take the idea of a GFP seriously. In his paper, which introduced the idea of life history to the study of individual and group differences, Rushton stated:

An exciting, if open-ended possibility is that one basic dimension—K—underlies much of the field of personality psychology. (Rushton, 1985, p. 445)

In subsequent work, Rushton explicitly described this common variance among personality domains as the General Factor of Personality, and proposed that it evolved as a source of individual differences in an underlying prosocial personality, permitting individuals to tolerate one another and to behave cooperatively. He and his colleagues explicitly likened the GFP to social and emotion intelligence (Rushton et al., 2008). Rushton also acknowledged Darwin's (1871) writings as inspiration for this insight, crediting Darwin as the first to identify a need for altruistic personality to harmonize individual relations in a way that enhances group-level evolutionary effectiveness (Rushton & Irwing, 2011). More recently, Rushton corroborated another important prediction of a life history-anchored theory of personality, namely that the low-functioning pole of the GFP relates to certain extreme manifestations of personality, which shade into recognized clinical disorders. This includes various personality disorder assessment scales, which seem to share common variance giving rise to a “dark” or low-functioning GFP (Rushton & Irwing, 2009).

Immediately subsequent to Rushton's (1985) published insights, little progress was made towards testing predictions from the GFP until the 1997 Spearman Symposium on Intelligence and Personality, in which Hofstee proposed the existence of a p-factor, or general personality factor. He suggested an evolutionary function for this factor much along the lines of that proposed by Rushton—namely, that it embodied a suite of socially desirable traits including competence, emotional steadiness, and reality orientation. Importantly, Hofstee's model encompassed the idea that socially desirable responding is in fact an integral or primordial component of p, rather than a social-perception artifact (Hofstee, 2001, 2003).

Perhaps the most substantial empirical and theoretical developments with respect to understanding the nature of the construct occurred in a series of papers stemming from the Ethology and Evolutionary Psychology Laboratory at the University of Arizona. In these papers (Figueredo et al., 2004; Figueredo, Sefcek, et al., 2005; Figueredo, Vásquez, et al., 2007), several important theoretical and empirical advances were made. First, the GFP was successfully isolated from respondent data in the America at Midlife Survey, which comprises a large and representative sample of the midlife population of the United States. In the original paper (Figueredo et al., 2004), this factor was termed the higher-order personality construct (the term GFP had not yet been coined). Second, the GFP was shown to be substantially heritable (h2 = .50; Figueredo et al., 2004). Third, two other substantially heritable factors, one encompassing behavioral and attitudinal scales capturing slow life history or high-K behavior (termed the K-Factor), and a second encompassing physical and mental health (Covitality; Weiss et al., 2002), were extracted from the same data set, where it was found that a higher order Super-K factor accounted for the preponderance of the variance among the three subfactors. The Super-K factor is itself substantially heritable (h2 = .68). Subsequent analyses revealed genetic correlations among both the subfactors of Super-K and also the subcomponents of each factor (Figueredo, Vásquez, et al., 2007; Figueredo & Rushton, 2009). These developments should be considered significant because they strongly validate Rushton's (1985) notion of a unitary life history core to personality, which extends well beyond personality into other psychophysical domains as well.

Subsequent to this seminal work was that of Musek (2007), who (apparently unaware of Rushton's, Hofstee's, or Figueredo and colleagues' research) termed the GFP the “Big One.” Musek was the first to extract the GFP from three large samples. Musek also identified a hierarchy among personality factors, with the Big Two traits of plasticity (encompassing openness and extraversion in the Big Five) and stability (encompassing conscientiousness, agreeableness, and emotional stability in the Big Five) being subordinate to the GFP and the Big Five subordinate to the Big Two. He also considered the “Big One” to be related to the evolution and genetics of social effectiveness.

Musek's (2007) paper can be rightly considered to have opened the floodgates of research into the GFP. Since its publication, dozens of papers have been published both debating and describing the construct, in addition to exploring the large nomological net of associations with life outcomes (Just, 2011; Rushton & Irwing, 2011). A landmark event occurred in 2011 when the International Society for the Study of Individual Differences devoted an entire symposium to the GFP. Recently, the GFP was even examined in the context of primate personality, where it was found to be almost entirely absent (Weiss, Adams, & Johnson, 2011). This has potentially major ramifications. The existence of a GFP in humans, but not in other anthropoid primates, may stem from the complexity and intensity of sociality—even though primates, compared to most other mammals, live in larger groups, devote more time to social grooming, and form more complex cliques. Hominin and especially modern humans have an even more complex sociality system, with a much larger average functional group size, and use their time devoted to social interactions even more efficiently (Dunbar, 2001; Hill & Dunbar, 2003).

Controversies Regarding the Interpretation of the GFP

Ultimately, few ideas in psychology have proven to be as controversial as the notion that there exists a common source of variance latent in the various diverse measures of personality. As has been mentioned, many have raised objections to its putative psychological function; others have raised objections to its very existence (see Irwing, 2013, and Just, 2011, for an overview of these theories, which we discuss more thoroughly below). Despite this, and perhaps like a moth to a flame, psychometricians, and increasingly evolutionists too, are being drawn towards the study of this parsimonious construct. As we have seen, Just's (2011) broad systematic review indicates a major upswing in interest in this construct after 2007. Major headway has been made in the past decade toward a better understanding of both the behavioral genetic and the evolutionary underpinnings of this construct. Previous reviews of the GFP have not, however, seriously considered the idea that some prominent and even ancient theories of personality presaged aspects of the GFP, incorporating analogous concepts into their own distinct theoretical bodies of work. We contend that the reader should take this as evidence that the GFP exhibits intuitive or face validity, perhaps congruent with its potential evolutionary role as an indicator of underlying life history strategy aiding in sexual and social selection (Figueredo, Sefcek, & Jones, 2006).

In addition, the most important challenge to the status of the GFP as a valid theoretical construct, as reflecting a personality characteristic that exists independently of observer bias rather than an artifact of measurement, stems from the observation that the personality indicators of the GFP are all oriented in the “socially desirable” direction (Anusic, Schimmack, Pinkus, & Lockwood, 2009; Ashton, Lee, Goldberg, & de Vries, 2009; Bäckström, Bjorklund, & Larsson, 2009), suggesting that the common source of variance might be method rather than trait variance (Campbell & Fiske, 1959). However methodologically sophisticated, this argument is evolutionarily uninformed.

One fundamental misconception is that self-presentation bias exists only in responding to questionnaire items and does not reflect a real pattern of behavior. Aside from the fact that responding to test items itself constitutes verbal behavior, and not some ethereal activity, a growing body of literature supports the observation that socially desirable verbal behavior is highly correlated to socially desirable nonverbal behavior. In fact, a growing number of social psychologists now consider “social desirability” to represent a behavioral trait rather than a response bias (e.g., Fleming, 2012). This is because the fundamental motivation that drives socially desirable verbal and nonverbal behavior is the same: obtaining what Darwin (1871) called “approval of one's fellows.” It is therefore not surprising that these two behavioral manifestations tend to co-occur within the same individuals, and this logic implies that the allegedly biased self-reports of prosocial behavior are, more often than not, reasonably veridical. In contrast, this state of affairs does not hold symmetrically with respect to self-reports of socially undesirable behavior because antisocial individuals avoid revealing their own antisocial acts (for obvious reasons), while not necessarily fabricating false accounts of their own prosocial behavior.

Second is the misconception that what is socially desirable is somehow subjective or idiosyncratic. In fact, there is a high degree of agreement among both individuals and cultural groups regarding what constitutes prosocial behavior, although there might occasionally exist some differences in detail. Third is a direct consequence of the second misconception, and that is that there is no relation between a preference for certain traits and the possession of those traits. As originally proposed by Fisher (1930) for sexual selection, and extended by Nesse (2007) to social selection in general, a population preference for a certain trait inevitably creates selective pressures for the possession of that trait. Furthermore, these selective pressures also automatically produce genetic correlations among the preference and the possession of the given socially or sexually desirable trait over evolutionary time. This logical implication further supports the general veridicality of prosocial self-report. We may therefore link all the evidence associating the common factor variance underlying the GFP directly with the original conceptualization of the GFP (Rushton et al., 2008; Figueredo & Rushton, 2009) as a shared dimension of prosocial personality that extends to both the verbal and nonverbal domains of behavior.

Fourth are the increasingly numerous demonstrations that the GFP does not survive what has frequently been referred to as “multitrait-multimethod analysis” (MTMM; e.g., Riemann & Kandler, 2010); although the mathematical methods being applied are the same as those often applied to MTMM data, the different “methods” used in all these cases are comparison of self-report to peer report. Nevertheless, these are neither completely equivalent nor completely independent “methods” of assessment, because self-report is based on personal experience and introspection (which are themselves fallible) and the corresponding descriptions by “peers” that (almost by definition) are working with incomplete information and detailed knowledge of the person being rated, and have their own distinctive biases that are not due to any measurement error but to different experiential histories.

The broader understanding of the problem that we are proposing provides direct links to the evolutionary theories of personality that we have considered. In the sections that follow, we therefore seek to reconcile the entire corpus of results and the growing body of evidence for the existence of higher-order factors of personality structure than have been previously considered.

Cognitive and Strategic Differentiation-Integration Theory

A more recent empirical development in the application of life history theory to understanding personality concerns the idea that in addition to higher levels of the GFP, conative integration is associated with faster life history (low K-selected) populations and is adaptive given unstable and unpredictable environmental contexts where the ability to contingently switch among transient social-ecological niches leads to increased fitness (Figueredo, Woodley, Brown, & Ross, 2013). In contrast, slower life history (high-K) populations exhibit more highly differentiated GFPs, which account for the generally lower correlations among lower-order personality factors in slower life history strategists than appear among the less differentiated GFPs characteristic of faster life history (high-r) populations, which account for the generally higher correlations among lower-order personality factors in slower life history strategists. This is termed the Strategic Differentiation-Integration Effort (SD-IE) theory, and it is based on the idea that conative (social cognitive and psychosocial behavioral) differentiation permits more efficient niche splitting where conspecific densities and interindividual competition are high, and where there is more variation between individuals in terms of personality specialization.

The observation of these systematic individual differences in either the integration or the differentiation of the GFP, presumably in response to the adaptive demands of the environment, opened up a whole new way for us to view the evolved structure of personality as controlled by mechanisms that are exquisitely shaped by selective pressures for either the articulation or the coordination of life history resource allocations in general, as required by the contingencies of survival and reinforcement across the multifaceted adaptive landscape of more specific contexts and domains.

To test this theory empirically, as applied to the evolution and development of individual differences in personality, one needs to demonstrate that the contingent differentiation and integration of personality constructs (and of life history traits in general) is also systematic, predictable, and adaptively strategic, as specified by the relevant evolutionary theory, and by means of the specific mechanisms that we have proposed. We now turn our attention to the growing number of critical tests of this theory that have been done in the elucidation of the strategically contingent nature of the differentiation and integration of cognitive and conative individual difference factors in differential evolutionary psychology.

Empirical Tests of SD-IE Theory

The realization that those individual lineages exhibiting slow life histories must be capable of cognitive and conative differentiation in response to heightened environmental stability sparked a new development in the area of life history research (Woodley, 2011). This is because slower life-history populations rapidly grow to the limits of their environmental carrying capacity, which produces greatly increased interindividual competition. Thus, cognitive and conative differentiation encourages prosocial competition, which is competition over narrow sociocultural microniches. Prosocial competition, in its turn, encourages intraspecific character displacement, giving each individual a comparative advantage. A comparative advantage then raises the environmental carrying capacity by increasing the aggregate efficiency of the diversified population of high-K specialists (as originally predicted by the coral reef model of personality evolution and development proposed in Figueredo, Sefcek, et al., 2005). In contrast, those with faster life histories are cognitive and conative generalists. Being a generalist advantages individuals coping with unstable environments because they can contingently switch between a variety of different sociocultural microniches, and thus they invest little in any single microniche at any given time, but over time can come to occupy many in response to spatiotemporal heterogeneity.

The theory was originally developed to resolve an anomaly in the individual-differences literature—namely, why it is that the speed of life history correlates positively with general intelligence when population-level aggregates are considered (Rushton, 2004), but not at all when the dimensions are considered at the individual-differences level (Woodley, 2011). This anomaly has been termed “Rushton's Paradox” (Meisenberg & Woodley, 2013). One possible solution involved the idea that even though there is no individual-level main effect of K on g (the general intelligence factor), K might nonetheless control the amount of effort that goes into reinforcing the positive manifold of g during development, such that those with high K tend to exhibit a more specialized ability profile and weaker g than those with low K. In this model, the level of g functions as a fitness indicator, as per G. F. Miller's (2000a) Fitness Indicators Theory and is thus genetically uncorrelated with K.

This Cognitive Differentiation-Integration Effort (CD-IE) hypothesis was tested using the Continuous Parameter Estimation Method (CPEM; Gorsuch, 2005), which permits individual differences in the level of trait covariance to be measured via the use of the individual-level cross-products between the common factor and component scores (Woodley, Figueredo, Brown, & Ross, 2013). CD-IE effects were tested using four individual-level samples (two student samples and two nationally representative ones) totaling 12,374 individuals. Statistically significant CD-IE effects were detected in all four samples, in the expected negative direction, indicating that the covariance among convergent indicators weakens as a function of increasing levels of the latent common factor (K). The Strategic Differentiation-Integration Effort (SD-IE) hypothesis derived from research into the CD-IE phenomenon (Woodley et al., 2013). As was mentioned previously in the section reviewing the history of the GFP, SD-IE tradeoffs occur among the conative and behavioral fitness domains of life history itself, with slower life history individuals exhibiting more specialized profiles of behavior and personality and faster life history ones showing the opposite tendency.

Bronfenbrenner's (1979) ecological systems theory defined a series of concentric circles defining the social influences surrounding any developing individual, using Greek praefices to describe the relative ranks of each concentric circle, characterizing their relative inclusiveness within this hierarchically nested system: microsystem, mesosystem, exosystem, and macrosystem. This basic framework has been applied within evolutionary psychology (Figueredo, Brumbach, et al., 2007) for understanding the various pressures of social selection that these systems generate by (a) adapting the theoretical framework to conform to more evolutionarily informed levels of social organization and (b) generalizing the principle from applying exclusively to phenomena occurring over developmental time to encompass phenomena occurring over evolutionary time. Consistent with this evolutionary application of ecological systems theory, wherein similar but nonidentical selective pressures (including developmental influences) exist across the hierarchically nested levels of social organization, the predictions of SD-IE theory have been subjected to empirical tests across a wide array of different levels of organization. The results of these various empirical tests of the theory, including the original CD-IE results described above, are summarized in Table 40.1.

Table 40.1 CD-IE and SD-IE Effects at Increasing Hierarchically Nested Levels of Social Organization

Scale Effect Type Average Effect Size (β) Sample Size (N) Reference
Individual Level CD-IE1 −.10 12,374 individuals Woodley, Figueredo, Brown, and Ross (2013)
SD-IE (Super-K, Sweden) −.36 1,726 twin-singletons Woodley of Menie, Figueredo, Cabeza de Baca, Fernandes, Madison, and Black (2015)
SD-IE (Super-K, United States) −.32 7,749 individuals Figueredo, Woodley, Brown, and Ross (2013)
SD-IE (K-Factor, United States) −.31
SD-IE (GFP, United States) −.25
SD-IE (Covitality, United States) −.38
Sociosexual SD-IE (Brazil) −.25 448 individuals Fernandes, Woodley, Kruger, and Hutz (2014)
Sociosexual SD-IE (United States) −.29 318 individuals
Sociosexual SD-IE (Multinational) −.37 112 individuals
Regional Level CD-IE (Italy) −.43 18 counties Armstrong, Fernandes, and Woodley (2014)
CD-IE (Spain) −.78 18 provinces
SD-IE (Italy) −.49 18 counties
SD-IE (Spain) −.56 18 provinces
SD-IE (Japan) −.22 47 prefectures Woodley, Fernandes, and Madison (2014)
SD-IE (United States) −.44 50 states Fernandes and Woodley (2013)
National Level CD-IE −.23 76 countries Woodley and Fernandes (2014)
SD-IE −.43
Continental Level CD-IE1 −.17 107 observations Woodley, Figueredo, Brown, and Ross (2013)
Species Level (Primates) SD-IE −.32 120 species Fernandes, Figueredo, and Woodley (2014)
1CD-IE effects were obtained either in the absence of a g/K correlation, or where a preexisting correlation had been eliminated.

As with CD-IE effects, individual-level tests of the predicted SD-IE effects were conducted using two student samples and two nationally representative samples totaling n = 7,749. The effect sizes across all samples were statistically significant, substantial in magnitude, and in the expected negative direction, thus confirming the presence of SD-IE. SD-IE effects were found for both the convergent indicators of lower-order and the higher-order latent common factor of life history strategy, where the magnitudes of the effects were appreciably larger in absolute value for the higher-order factor. It was predicted that the positive manifold of life history traits should be the locus of SD-IE effects, because the phenomenon involves a fundamental reconfiguration of the ways in which individuals allocate effort into specific life history domains. A final note on these two large individual-differences-level studies is that the effects are not confounded with sex differences, this having been measured via the construction of a dimorphic sex indicator, which was used as a moderator in regression analysis. Thus, CD-IE and SD-IE constitute sex-universal sources of individual differences.

More recently, the heritability of the SD-IE effect on the components of Super-K has been estimated using twin data from the U.S. MIDUS (316 monozygotic and 274 dizygotic twin dyads) and the Swedish STAGE (863 monozygotic and 475 dizygotic twin dyads) cohorts. It was found that the heritabilities of the SD-IE effects ranged from .3 to .64 in the U.S. sample, and from .55 to .61 in the case of the Swedish sample. The specific h2 of the SD-IE effect on the GFP was .3 in the U.S. and .61 in the Swedish sample (Woodley of Menie et al., 2015).

Cross-culturally, individual-level SD-IE effects have also been detected among sexual strategy indicators in Brazilian (n = 448), American (n = 318), and multinational (n = 112) samples (Fernandes, Woodley, Kruger, & Hutz, 2014). Scores on sociosexual behavior, attachment anxiety and avoidance, factors of postcoital emotions, and mate value appear to be more integrated among themselves in those with faster life histories. A considerably higher range of strategic differentiation and integration was found in the multinational sample compared to the nation-specific samples, which might partly be due to the higher population stratification in this sample, as it was composed of individuals originating from various continents and ethnic-genetic clusters that have been demonstrated to vary in their aggregates of both life history speed (Rushton, 2000) and strategic integration and differentiation (Woodley & Fernandes, 2014).

At the level of entire populations, a potentially significant theoretical innovation in Woodley and Fernandes (2014) is the idea of group-level character displacement. It was argued that the ecological regimes favoring individual-level character displacement also favor this process at the group level; specifically, the presence of both group-level and individual-level competition offers opportunities for multilevel selection among aggregately specialized groups.

To test this more extended theory, the phenomenon of group-level SD-IE has been replicated using regional-level aggregate data in several other national samples. In Fernandes and Woodley (2013), U.S. state-level data on five life history variables were used to construct a Super-K Factor. Across the states of the United States, statistically significant SD-IE effects were detected that were substantial in magnitude and in the expected negative direction. Another test of group-level SD-IE has been conducted using aggregate-level data on eight life history salient indicators collected among the 47 prefectures of Japan (Woodley, Fernandes, et al., 2014). This analysis revealed a significantly trifurcated factor structure among these indicators, suggesting considerable levels of underlying differentiation consistent with the observation that Japan has one of the slowest aggregate life history speeds of any country (Woodley & Fernandes, 2014). Attempts to quantify SD-IE therefore focused on the five indicators, which loaded on the first principal axis factor because these were considered to constitute the “primary K factor.” Across the 47 prefectures of Japan, statistically significant SD-IE effects were detected that were substantial in magnitude and in the expected negative direction.

Armstrong, Fernandes, and Woodley (2014) conducted the most recent test of group-level SD-IE using regional-level data for both Spain and Italy. In this analysis, six aggregate life history indicators were collected for 18 Spanish counties and 10 such indicators were collected for 18 Italian provinces. In addition to these, data on five different cognitive ability indicators were collected for the Italian sample and data on four were collected for the Spanish sample. Across the 18 Spanish counties and the 18 Italian provinces, both CD-IE and SD-IE effects were detected that were substantial in magnitude and in the expected negative direction.

At an even higher level of population structure, Woodley and Fernandes (2014) found SD-IE effects on 10 aggregate national-level life history measures comprising a K Super-Factor (Templer, 2008), using a sample of 76 Old-World countries. At the even higher continental-level of genetic population clusters, another recently published analysis of group-level SD-IE (Dunkel, Cabeza de Baca, Woodley, & Fernandes, 2014) used data from populations in the United States dating back to the 1960s taken from Project Talent. These data were split into three major groups based upon geographical region of ancestral origin: Africa (n = 6,533), Europe (n = 147,355), and Asia. A GFP was constructed using the 10 personality subscales of a student activities inventory and data on general intelligence were obtained from a 16-subtest cognitive ability measure.

Although molecular genetic research has shown that continental-level population clusters account for only about 10% of the variance in global-level human genetic biodiversity as measured by the relative frequencies of individual alleles (as opposed to those of latent clusters of alleles or of entire haplotypes), these three continental-level population clusters have been shown to have statistically significant differences in averaged life history speed (e.g., Rushton, 1985). Thus, in spite of the preponderance of interindividual variance within each of them (e.g., Figueredo, Vásquez, Brumbach, & Schneider, 2004, 2007), the large amount of extant data on these continental-level classifications makes it possible to use the groupings as convenient proxies for aggregate mean differences in life history, because when aggregated across literally hundreds of millions of individuals, these average differences inevitably achieve any desired level of statistical significance. The relative rankings of these continental population clusters, by average differences in life history speed, are ordered as follows, from faster to slower: Africa>Europe>Asia (Rushton, 2000). Based on both CD-IE and SD-IE theories, it was therefore hypothesized that the within-group correlation between the GFP and g would vary in strength based on the aggregate life history speed of the three groups, and the results were found to be consistent with these predictions.

Finally, at the higher taxonomic level of the primate order, it appears that SD-IE theory applies beyond human individual and group-level differences; SD-IE effects have been detected among a large number of primate species with six life history traits (Fernandes, Figueredo, & Woodley, 2014). A statistically significant and negative SD-IE effect was detected across 120 primate species, after controlling for any effects of phylogeny (as distinct from effects of adaptation; see Tinbergen, 1963), such as phylogenetic inertia (higher similarity among closely related clades than among distantly related ones; Felsenstein, 1985) and faster evolutionary rates in faster life history species due to differences in generation time and in DNA repair mechanisms (e.g., Bromham, 2009). Importantly, species endocranial volume also positively predicted life history differentiation (β = −.25); however, K fully mediated the effect. Sociality, in turn, did not have a direct SD-IE effect that was statistically significant, but instead had an indirect effect on life history differentiation through its significant direct effect on endocranial volume (Dunbar, 2010; Fernandes, Woodley, et al., 2014).

Although it might be a seeming contradiction that a weaker GFP should be found both in nonhuman primates and in slower LH humans, the presence of a weaker GFP in slow LH humans is in no way equivalent to the complete absence of a GFP in the subset of other primates that have been assessed for it (mainly other apes and not monkeys). In one case, we contend that the GFP has not even evolved, or at least not sufficiently to be detectable. This is the case of species like gorillas and chimpanzees. In the other case, we contend that not only does the GFP exist as a mental structure, but a mechanism has evolved for adaptively integrating or differentiating its components in response to environmental contingencies. This other case is that of humans, seemingly exclusively (to our present knowledge), and represents a much more sophisticated set of psychological mechanisms that the mere absence or presence of the structure, involving not only the possession of a developmental program for constructing a GFP, but also a controlling epigenetic mechanism with developmental switches in place for accomplishing that function. Interestingly enough, the recent work documenting SD-IE in nonhuman primates strongly suggests that this latter mechanism evolved for differentiating LH traits prior to the emergence of the GFP. This implies that SD-IE effects upon the GFP arose when personality became more fully integrated into LH strategies in our own hominan lineage.

Theoretical Interpretations of Empirical Tests of SD-IE

We claim this accumulating corpus of evidence demonstrates that differentiation and integration of personality constructs, and of life history traits in general, is strategically contingent upon the overall speed of life history (the fast-slow or “r-K” continuum), and therefore, ultimately, upon the well-documented ecological conditions known to govern its selection over evolutionary and developmental time—an effect that occurs across a wide array of species of nonhuman animals and plants (for a more comprehensive review, see Ellis, Figueredo, Brumbach, & Schlomer, 2009). The main selective pressures shaping the speed of life history are the relative degrees of environmental stability and the organism's ability to predict and control it as afforded by that environment. The controllability aspect is particularly essential, although the other two dimensions are logical prerequisites for it, because high levels of extrinsic morbidity and mortality preserve faster (r) life histories—that is, high levels of hazards of disease and death that cannot be controlled by any evolvable physiological or psychological mechanism select against slow life history strategies. The opposite, called intrinsic morbidity and mortality, are parameters that can be brought under at least partial control by biologically evolvable mechanisms, and high levels of this instead selectively favor slower (K) life history strategies.

The explicit conditions for theory falsification that we offered above involved demonstrations that the contingent differentiation and integration of personality constructs (and of life history traits in general) are systematic, predictable, and adaptively strategic, as specified by the relevant evolutionary theory. We identified evolutionary life history theory as the relevant interpretive framework, based on our previous psychometric work examining the hierarchical latent structure of life history traits, encompassing both higher-order and lower-order personality constructs. Thus, we assert that we have met at least some of the critical testing conditions and that our integrative theory survived multiple repeated and nontrivially severe attempts at falsification.

Of course, all that philosophy of science will support in such a case is the claim that we have “supported,” not “proven,” our integrative theory. There are other conditions that future research needs to meet to help develop this conceptualization of the problem. It is to various proposals for these additional tests that we now turn.

We propose that to become more conclusive, future research in personality needs to apply what can be referred to as vertical integration, which involves integrating knowledge relevant to personality theory from those disciplines considered to be fundamental to psychology, specifically physiology, anatomy, and genetics, and those to which psychology is a fundamental discipline, specifically, evolutionary biology, evolutionary anthropology, ecology, and ethology. In addition, research should use multiple methods, ranging from controlled experiments to naturalistic observation, in what is referred to as horizontal integration (e.g., Jacobs, 1994; Jones, Wenner, & Jacobs, 2005). This is particularly important because personality research is based on methods, each of which has specific inherent flaws, such as observer drift and reactivity associated with observation (Jacobs et al., 1988; Klahr & Simon, 1999; Repp, Nieminen, Olinger, & Brsca, 1988).

The specific phylogenetic and ontogenetic mechanisms necessarily involved in the organic implementation or proximate mediation of the strategically contingent differentiation and integration of cognitive and conative individual difference factors has yet to be demonstrated. For example, it is not sufficient to demonstrate that in unstable, unpredictable, and uncontrollable environments, life history traits (such as personality constructs) are more integrated, and that in stable, predictable, and controllable environments, life history traits (such as personality constructs) are more differentiated. These are mere descriptions. We also need to show that the differentiation is strategically adaptive, and not just strategically contingent. In other words, the allocation of resources to life history and personality domains that increase or decrease relative to one another must correspond to the fitness gains and losses afforded by any given environment in which trait differentiation occurs. Specifically, trait-specific adaptive domains associated with higher fitness gains must receive higher resource allocations, and trait-specific adaptive domains associated with lower fitness gains must receive lower resource allocations.

To substantiate this empirically, it might be fruitful to conduct studies using mixed quasi- and true-experimental designs that relate measured prior traits of different individuals and then predict what their allocations of behavioral effort should be within different environmental contexts (which could be manipulated in the laboratory). Afterwards, one would expose a variety of such individuals to these same conditions and try to match their observed behavioral effort allocations to the predicted patterns. This is similar to what Sherman, Figueredo, and Funder (2013) have already done retrospectively by comparing theoretically expected patterns of behavior for fast and slow life history individuals (produced by an expert panel) to the self-reported patterns of behavior of research participants matching the prototypical trait ratings obtained for fast and slow life history individuals.

To accomplish this, one might administer pretests for the life history traits (or general constructs) of interest, in a way that has adequate Brunswik-Symmetry to the expected outcome of the mixed-design experiment. The reason that this portion of such a study is necessarily a mixed design is that life history speed is a trait that is quite stable over time and is also highly heritable in adults (h2 ca. .65; Figueredo et al., 2004; Figueredo & Rushton, 2009); thus, it is unlikely that any experimental manipulation will change it dramatically. More importantly, life history speed cannot be randomly assigned, which is a prerequisite for true experimental designs. We expect (based on our stated theory), however, that environmental contexts influence behavioral expression of life history traits in proximal time. If the so-called person-situation interaction can be specified as systematic and predictable (as required by our theory), we should therefore obtain the specified patterns of differential and context-specific behavior predicted by theory.

For example, if participants are prescreened (by questionnaires) on fast or slow life history strategy, then are brought into the laboratory to perform a delay-of-gratification task, we expect that the faster life history strategists will favor shorter-term fitness gains over longer-term fitness gains, and may not be willing to incur shorter-term fitness losses (or defer short-term gains) for longer-term fitness gains. Conversely, we expect that the slower life history strategists will favor longer-term fitness gains over shorter-term fitness gains, and may be willing to incur shorter-term fitness losses (or defer shorter-term fitness gains) for longer-term fitness gains.

Mischel and Ebbesen (1970; see also Mischel, Shoda, and Rodriguez, 1989), for example, applied a true-experimental design to examine delay of gratification in children using the now-famous “marshmallow task,” and were able to discriminate between children that were favorably disposed to defer gratification and those that were not on the basis of their observable behavior. Mischel, a well-known critic of trait theory in personality, did not attempt to predict this differential responding by matching them to any preexistent traits that these children might have possessed. In our proposed reexamination of the phenomenon, we expect differential responding based primarily on pretask assessment of life history strategy. Similarly, we predict that fast life history strategists would be more likely to “defect” in a Prisoner's Dilemma task than slow life history strategists, who are generally more invested in maintaining longer-term social and sexual relationships.

Conclusions

In summary, we have reviewed the general contents and conclusions of our previous chapter on the same topic published in the first edition of this handbook (Buss, 2005) and extended our reasoning to the evolutionary significance of the GFP, reviewing both its history as a construct and most of recent psychometric tests of its validity. We have proposed an evolutionary theoretical framework for understanding the evolution of the higher-order personality factors as well as the persistence of the lower-order personality factors. We examined and evaluated several empirical tests of risky predictions derived from that framework, found their results to be generally consistent with those theoretical predictions, and followed up with proposals for research designs that should help elucidate the complex and dynamic relationships among the various semi-autonomous components of personality.

Based on this review, we argue that personality is both unitary and manifold, just as the contingencies of survival and reproduction demand; personality is both persistent and stable and, at the same time, subject to fine-tuning. As characterized so long ago by Gordon Allport (1961): “Personality is the dynamic organization within the individual of those psychophysical systems that determine his characteristic behavior and thought (p. 28).” Personality, according to Figueredo, Cox, and Rhine (1995), “(1) exists as a definable construct, (2) represents a fluid property of a constantly changing and adapting organism, and (3) characterizes the individual, rather than being constructed by the observer” (p. 168). It is our future task as differential evolutionary psychologists to discern the ultimate and proximate causes of these organic and protean behavioral phenomena.

References

  1. Allport, G. (1961). Pattern and growth in personality. New York, NY: Holt, Rinehart & Winston.
  2. Anusic, I., Schimmack, U., Pinkus, R., & Lockwood, P. (2009). The nature and structure of correlations among Big Five ratings: The Halo-Alpha-Beta model. Journal of Personality and Social Psychology, 97, 1142–1156.
  3. Armstrong, E. L., Fernandes, H. B. F., & Woodley, M. A. (2014). SD-IE and other differentiation effects in Italy and Spain. Personality and Individual Differences, 68, 189–194.
  4. Ashton, M. C., Lee, K., Goldberg, L. R., & de Vries, R. E. (2009). Higher-order factors of personality: Do they exist? Personality and Social Psychology Review, 13, 79–91.
  5. Ashton, M. C., Lee, K., Perugini, M., Szarota, P., de Vries, R. E., Di Blas, L.,… De Raad, B. (2004). A six-factor structure of personality-descriptive adjectives: Solutions from psycholexical studies in seven languages. Journal of Personality and Social Psychology, 86, 356–366.
  6. Bäckström, M., Bjorklund, F., & Larsson, M. R. (2009). Five-factor inventories have a major general factor related to social desirability which can be reduced by framing items neutrally. Journal of Research in Personality, 43, 335–344.
  7. Brand, C. R. (1994). Open to experience—Closed to intelligence: Why the “Big Five” are really the “Comprehensive Six.” European Journal of Personality, 8, 299–310.
  8. Bromham, L. (2009). Why do species vary in their rate of molecular evolution? Biology Letters, 5, 401–404.
  9. Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press.
  10. Brunswik, E. (1952). The conceptual framework of psychology (International Encyclopedia of Unified Science, Vol. 1, No. 10). Chicago, IL: The University of Chicago Press.
  11. Buss, D. M. (1985). Human mate selection. American Scientist, 73, 47–51.
  12. Buss, D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures. Behavioral and Brain Sciences, 12, 1–49.
  13. Buss, D. M. (1991). Evolutionary personality psychology. Annual Review of Psychology, 42, 459–491.
  14. Buss, D. M. (Ed.). (2005). The handbook of evolutionary psychology. Hoboken, NJ: Wiley.
  15. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81.
  16. Cattell, R. B. (1946). The description and measurement of personality. New York, NY: World Book.
  17. Cloninger, C. R., & Gilligan, S. B. (1987). Neurogenetic mechanisms of learning: A phylogenetic perspective. Journal of Psychiatric Research, 21, 457–472.
  18. Costa, P. T., Jr. & McCrae, R. R. (1992). Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) manual. Odessa, FL: Psychological Assessment Resources.
  19. Darwin, C. (1871). The descent of man, and selection in relation to sex. London, England: D. Appleton & Co.
  20. Darwin, C. (1968). On the origin of species by means of natural selection. New York, NY: Penguin Books. (Original work published 1859).
  21. DeYoung, C. G., Peterson, J. B., & Higgins, D. M. (2002). Higher-order factors of the Big Five predict conformity: Are there neuroses of health? Personality and Individual Differences, 33, 53–552.
  22. Digman, J. M. (1997). Higher-order factors of the Big Five. Journal of Personality and Social Psychology, 73, 1246–1256.
  23. Dunbar, R. I. (2001). Brains on two legs: Group size and the evolution of intelligence. In F. B. M. de Waal (Ed.), Tree of origin: What primate behavior can tell us about human social evolution (pp. 173–191). Cambridge, MA: Harvard University Press.
  24. Dunbar, R. I. M. (2010). Brain and behaviour in primate evolution. In P. H. Appeler & J. Silk (Eds.), Mind the gap: Tracing the origins of human universals (pp. 315–330). Berlin, Germany: Springer.
  25. Dunkel, C. S., Cabeza de Baca, T., Woodley, M. A., & Fernandes, H. B. F. (2014). The general factor of personality and general intelligence: Testing hypotheses from Differential-K, Life History Theory, and Strategic Differentiation-Integration Effort. Personality & Individual Differences, 61–62, 13–17.
  26. Eaves, L. J., Martin, N. G., Heath, A. C., Hewitt, J. K., & Neale, M. C. (1990). Personality and reproductive fitness. Behavior Genetics, 20(5), 563–568.
  27. Ellis, B. J., Figueredo, A. J., Brumbach, B. H., & Schlomer, G. L. (2009). Fundamental dimensions of environmental risk: The impact of harsh versus unpredictable environments on the evolution and development of life history strategies. Human Nature, 20, 204–268.
  28. Eysenck, H. J. (1976). Sex and personality. London, England: England Open Books.
  29. Eysenck, H. J., & Eysenck, S. B. G. (1976). Psychoticism as a dimension of personality. London, England: Hodder & Stoughton.
  30. Felsenstein, J. (1985). Phylogenies and the comparative method. American Naturalist, 125, 1–15.
  31. Fernandes, H. B. F., & Woodley, M. A. (2013). Strategic differentiation and integration among the 50 states of the USA. Personality & Individual Differences, 55, 1000–1002.
  32. Fernandes, H. B. F., Figueredo, A. J., & Woodley, M. A. (2014). The coevolution of ecological specialism-generalism, life history, brain size and sociality in the primate order. Manuscript in preparation.
  33. Fernandes, H. B. F., Woodley, M. A., Kruger, D. J., & Hutz, C. S. (2014). The cross-national pattern in strategic differentiation and integration of sexual strategy indicators. Manuscript in preparation.
  34. Figueredo, A. J. (1995). The evolution of individual differences. Paper presented at Jane Goodall Institute ChimpanZoo annual conference, Tucson, Arizona.
  35. Figueredo, A. J., Brumbach, B. H., Jones, D. N., Sefcek, J. A., Vásquez, G., & Jacobs, W. J. (2007). Ecological constraints on mating tactics. In G. Geher & G. F. Miller (Eds.), Mating intelligence: Sex, relationships and the mind's reproductive system (pp. 335–361). Mahwah, NJ: Erlbaum.
  36. Figueredo, A. J., Cox, R. L., & Rhine, R. J. (1995). Generalizability analysis for confirmatory factor modeling with small samples. EGAD Quarterly, 1(1), 6–11.
  37. Figueredo, A. J., & King, J. E. (2001). The evolution of individual differences. In S. D. Gosling & A. Weiss (Chairs), Evolution and Individual Differences Symposium conducted at the annual meeting of the Human Behavior and Evolution Society, London, England, United Kingdom.
  38. Figueredo, A. J., & Rushton, J. P. (2009). Evidence for shared genetic dominance between the general factor of personality, mental and physical health, and life history traits. Twin Research and Human Genetics, 12(6), 555–563.
  39. Figueredo, A. J., Sefcek, J. A., & Jones, D. N. (2006). The ideal romantic partner personality. Personality and Individual Differences, 41, 431–441.
  40. Figueredo, A. J., Sefcek, J. A., Vásquez, G., Brumbach, B. H., King, J. E. & Jacobs, W. J. (2005). Evolutionary personality psychology. In D. M. Buss (Ed.), Handbook of evolutionary psychology (pp. 851–877). Hoboken, NJ: Wiley.
  41. Figueredo, A. J., Vásquez, G., Brumbach, B. H., & Schneider, S. M. R. (2004). The heritability of life history strategy: The K-factor, covitality, and personality. Social Biology, 51, 121–143.
  42. Figueredo, A. J., Vásquez, G., Brumbach, B. H., & Schneider, S. M. R. (2007). The K-factor, covitality, and personality: A psychometric test of life history theory. Human Nature, 18, 47–73.
  43. Figueredo, A. J., Vásquez, G., Brumbach, B. H., Schneider, S. M., Sefcek, J. A., Tal, I. R., & Jacobs, W. J. (2006). Consilience and life history theory: From genes to brain to reproductive strategy. Developmental Review, 26(2), 243–275.
  44. Figueredo, A. J., Vásquez, G., Brumbach, B. H., Sefcek, J. A., Kirsner, B. R., & Jacobs, W. J. (2005). The K-Factor: Individual differences in life history strategy. Personality & Individual Differences, 39, 1349–1360.
  45. Figueredo, A. J., Wolf, P. S. A., Olderbak, S. G., Sefcek, J. A., Frías-Armenta, M., Vargas-Porras, C., & Egan, V. (in press). Positive assortative pairing in social and romantic partners: A cross-cultural observational field study of naturally occurring pairs. Personality and Individual Differences. doi:10.1016/j.paid.2014.12.060
  46. Figueredo, A. J., Woodley, M. A., Brown, S. D., & Ross, K. C. (2013). Multiple successful tests of the strategic differentiation-integration effort (SD-IE) hypothesis. Journal of Social, Evolutionary & Cultural Psychology, 7, 361–383.
  47. Fisher, R. A. (1930). The genetical theory of natural selection. Oxford, England: Clarendon Press.
  48. Fleming, P. (2012). Social desirability, not what it seems: A review of the implications for self-reports. The International Journal of Educational and Psychological Assessment, 11, 3–22.
  49. Freud, S. (1930). Civilization and its discontents. Berlin, Germany: Internationaler Psychoanalytischer Verlag Wien.
  50. Friedman, H. S. (2000). Long-term relations of personality and health: Dynamisms, mechanism, tropisms. Journal of Personality, 68(6), 1089–1107.
  51. Friedman, H. S., & Booth-Kewley, S. (1987). The “disease-prone personality”: A meta-analytic view of the construct. American Psychologist, 42, 539–555.
  52. Galton, F. (1869). Hereditary genius. London, England: Macmillan Everyman's Library.
  53. Galton, F. (1884). Measurement of character. Fortnightly Review, 36, 179–185.
  54. Garrison, F. H. (1966). History of medicine. Philadelphia, PA: W.B. Saunders.
  55. Gonzaga, G. C., Carter, S., & Buckwalter, J. G. (2010). Assortative mating, convergence, and satisfaction in married couples. Personal Relationships, 17, 634–644. doi: 10.1111/j.1475-6811.2010.01309.x
  56. Gorsuch, R. L. (2005). Continuous parameter estimation model: Expanding the standard 26 statistical paradigm. Journal of the Science Faculty of Chiang Mai University, 32, 11–27.
  57. Gosling, S. D., & John, O. P. (1999). Personality dimensions in nonhuman animals: A cross-species review. Current Directions in Psychological Science, 8(3), 69–75.
  58. Hellhammer, D. H., Hubert, W., Phil, C., Freischem, C. W., & Nieschlag, E. (1985). Male infertility: Relationships among gonadotropins, sex steroids, seminal parameters, and personality attitudes. Psychosomatic Medicine, 47(1), 58–66.
  59. Hill, R. A., & Dunbar, R. I. (2003). Social network size in humans. Human Nature, 14, 53–72.
  60. Hofstee, W. K. B. (2001). Intelligence and personality: Do they mix? In J. M. Collis & S. Messick (Eds.), Intelligence and personality: Bridging the gap in theory and measurement (pp. 43–60). Mahwah, NJ: Erlbaum.
  61. Hofstee, W. K. B. (2003). Structures of personality traits. In I. B. Weiner (Series Ed.) & T. Millon & M. J. Lerner (Vol. Eds.), Handbook of psychology: Vol. 5. Personality and social psychology (pp. 231–254). Hoboken, NJ: Wiley.
  62. Irwing, P. (2013). The general factor of personality: Substance or artefact? Personality and Individual Differences, 55, 234–232.
  63. Jacobs, W. J. (1994, February). Stress-induced characteristics of anxiety, fear, and specific phobias. Invited colloquium presented to the Psychology Department, University of Southern California, Los Angeles, California.
  64. Jacobs, W. J., Blackburn, J. R., Buttrick, M., Harpur, T. J., Kennedy, D., Mana, M. J.,… Pfaus, J. G. (1988). Observations. Psychobiology, 16, 3–19.
  65. Jones, D. N., Wenner, C., & Jacobs, W. J. (2005, June). Getting the big picture: Methodological constraints on evolutionary approaches to psychological research using horizontal and vertical integration. Invited symposium presented to the annual Human Behavior and Evolution Society, Austin, Texas.
  66. Jung, C. G. (1964). Man and his symbols. New York, NY: Doubleday.
  67. Just, C. (2011). A review of the literature on the general factor of personality. Personality and Individual Differences, 50, 165–771.
  68. King, J. E., & Figueredo, A. J. (1997). The five-factor model plus dominance in chimpanzee personality. Journal of Research in Personality, 31(2), 257–271.
  69. Klahr, D., & Simon, H. A. (1999). Studies of scientific discovery: Complementary approaches and convergent findings. Psychological Bulletin, 125, 524–543.
  70. MacDonald, K. B. (1998). Evolution, culture, and the five-factor model. Journal of Cross-Cultural Psychology, 29(1), 119–149.
  71. Mather, M. E., Frank, H. J., Smith, J. M., Cormier, R. D., Muth, R. M., & Finn, J. T. (2012). Assessing freshwater habitat of adult anadromous alewives using multiple approaches. Marine and Coastal Fisheries, 4(1), 188–200.
  72. Mayr, E. (1982). The growth of biological thought: Diversity, evolution, and inheritance. Cambridge, MA: Harvard University Press.
  73. Meisenberg, G., & Woodley, M.A. (2013). Global behavioural variation: A test of differential-K. Personality & Individual Differences. 55, 273–278.
  74. Miller, G. F. (2000a). Mental traits as fitness indicators. In D. LeCrosy & P. Moller (Eds.), Evolutionary perspectives on human reproductive behavior (pp. 62–74). New York, NY: New York Academy of Sciences.
  75. Miller, G. F. (2000b). Sexual selection for indicators of intelligence. In G. R. Bock, J. A. Goode, & K. Webb (Eds.), The nature of intelligence (pp. 260–275). Chichester, England: Wiley.
  76. Mischel, W., & Ebbesen, E. B. (1970). Attention in delay of gratification. Journal of Personality and Social Psychology, 16, 329–337.
  77. Mischel, W., Shoda, Y., & Rodriguez, M. I. (1989). Delay of gratification in children. Science, 244(4907), 933–938.
  78. Musek, J. (2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233.
  79. Nesse, R. M. (1990). The evolutionary functions of repression and the ego defense. Journal of the American Academy of Psychoanalysis, 18, 260–285.
  80. Nesse, R. M. (2007). Runaway social selection for displays of partner value and altruism. Biological Theory, 2(2), 143–155.
  81. Novgorodoff, B. D. (1974). Boy meets girl: Machiavellianism and romantic attraction. Personality and Social Psychology Bulletin, 1(1), 307–309.
  82. Olderbak, S., & Figueredo, A. J. (2012). Shared life history strategy as a strong predictor of romantic relationship satisfaction. Journal of Social, Evolutionary, and Cultural Psychology, 6, 111–131.
  83. Olderbak, S. G., Wolf, P. S. A., & Figueredo, A. J. (2014). Positive assortative pairing in social and romantic partners: 2. A quasi-experimental laboratory study of alternative proximate mechanisms. Manuscript in preparation.
  84. Repp, A. C., Nieminen, G. S., Olinger, E., & Brsca, R. (1988). Direct observation: Factors affecting the accuracy of observers. Exceptional Children, 55, 29–36.
  85. Riemann, R., & Kandler, C. (2010), Construct validation using multitrait-multimethod-twin data: The case of a general factor of personality. European Journal of Personality, 24, 258–277. doi: 10.1002/per.760
  86. Rushton, J. P. (1985). Differential K theory: The sociobiology of individual and group differences. Personality and Individual Differences, 6, 441–452.
  87. Rushton, J. P. (2000). Race, evolution and behavior: A life history perspective (3rd ed.). Port Huron, MI: Charles Darwin Research Institute.
  88. Rushton, J. P. (2004). Placing intelligence into an evolutionary framework, or how g fits into the r-K matrix of life history traits including longevity. Intelligence, 32, 321–328.
  89. Rushton, J. P., Bons, T. A., & Hur, Y.-M. (2008). The genetics and evolution of a general factor of personality. Journal of Research in Personality, 42, 1173–1185.
  90. Rushton, J. P., & Irwing, P. (2009). A general factor of personality in the Millon Clinical Multiaxial Inventory-III, the dimensional assessment of personality pathology, and the personality assessment inventory. Journal of Research in Personality, 43, 1091–1095.
  91. Rushton, J. P., & Irwing, P. (2011). The general factor of personality: Normal and abnormal. In T. Chamorro-Premuzic, S. von Stumm, & A. Furnham (Eds.), The Wiley-Blackwell handbook of individual differences (pp. 134–163). Hoboken, NJ: Wiley.
  92. Sherman, R. A., Figueredo, A. J., & Funder, D. C. (2013). The behavioural correlates of overall and distinctive life history strategy. Journal of Personality and Social Psychology, 105, 873–888.
  93. Spearman, C. (1904). “ General intelligence,” objectively determined and measured. The American Journal of Psychology, 15(2), 201–292.
  94. Stevenson-Hinde, J., Stillwell-Barnes, R., & Zunz, M. (1980a). Individual characteristics in young rhesus monkeys: Consistency and change. Primates, 21, 498–509.
  95. Stevenson-Hinde, J., Stillwell-Barnes, R., & Zunz, M. (1980b). Subjective assessment of rhesus monkeys over four successive years. Primates, 21, 66–82.
  96. Templer, D. I. (2008). Correlational and factor analytic support for Rushton's differential-K life history theory. Personality and Individual Differences, 45, 440–444.
  97. Tinbergen, N. (1963). On aims and methods of ethology. Zeitschrift für Tierpsychologie, 20, 410–433.
  98. Tooby, J., & Cosmides, S. (1990). On the universality of human nature and the uniqueness of the individual: The role of genetics and adaptation [Special issue: Biological foundations of personality—Evolution, behavioral genetics, and psychophysiology]. Journal of Personality, 58, 17–67.
  99. Weiss, A., Adams, M. J., & Johnson, W. (2011). The big none: No evidence for a general factor of personality in chimpanzees, orangutans, or rhesus macaques. Journal of Research in Personality, 45, 393–397.
  100. Weiss, A., King, J. E., & Enns, R. M. (2002). Subjective well-being is heritable and genetically correlated with dominance in chimpanzees. Journal of Personality and Social Psychology, 83, 1141–1149.
  101. Wilson, D. S. (1994). Adaptive genetic variation and human evolutionary psychology. Ethology and Sociobiology, 15, 219–235.
  102. Wittmann, W. W. (2012). Principles of symmetry in evaluation research with implications for offender treatment. In T. Bliesener, A. Beelmann, & M. Stemmler (Eds.), Antisocial behavior and crime: Contributions of developmental and evaluation research to prevention and intervention (pp. 357–368). Cambridge, MA: Hogrefe.
  103. Woodley, M. A. (2011). The cognitive differentiation-integration effort hypothesis: A synthesis between the fitness indicator and life history models of human intelligence. Review of General Psychology, 15, 228–245.
  104. Woodley, M. A., & Fernandes, H. B. F. (2014). Strategic and cognitive differentiation-integration effort in a study of 76 countries. Personality & Individual Differences, 57, 3–7.
  105. Woodley, M. A., Fernandes, H. B. F., & Madison, G. (2014). Strategic differentiation-integration effort amongst the 47 prefectures of Japan. Personality and Individual Differences, 63, 64–68.
  106. Woodley, M. A., Figueredo, A. J., Brown, S. D., & Ross, K. C. (2013). Four successful tests of the cognitive differentiation-integration effort hypothesis. Intelligence, 41, 832–842.
  107. Woodley of Menie, M. A., Figueredo, A. J., Cabeza de Baca, T., Fernandes, H. B. F., Madison, G., & Black, C. (2015). Strategic differentiation and integration of genomic-level heritabilities facilitate individual differences in preparedness and plasticity of human life history. Frontiers in Psychology, 6, 422.