Multiple successful tests of the Strategic Differentiation-Integration Effort (SD-IE) hypothesis.

Abstract

The Strategic Differentiation-Integration Effort (SD-IE) hypothesis predicts regulation by life history speed (K) of the magnitudes of the correlations among its components, such that individuals with slower life history strategies exhibit life history traits that are less correlated with each other than individuals with faster life history strategies. This conative differentiation among high-K individuals is proposed to arise due to the elevated social competition in stable, predictable environments faced by these individuals and to facilitate mutualistic rather than antagonistic social interaction strategies via social-ecological nichesplitting and domain-specific resource allocation. We tested the predictions of SD-IE regarding relations among life history traits using the Continuous Parameter Estimation Method on data from two college student convenience samples, one all-female sample (N=382) and one mixed-sex sample (N=205), as well as two nationally-representative samples of the US population, the MIDUS (National Survey of Midlife Development in the United States, N=2080) and the NLSY (National Longitudinal Survey of Youth, N=5082). The predicted SD-IE effects were statistically significant and in the expected negative direction among most indicators of the lower-order slow life history factors and among all indicators of the single higher-order slow life history Super-K factor.

Measures of domain-specific resource allocations in life history strategy: Indicators of a latent common factor or ordered developmental sequence?

“…Broadly, the measures across the samples utilize items and subscales that capture the six social affordance areas in which individuals can invest time and energy (Figueredo, Patch, & Ceballos Gomez, 2015). Prior research (e.g., Figueredo, Woodley, Brown, & Ross, 2013) has compared across disparate measures of psychometric life history and yielded similar results. Study 1.…”

“…Study 1. The first study utilized subscales in the MIDUS that had been previously identified as converging on a single life history factor (Figueredo et al, 2004, but were reorganized into the different functional domains reflected in the subscales of the Arizona Life History Battery (ALHB; as had been done in Figueredo, Woodley, Brown, and Ross (2013), which supported the validity of these secondary aggregations by showing the part-whole correlations between each of the original MIDUS K-Factor indicators and the functional (ALHB-inspired) composites to which it had been theoretically assigned. In that study, multiple MIDUS scales had been aggregated into the functional domains specified by the ALHB for comparison, but the component MIDUS scales were in no way modified for this purpose.…”

Life History Selection and Phenotypic Diversification

“…Savantism is frequently associated with autistic-like personality (Treffert, 2009), which, based on Del Giudice's schema, is associated with slow life history. Woodley (2011) posited that high differentiation effort stemming from slow life history could account for this phenotype, despite Savant's exhibiting lower g. Similarly, Figueredo et al (2013) posited that those with autistic-like personalities constitute a distinct morph of slow life history strategy, as illustrated by contrasting the characteristics of the typical high-K population (who are characterized by high social effectiveness, as evidenced by high GFP; Figueredo et al, 2004) with those of individuals exhibiting autistic-like personality (who are typically COMMENTARIES characterized by low social effectiveness). Similarly, those with autistic-like personalities exhibit a strong tilt toward visuospatial ability and away from verbal ability (Del Giudice, Angeleri, Brizio & Elena, 2010).…”

The Experimenting Society

“…Specific theoretical justification for the construction of each of these lower-order and higher-order common factors using MIDUS data was published in Figueredo, Vásquez, Brumbach, and Schneider (2004;. The current hierarchical system for data aggregation, according to domain-specific resource allocations, was detailed in Figueredo, Woodley, Brown, and Ross (2013) and had also been applied in previous biometric behavioral-genetic models by Figueredo and Rushton (2009). However, only the following subset of items and scales that were sampled in both waves of data collection were used in the analyses reported in the present paper:…”

“…The K-Factor  The Self Scale was composed of MIDUS Subscales assessing Insight (4), Persistence (5), Positive Reappraisals (4), Self-Directedness (3), Agency (5), and Financial Status (6), which had been previously analyzed as separate scales in Figueredo, Vásquez, Brumbach, and Schneider (2004; but were subsequently aggregated in Figueredo, Woodley, Brown, and Ross (2013);  The Romantic Partner Attachment Scale was constructed from the MIDUS Marital Relationship Quality Subscale (31);  The Family Support Scale was constructed from the MIDUS Family Support Subscale (6);  The Friends Support Scale was constructed from the MIDUS Friends Support Subscale (6);  The General Social Altruism Scale was composed of MIDUS Subscales assessing Close Relationships (2), Children Relationship Quality (5), and Communitarian Beliefs (13), which had been previously analyzed as separate scales in Figueredo, Vásquez, Brumbach, and Schneider (2004; but were subsequently aggregated in Figueredo, Woodley, Brown, and Ross (2013);  The Religiosity Scale was constructed from the MIDUS Religiosity…”