Evan

A fictional account of how a speculative hypothesis about how to eliminate the "we/they" distinction is implemented by rearing children (during early critical years) in "aggregates in flux" instead of in kinship-based families: In "aggregates in flux," the individual members would be constantly varying (and unrelated, genetically). The only invariant would be that they were all human

Spare Me the Complements: An Immoderate Proposal for Eliminating the "We/They" Category Boundary

A speculative hypothesis about how to eliminate the "we/they" distinction by rearing children (during early critical years) in "aggregates in flux" instead of in kinship-based families: A category cannot be formed from positive examples only: one must be able to sample both what is and what is not in a category in order to recognise the category at all. The basis for the distinction is the features shared by the members (invariants), and absent from the non-members. In "aggregates in flux," the individual members would be constantly varying (and unrelated, genetically). The only invariant would be that they are all human

Spare Me the Complements: An Immoderate Proposal for Eliminating the "We/They" Category Boundary

A speculative hypothesis about how to eliminate the "we/they" distinction by rearing children (during early critical years) in "aggregates in flux" instead of in kinship-based families: A category cannot be formed from positive examples only: one must be able to sample both what is and what is not in a category in order to recognise the category at all. The basis for the distinction is the features shared by the members (invariants), and absent from the non-members. In "aggregates in flux," the individual members would be constantly varying (and unrelated, genetically). The only invariant would be that they are all human

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even data sets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper we re-examine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (6 CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1357 individuals in 124 pedigrees) takes less than 2 minutes and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 minutes and 1.5 GB of memory

Dispositional Influences on Attributions Concerning Absenteeism

Because the degree to which absenteeism is within or beyond an employee\u27s control is a significant yet unresolved issue in the absence literature, it is important to understand the factors which influence employees\u27 attributions about the causes of absence events. As a result of recent research suggesting that personality variables are important influences on work attitudes and behaviors, the present study took a dispositional approach in investigating the predictors of employee absence attributions. Using data collected from three sources, between-subjects analyses suggested a number of dispositional influences on absence attributions. Within-subjects analyses suggested that the factors leading to external attributions vary widely across individuals

Kinship, lineage identity, and an evolutionary perspective on the structure of cooperative big game hunting groups in Indonesia.

Work was conducted among traditional, subsistence whale hunters in Lamalera, Indonesia in order to test if kinship or lineage membership is more important for explaining the organization of cooperative hunting parties ranging in size from 8-14 men. Crew identifications were collected for all 853 hunts that occurred between May 3 and August 5, 1999. Lineage identity and genetic relatedness were determined for a sample of 189 hunters. Results of matrix regression show that kinship explains little of the hunters' affiliations independent of lineage identity. Crews are much more related amongst themselves than expected by chance. This is due, however, to the correlation between lineage membership and kinship. Lineage members are much more likely to affiliate in crews, but beyond r = 0.5 kin are just as likely not to affiliate. The results are discussed vis-à-vis the evolution of cooperation and group identity

Kin Cognition and Communication: What Talking, Gesturing, and Drawing About Family Can Tell us About the Way We Think About This Core Social Structure

When people talk about kinship systems, they often use co-speech gestures and other representations to elaborate. This paper investigates such polysemiotic (spoken, gestured, and drawn) descriptions of kinship relations, to see if they display recurring patterns of conventionalization that capture specific social structures. We present an exploratory hypothesis-generating study of descriptions produced by a lesser-known ethnolinguistic community to the cognitive sciences: the Paamese people of Vanuatu. Forty Paamese speakers were asked to talk about their family in semi-guided kinship interviews. Analyses of the speech, gesture, and drawings produced during these interviews revealed that lineality (i.e., mother's side vs. father's side) is lateralized in the speaker's gesture space. In other words, kinship members of the speaker's matriline are placed on the left side of the speaker's body and those of the patriline are placed on their right side, when they are mentioned in speech. Moreover, we find that the gesture produced by Paamese participants during verbal descriptions of marital relations are performed significantly more often on two diagonal directions of the sagittal axis. We show that these diagonals are also found in the few diagrams that participants drew on the ground to augment their verbo-gestural descriptions of marriage practices with drawing. We interpret this behavior as evidence of a spatial template, which Paamese speakers activate to think and communicate about family relations. We therefore argue that extending investigations of kinship structures beyond kinship terminologies alone can unveil additional key factors that shape kinship cognition and communication and hereby provide further insights into the diversity of social structures

Bioinspired Infrastructure Design: Leveraging Kinship Coefficients in Eusocial Animals for Resilient Systems

This study introduces a novel bioinspired algorithm influenced by the kinship coefficients observed in eusocial animals, particularly honeybees (Apis mellifera). In our study, we present a novel bioinspired algorithm, taking inspiration from honeybee kinship coefficient, tailored for optimizing resource allocation in disaster scenarios. This focuses on innovative product-service and energy systems by proposing an infrastructure design that is both resilient and adaptable. By emulating the kinship coefficient observed in bees, we offer an algorithm that enhances the effectiveness of firefighting resources, underscoring the potential of bioinspired computing to revolutionize emergency management and resilience within the context of product-service systems. Our hypothesis is, if the algorithm is inspired by the kinship coefficient observed in bee colonies, then it is possible to improve the allocation and effectiveness of firefighting resources, because these biological models of organization and problem-solving are optimized through evolutionary processes for resilience and adaptability. Our study sets a new paradigm in emergency management, proposing resilient, adaptable, and efficient systems derived from the sophisticated social organizations of eusocial species. Through this work, we demonstrate the value of leveraging natural models of organization to solve complex, dynamic human problems, with potential implications across a spectrum of applications beyond firefighting. Keywords: Bioinspired algorithm; Kinship coefficients; Resource allocation optimization; Emergency management; Resilient system