The Norm of Reciprocity in Intergroup Context: A Normative-Identity Model

Reciprocity, regarded as a fundamental psychological phenomenon, may underlie a wide range of interpersonal and intergroup behaviors. Various disciplines such as behavioral economics, anthropology, sociology, and psychology as well documented how reciprocity is a strong determinant of human behavior. On the other hand, less is known about intergroup reciprocity, its functions and consequences as well as the psychological mechanisms through which these effects manifest, remain mostly unknown. In this paper, we propose a model to understand how the reciprocity norm operates in the intergroup contexts, through employing the Personal Norm of Reciprocity model (Perugini et al., 2003) and the Self-Categorization Theory (Turner et al., 1987). We suggest that the conditions that give rise to intergroup reciprocal behavior are ingroup identification, labeling outgroup behavior as a favor or transgression, and the internalization of the reciprocity norm. We also propose that the intergroup outcomes, such as ingroup favoritism, discrimination, collective action, and conflict resolution, might become more understandable when taking into account the reciprocity as an explanatory variable.

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

BACKGROUND

The aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patients with clear cell renal cell carcinoma (ccRCC) and demonstrate the impact of novel feature selection strategies and sub-segmentations on model interpretability.

METHODS

Contrast-enhanced CT scans from the first 101 patients recruited to the TRACERx Renal Cancer study (NCT03226886) were used to derive radiomics classification models to predict 20 molecular, histopathology and clinical target variables. Manual 3D segmentation was used in conjunction with automatic sub-segmentation to generate radiomics features from the core, rim, high and low enhancing sub-regions, and the whole tumour. Comparisons were made between two classification model pipelines: a Conventional pipeline reflecting common radiomics practice, and a Proposed pipeline including two novel feature selection steps designed to improve model interpretability. For both pipelines nested cross-validation was used to estimate prediction performance and tune model hyper-parameters, and permutation testing was used to evaluate the statistical significance of the estimated performance measures. Further model robustness assessments were conducted by evaluating model variability across the cross-validation folds.

RESULTS

Classification performance was significant (p < 0.05, H0:AUROC = 0.5) for 11 of 20 targets using either pipeline and for these targets the AUROCs were within ± 0.05 for the two pipelines, except for one target where the Proposed pipeline performance increased by > 0.1. Five of these targets (necrosis on histology, presence of renal vein invasion, overall histological stage, linear evolutionary subtype and loss of 9p21.3 somatic alteration marker) had AUROC > 0.8. Models derived using the Proposed pipeline contained fewer feature groups than the Conventional pipeline, leading to more straightforward model interpretations without loss of performance. Sub-segmentations lead to improved performance and/or improved interpretability when predicting the presence of sarcomatoid differentiation and tumour stage.

CONCLUSIONS

Use of the Proposed pipeline, which includes the novel feature selection methods, leads to more interpretable models without compromising prediction performance.

TRIAL REGISTRATION

NCT03226886 (TRACERx Renal).

Intra-colony venom diversity contributes to maintaining eusociality in a cooperatively breeding ant

BACKGROUND

Eusociality is widely considered to evolve through kin selection, where the reproductive success of an individual's close relative is favored at the expense of its own. High genetic relatedness is thus considered a prerequisite for eusociality. While ants are textbook examples of eusocial animals, not all ants form colonies of closely related individuals. One such example is the ectatommine ant Rhytidoponera metallica, which predominantly forms queen-less colonies that have such a low intra-colony relatedness that they have been proposed to represent a transient, unstable form of eusociality. However, R. metallica is among the most abundant and widespread ants on the Australian continent. This apparent contradiction provides an example of how inclusive fitness may not by itself explain the maintenance of eusociality and raises the question of what other selective advantages maintain the eusocial lifestyle of this species.

RESULTS

We provide a comprehensive portrait of the venom of R. metallica and show that the colony-wide venom consists of an exceptionally high diversity of functionally distinct toxins for an ant. These toxins have evolved under strong positive selection, which is normally expected to reduce genetic variance. Yet, R. metallica exhibits remarkable intra-colony variation, with workers sharing only a relatively small proportion of toxins in their venoms. This variation is not due to the presence of chemical castes, but has a genetic foundation that is at least in part explained by toxin allelic diversity.

CONCLUSIONS

Taken together, our results suggest that the toxin diversity contained in R. metallica colonies may be maintained by a form of group selection that selects for colonies that can exploit more resources and defend against a wider range of predators. We propose that increased intra-colony genetic variance resulting from low kinship may itself provide a selective advantage in the form of an expanded pharmacological venom repertoire. These findings provide an example of how group selection on adaptive phenotypes may contribute to maintaining eusociality where a prerequisite for kin selection is diminished.

The genome loading model for the origin and maintenance of sex in eukaryotes

Understanding why sexual reproduction-which involves syngamy (union of gametes) and meiosis-emerged and how it has subsisted for millions of years remains a fundamental problem in biology. Considered as the essence of sex, meiotic recombination is initiated by a DNA double-strand break (DSB) that forms on one of the pairing homologous chromosomes. This DNA lesion is subsequently repaired by gene conversion, the non-reciprocal transfer of genetic information from the intact homolog. A major issue is which of the pairing homologs undergoes DSB formation. Accumulating evidence shows that chromosomal sites where the pairing homologs locally differ in size, i.e., are heterozygous for an insertion or deletion, often display disparity in gene conversion. Biased conversion tends to duplicate insertions and lose deletions. This suggests that DSB is preferentially formed on the "shorter" homologous region, which thereby acts as the recipient for DNA transfer. Thus, sex primarily functions as a genome (re)loading mechanism. It ensures the restoration of formerly lost DNA sequences (deletions) and allows the efficient copying and, mainly in eukaryotes, subsequent spreading of newly emerged sequences (insertions) arising initially in an individual genome, even if they confer no advantage to the host. In this way, sex simultaneously repairs deletions and increases genetic variability underlying adaptation. The model explains a remarkable increase in DNA content during the evolution of eukaryotic genomes.

A Note Against the Use of "Belonging To" Properties in Multilevel Selection Theory

In this short paper, I argue against what I call the "belonging to" interpretation of group selection in scenarios in which a group's fitness is defined as the per capita reproductive output of the individuals of the group. According to this interpretation, group selection acts on "belonging to" properties of individuals, i.e. on relational or contextual properties that all the individuals of a group share simply by belonging to that group; thus, if differences in the individuals' "belonging to" properties cause differences in their fitness, group selection sensu the "belonging to" interpretation is said to be at work. I argue that the main problem with the "belonging to" interpretation is that it confuses evolutionary changes due to differences in environmental quality with evolutionary changes due to selection. In other words, I argue that, in the majority of cases, this interpretation actually takes the "selection" out of the "group selection" notion it aims to interpret: by adopting this perspective, one implicitly commits to explaining the evolutionary change under consideration not by a kind of selection (be it individual or group selection), but by differences in the environmental quality experienced by individual types.

Spare the rod and spoil the group's cultural fitness? Conditions under which corporal punishment leads to detrimental and beneficial outcomes

Corporal punishment of children is common across human history, and the specific practice of striking the buttocks, known as spanking, seems to have developed independently across a number of separate cultures. This pattern suggests adaptive value, posing a paradox in view of the many reviews stating that spanking has purely negative outcomes on future mental health, and the recommendation of the American Academy of Pediatrics that it be outlawed. We purport to resolve this paradox by separating this particular type of corporal punishment from less controlled lashing out in anger, and we reanalyze these reviews in terms of psychological and physical health outcomes. We find that spanking is associated with positive mental health outcomes when (1) performed by calm parents in a (2) ritualized, structured fashion and combined with (3) other disciplinary techniques within (4) a loving relationship with the child, typically (5) as part of the practice of moral, collective religiosity, and when (6) controlling for confounding variables. In that spanking is noticeably practiced by conservative religious cultural groups, we hypothesize that it can be a fitness-promoting form of behaviour in line with religiousness being an example of a group-fitness-promoting adaptation.

LOG-CONTRAST REGRESSION WITH FUNCTIONAL COMPOSITIONAL PREDICTORS: LINKING PRETERM INFANT'S GUT MICROBIOME TRAJECTORIES TO NEUROBEHAVIORAL OUTCOME

The neonatal intensive care unit (NICU) experience is known to be one of the most crucial factors that drive preterm infant's neurodevelopmental and health outcome. It is hypothesized that stressful early life experience of very preterm neonate is imprinting gut microbiome by the regulation of the so-called brain-gut axis, and consequently, certain microbiome markers are predictive of later infant neurodevelopment. To investigate, a preterm infant study was conducted; infant fecal samples were collected during the infants' first month of postnatal age, resulting in functional compositional microbiome data, and neurobehavioral outcomes were measured when infants reached 36-38 weeks of post-menstrual age. To identify potential microbiome markers and estimate how the trajectories of gut microbiome compositions during early postnatal stage impact later neurobehavioral outcomes of the preterm infants, we innovate a sparse log-contrast regression with functional compositional predictors. The functional simplex structure is strictly preserved, and the functional compositional predictors are allowed to have sparse, smoothly varying, and accumulating effects on the outcome through time. Through a pragmatic basis expansion step, the problem boils down to a linearly constrained sparse group regression, for which we develop an efficient algorithm and obtain theoretical performance guarantees. Our approach yields insightful results in the preterm infant study. The identified microbiome markers and the estimated time dynamics of their impact on the neurobehavioral outcome shed lights on the linkage between stress accumulation in early postnatal stage and neurodevelpomental process of infants.

Explanatory goals and explanatory means in multilevel selection theory

It has become customary in multilevel selection theory to use the same terms (namely "multilevel selection 1" and "multilevel selection 2") to denote both two explanatory goals (explaining why certain individual- and, respectively, group-level traits spread) and two explanatory means (namely, two kinds of group selection we may appeal to in such explanations). This paper spells out some of the benefits that derive from avoiding this terminological conflation. I argue that keeping explanatory means and goals well apart allows us to see that, contrary to a popular recent idea, Price's equation and contextual analysis-the statistical methods most extensively used for measuring the effects of certain evolutionary factors (like individual selection, group selection etc.) on the change in the focal individual trait in multilevel selection scenarios-do not come with built-in notions of group selection and, therefore, the efficacy of these methods at analyzing various kinds of cases does not constitute a basis for deciding how group selection should best be defined. Moreover, contrary to another widely accepted idea, I argue that more than one type of group selection may serve as explanatory means when one's goal is that of explaining the evolution of individual traits in multilevel selection scenarios and I spell out how this explanatory role should be understood.

Natural selection in compartmentalized environment with reshuffling

The emerging field of high-throughput compartmentalized in vitro evolution is a promising new approach to protein engineering. In these experiments, libraries of mutant genotypes are randomly distributed and expressed in microscopic compartments-droplets of an emulsion. The selection of desirable variants is performed according to the phenotype of each compartment. The random partitioning leads to a fraction of compartments receiving more than one genotype making the whole process a lab implementation of the group selection. From a practical point of view (where efficient selection is typically sought), it is important to know the impact of the increase in the mean occupancy of compartments on the selection efficiency. We carried out a theoretical investigation of this problem in the context of selection dynamics for an infinite non-mutating subdivided population that randomly colonizes an infinite number of patches (compartments) at each reproduction cycle. We derive here an update equation for any distribution of phenotypes and any value of the mean occupancy. Using this result, we demonstrate that, for the linear additive fitness, the best genotype is still selected regardless of the mean occupancy. Furthermore, the selection process is remarkably resilient to the presence of multiple genotypes per compartments, and slows down approximately inversely proportional to the mean occupancy at high values. We extend out results to more general expressions that cover nonadditive and non-linear fitnesses, as well non-Poissonian distribution among compartments. Our conclusions may also apply to natural genetic compartmentalized replicators, such as viruses or early trans-acting RNA replicators.

Group SLOPE - adaptive selection of groups of predictors

Sorted L-One Penalized Estimation (SLOPE, Bogdan et al., 2013, 2015) is a relatively new convex optimization procedure which allows for adaptive selection of regressors under sparse high dimensional designs. Here we extend the idea of SLOPE to deal with the situation when one aims at selecting whole groups of explanatory variables instead of single regressors. Such groups can be formed by clustering strongly correlated predictors or groups of dummy variables corresponding to different levels of the same qualitative predictor. We formulate the respective convex optimization problem, gSLOPE (group SLOPE), and propose an efficient algorithm for its solution. We also define a notion of the group false discovery rate (gFDR) and provide a choice of the sequence of tuning parameters for gSLOPE so that gFDR is provably controlled at a prespecified level if the groups of variables are orthogonal to each other. Moreover, we prove that the resulting procedure adapts to unknown sparsity and is asymptotically minimax with respect to the estimation of the proportions of variance of the response variable explained by regressors from different groups. We also provide a method for the choice of the regularizing sequence when variables in different groups are not orthogonal but statistically independent and illustrate its good properties with computer simulations. Finally, we illustrate the advantages of gSLOPE in the context of Genome Wide Association Studies. R package grpSLOPE with an implementation of our method is available on CRAN.

Variability in fitness effects can preclude selection of the fittest

Evolutionary biologists often predict the outcome of natural selection on an allele by measuring its effects on lifetime survival and reproduction of individual carriers. However, alleles affecting traits like sex, evolvability, and cooperation can cause fitness effects that depend heavily on differences in the environmental, social, and genetic context of individuals carrying the allele. This variability makes it difficult to summarize the evolutionary fate of an allele based solely on its effects on any one individual. Attempts to average over this variability can sometimes salvage the concept of fitness. In other cases evolutionary outcomes can only be predicted by considering the entire genealogy of an allele, thus limiting the utility of individual fitness altogether. We describe a number of intriguing new evolutionary phenomena that have emerged in studies that explicitly model long-term lineage dynamics and discuss implications for the evolution of infectious diseases.

Group-level events are catalysts in the evolution of cooperation

Group-level events, like fission and extinction, catalyze the evolution of cooperation in group-structured populations by creating new paths from uncooperative population states to more cooperative states. Group-level events allow cooperation to thrive under unfavorable conditions such as low intra-group assortment and moderate rates of migration, and can greatly speed up the evolution of cooperation when conditions are more favorable. The time-dependent effects of fission and extinction events are studied and illustrated here using a PDE model of a group-structured population based loosely on populations of hunter-gatherer tribes. By solving the PDE numerically we can compare models with and without group-level events, and explicitly calculate quantities associated with dynamics, like how long it takes a small population of cooperators to become a majority, as well as equilibrium population densities.

The spontaneous market order and evolution

Darwin's theory of natural selection and the idea of a spontaneous order share a fundamental feature: the claim that apparent design or order do not necessarily imply a designer or rational planning. But they also present important differences, which touch upon central questions such as the evolution of morality, the role of human agency in social evolution, the existence (or not) of directionality in undesigned processes, and the presence (nor not) of a providential element in evolutionary accounts. In this article, I explore these themes and probe the relationship between the notion of a spontaneous order and the theory of evolution by natural selection. The reflections of Nobel laureate in economics, F.A. von Hayek, provide the beginning and endpoint in this voyage, for they constitute the most pronounced effort to develop a full-fledged theory combining evolution and economics in recent times. But along the way, I also investigate the influence of classical political economy on Darwin's thought, primarily that of Adam Smith, and consider the reasons for which Darwin did not refer to Smith when discussing the principle of natural selection in The Origin of Species. I conclude that the spontaneous order, as understood by Hayek, and evolution by natural selection constitute two disparate concepts.

Sieve estimation of Cox models with latent structures

This article considers sieve estimation in the Cox model with an unknown regression structure based on right-censored data. We propose a semiparametric pursuit method to simultaneously identify and estimate linear and nonparametric covariate effects based on B-spline expansions through a penalized group selection method with concave penalties. We show that the estimators of the linear effects and the nonparametric component are consistent. Furthermore, we establish the asymptotic normality of the estimator of the linear effects. To compute the proposed estimators, we develop a modified blockwise majorization descent algorithm that is efficient and easy to implement. Simulation studies demonstrate that the proposed method performs well in finite sample situations. We also use the primary biliary cirrhosis data to illustrate its application.

Random and non-random mating populations: Evolutionary dynamics in meiotic drive

Game theoretic tools are utilized to analyze a one-locus continuous selection model of sex-specific meiotic drive by considering nonequivalence of the viabilities of reciprocal heterozygotes that might be noticed at an imprinted locus. The model draws attention to the role of viability selections of different types to examine the stable nature of polymorphic equilibrium. A bridge between population genetics and evolutionary game theory has been built up by applying the concept of the Fundamental Theorem of Natural Selection. In addition to pointing out the influences of male and female segregation ratios on selection, configuration structure reveals some noted results, e.g., Hardy-Weinberg frequencies hold in replicator dynamics, occurrence of faster evolution at the maximized variance fitness, existence of mixed Evolutionarily Stable Strategy (ESS) in asymmetric games, the tending evolution to follow not only a 1:1 sex ratio but also a 1:1 different alleles ratio at particular gene locus. Through construction of replicator dynamics in the group selection framework, our selection model introduces a redefining bases of game theory to incorporate non-random mating where a mating parameter associated with population structure is dependent on the social structure. Also, the model exposes the fact that the number of polymorphic equilibria will depend on the algebraic expression of population structure.

Evolution of fairness in the dictator game by multilevel selection

The most perplexing experimental results on fairness come from the dictator game where one of two players, the dictator, decides how to divide a resource with an anonymous player. The dictator, acting self-interestedly, should offer nothing to the anonymous second player, but in experimental studies, dictators offer much more than nothing. We developed a multilevel selection model to explain why people offer more than nothing in the dictator game. We show that fairness can evolve when population structure emerges from the aggregation and limited dispersal of offspring. We begin with an analytical model that shows how fair behavior can benefit groups by minimizing within-group variance in resources and thereby increasing group fitness. To investigate the generality of this result, we developed an agent-based model with agents that have no information about other agents. We allowed agents to aggregate into groups and evolve different levels of fairness by playing the dictator game for resources to reproduce. This allowed multilevel selection to emerge from the spatiotemporal properties of individual agents. We found that the population structure that emerged under low population densities was most conducive to the evolution of fairness, which is consistent with group selection as a major evolutionary force. We also found that fairness only evolves if resources are not too scarce relative to the lifespan of agents. We conclude that the evolution of fairness could evolve under multilevel selection. Thus, our model provides a novel explanation for the results of dictator game experiments, in which participants often fairly split a resource rather than keeping it all for themselves.

Multilevel selection, cooperation, and altruism : Reflections on unto others: The evolution and psychology of unselfish behavior

Unto Others (Sober and Wilson 1998) shows how the general principles of Multi-Level Selection (MLS) theory apply to selection at multiple levels of the biological hierarchy. It also argues for the existence of "genuine" evolutionary and psychological altruism. The authors' views on altruism do not follow logically from principles of MLS, and their failure do disentangle these two themes undermines their otherwise excellent presentation of MLS theory. Rebuttal of the view that human nature is completely selfish depends not on the prevalence of altruism but on the importance of group-advantageous traits that benefit both self and other group members without necessarily inflicting direct costs on outsiders.

Prosocial values and group assortation : Within an N-person prisoner's dilemma game

Ninety-five freshmen each recruited three peers to play a "group bidding game," an N-person prisoner's dilemma in which anyone could win movie tickets depending on their scores in the game. Prior to playing, all participants completed a measure of prosocial value orientation. Replicating and extending earlier findings (Sheldon and McGregor 2000), our results show that prosocial participants were at a disadvantage within groups. Despite this vulnerability, prosocial participants did no worse overall than asocial participants because a counteracting group-level advantage arose for prosocials, who tended to be concentrated in groups. Implications of this assortative process for the egoism/altruism debate, and for hierarchical selection theory, are discussed.

'From Man to Bacteria': W.D. Hamilton, the theory of inclusive fitness, and the post-war social order

W.D. Hamilton's theory of inclusive fitness aimed to define the evolved limits of altruism with mathematical precision. Although it was meant to apply universally, it has been almost irretrievably entwined with the particular case of social insects that featured in his famous 1964 papers. The assumption that social insects were central to Hamilton's early work contradicts material in his rich personal archive. In fact, careful study of Hamilton's notes, letters, diaries, and early essays indicates the extent to which he had humans in mind when he decided altruism was a topic worthy of biological inquiry. For this reason, this article reconsiders the role of extra-scientific factors in Hamilton's early theorizing. In doing so, it offers an alternative perspective as to why Hamilton saw self-sacrifice to be an important subject. Although the traditional narrative prioritizes his distaste for benefit-of-the-species explanations as a motivating factor behind his foundational work, I argue that greater attention ought to be given to Hamilton's hope that science could be used to address social ills. By reconsidering the meaning Hamilton intended inclusive fitness to have, we see that while he was no political ideologue, the socio-political relevance of his theory was nevertheless integral to its development.

The handicap principle and the argument of subversion from within

This paper examines the very disparate positions that various actors have taken towards the argument of subversion from within (a classical argument against the evolution of altruism by group selection) in a set of related debates on group selection, altruism and the handicap principle. Using this set of debates as a case study, this paper argues that different applications of epistemic values were one of the factors behind the disagreements between John Maynard Smith and Amotz Zahavi over a number of important evolutionary issues. The paper also argues that these different applications were connected to important epistemological differences related in part (but not solely) to their disciplinary background. Apart from conflicting evolutionary views concerning the theoretical feasibility of the handicap effect, these antagonists both differed in the confidence they ascribed to mathematical modeling and over the hereditary basis for altruistic behavior.

On the evolution of intergenerational division of labor, menopause and transfers among adults and offspring

We explain how upward transfers from adult children to their elderly parents might evolve as an interrelated feature of a deepening intergenerational division of labor. Humans have a particularly long period of juvenile dependence requiring both food and care time provided mainly by younger and older adults. We suggest that the division of labor evolves to exploit comparative advantage between young and old adults in fertility, childcare and foraging. Eventually the evolving division of labor reaches a limit when the grandmother's fertility reaches zero (menopause). Continuing, it may hit another limit when the grandmother's foraging time has been reduced to her subsistence needs. Further specialization can occur only with food transfers to the grandmother, enabling her to reduce her foraging time to concentrate on additional childcare. We prove that this outcome can arise only after menopause has evolved. We describe the conditions necessary for both group selection (comparative steady state reproductive fitness) and individual selection (successful invasion by a mutation), and interpret these conditions in terms of comparative advantages.

Semiparametric Regression Pursuit

The semiparametric partially linear model allows flexible modeling of covariate effects on the response variable in regression. It combines the flexibility of nonparametric regression and parsimony of linear regression. The most important assumption in the existing methods for the estimation in this model is to assume a priori that it is known which covariates have a linear effect and which do not. However, in applied work, this is rarely known in advance. We consider the problem of estimation in the partially linear models without assuming a priori which covariates have linear effects. We propose a semiparametric regression pursuit method for identifying the covariates with a linear effect. Our proposed method is a penalized regression approach using a group minimax concave penalty. Under suitable conditions we show that the proposed approach is model-pursuit consistent, meaning that it can correctly determine which covariates have a linear effect and which do not with high probability. The performance of the proposed method is evaluated using simulation studies, which support our theoretical results. A real data example is used to illustrated the application of the proposed method.