| 1. |
- Carroll, Joseph, et al.
(författare)
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Biocultural Theory: The Current State of Knowledge
- 2017
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Ingår i: Evolutionary Behavioral Sciences. - : American Psychological Association (APA). - 2330-2925 .- 2330-2933. ; 11:1, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Biocultural theory is an integrative research program designed to investigate the causal interactions between biological adaptations and cultural constructions. From the biocultural perspective, cultural processes are rooted in the biological necessities of the human life cycle: specifically human forms of birth, growth, survival, mating, parenting, and sociality. Conversely, from the biocultural perspective, human biological processes are constrained, organized, and developed by culture, which includes technology, culturally specific socioeconomic and political structures, religious and ideological beliefs, and artistic practices such as music, dance, painting, and storytelling. Establishing biocultural theory as a program that self-consciously encompasses the different particular forms of human evolutionary research could help scholars and scientists envision their own specialized areas of research as contributions to a coherent, collective research program. This article argues that a mature biocultural paradigm needs to be informed by at least 7 major research clusters: (a) gene-culture coevolution; (b) human life history theory; (c) evolutionary social psychology; (d) anthropological research on contemporary hunter-gatherers; (e) biocultural socioeconomic and political history; (f) evolutionary aesthetics; and (g) biocultural research in the humanities (religions, ideologies, the history of ideas, and the arts). This article explains the way these research clusters are integrated in biocultural theory, evaluates the level of development in each cluster, and locates current biocultural theory within the historical trajectory of the social sciences and the humanities.
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| 2. |
- Figueredo, Aurelio-Jose, et al.
(författare)
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The cascade of chaos : From early adversity to interpersonal aggression
- 2021
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Ingår i: Evolutionary Behavioral Sciences. - : American Psychological Association (APA). - 2330-2925 .- 2330-2933. ; 15:3, s. 231-250
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Tidskriftsartikel (refereegranskat)abstract
- We developed a cascade model to reconstruct the hypothesized developmental progression from (1) increased resource instability during childhood to (2) decreased maternal sensitivity during childhood to (3) social vulnerability cognitive schemata to (4) faster life history strategies to (5) decreased behavioral regulation to (6) more pronounced “Dark Triad” personalities to (7) higher levels of interpersonal aggression in adulthood. The hypothesized cascade model also evaluated the cross-cultural generality of this theoretically-specified developmental progression across a sampling of different societies: (1) the United States ofAmerica (N=144); (2) Mexico (N=118); (3) Brazil (N=1091, distributed across 3 datacollection sites); (4) Sweden (N=144); and (5) the United Kingdom (N=260). Out of 21 interactive tests of the cross-cultural robustness of the main model parameters, only five reached statistical significance, and were relatively small in magnitude compared to their main effects. In no case did the magnitude and direction of the interaction completely reverse that of the corresponding main effect of the predictor, but merely either augmented or attenuated it somewhat across the affected study sites. We conclude that the results generally supported both the configural and metric invariance of the cascade model to a relatively high, albeit imperfect, degree.
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| 3. |
- Kvam, P. D., et al.
(författare)
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Rewards, risks, and reaching the right strategy : Evolutionary paths from heuristics to optimal decisions
- 2018
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Ingår i: Evolutionary Behavioral Sciences. - : American Psychological Association Inc.. - 2330-2925 .- 2330-2933. ; 12:3, s. 177-190
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Tidskriftsartikel (refereegranskat)abstract
- Theories of decision-making often posit optimal or heuristic strategies for performing a task. In optimal strategies, information is integrated over time in order to achieve the ideal outcomes; in the heuristic case, some shortcut or simplification is applied in order to make the decision faster or easier. In this article, we use a computational framework to study the evolution of both types of decision strategies in artificial agents. The fitness of these agents is assessed based on their performance on a sequential decision task where they must accurately identify the source of as many incoming information signals as they can over a finite time span. In order to examine what decision strategies evolve as a function of task characteristics, we manipulate the quality of decision information (difficulty) and the magnitude of punishments for incorrect answers. We find that trivial (but optimal) strategies evolve when punishment magnitude is lower than the reward magnitude for correct answers, and optimal information-integrating strategies evolve when either punishment magnitude is low or information quality is high. However, the computational demands of the task become much greater as information quality decreases and punishment magnitudes increase. In these cases, heuristics are used to maintain decision accuracy in spite of the limited cognitive resources agents have available. The results suggest that heuristics are an evolved response to environments with high demands on cognitive resources, where optimal strategies are particularly difficult to achieve. © 2018 American Psychological Association.
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