The Experts below are selected from a list of 6012 Experts worldwide ranked by ideXlab platform
Monica Tamariz - One of the best experts on this subject based on the ideXlab platform.
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Network Connectivity Dynamics, Cognitive Biases, and the Evolution of Cultural Diversity in Round‐Robin Interactive Micro‐Societies
Cognitive science, 2020Co-Authors: José Segovia-martín, Bradley Walker, Nicolas Fay, Monica TamarizAbstract:The distribution of Cultural Variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures. The temporal dynamics of social network connectivity, that is, the order in which individuals in a population interact with each other, has been largely unexplored. In this paper, we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of Cultural Variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, mid, and late full-population connectivity); content bias, or a preference for high-quality Variants; coordination bias, or whether agents tend to use self-produced Variants (egocentric bias), or to switch to Variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of Variant spread, with lower connectivity slowing down convergence of the population onto a single Cultural Variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, while larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high-quality Variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. We evaluate our simulations against existing data collected from previous experiments and show how our model reproduces the empirical patterns of convergence.
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Network connectivity dynamics affect the evolution of Culturally transmitted Variants.
arXiv: Social and Information Networks, 2019Co-Authors: Jose Segovia Martin, Bradley Walker, Nicolas Fay, Monica TamarizAbstract:The distribution of Cultural Variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures, which include several individual cognitive biases, demographic factors and social network structures. The temporal dynamics of social network connectivity, i.e. the order in which individuals in a population interact with each other, has been largely unexplored. In this paper we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of Cultural Variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, middle and late full-population connectivity); content bias, or a preference for high-quality Variants; coordination bias, or whether agents tend to use self-produced Variants (egocentric bias), or to switch to Variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of Variant spread, with lower connectivity slowing down convergence of the population onto a single Cultural Variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, whilst larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high quality Variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. In this way, we provide for the first time a direct connection between the order of agents' interactions and punctuational evolution.
Marshall Abrams - One of the best experts on this subject based on the ideXlab platform.
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Cultural Variant interaction in teaching and transmission.
The Behavioral and brain sciences, 2015Co-Authors: Marshall AbramsAbstract:Focus on the way in which Cultural Variants affect other Variants' probabilities of transmission in modeling and empirical work can enrich Kline's conceptualization of teaching. For example, the problem of communicating complex cumulative culture is an adaptive problem; teaching methods that manage transmission so that acquisition of some Cultural Variants increases the probability of acquiring others, provide a partial solution.
Lauren E. Gulbas - One of the best experts on this subject based on the ideXlab platform.
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a Cultural idiom of distress?
2016Co-Authors: Luis H. Zayas, Lauren E. GulbasAbstract:The high rates of suicide attempts among adolescent Hispanic females in the United States have been well established by epidemiological and clinical studies. In this paper, we review the research history of Latina suicide attempts and their characteristics. Then we apply multi-faceted conceptual and empirical criteria found in the anthropological and psychiatric literature about Cultural idioms of distress to the suicide attempts of young Latinas. We contrast the suicide-attempt phenomenon to the well-known ataque de nervios and propose that the phenomenon may reflect a developmental or Cultural Variant of the ataque. The attempt-as-idiom proposition is intended to invite discussion that can deepen our understanding of the Cultural roots of the suicide attempts and their possible designation as Cultural idiom. Establishing the meaning of suicide attempts within a Cultural perspective can assist psychological and psychiatric research and clinical interventions
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Are suicide attempts by young Latinas a Cultural idiom of distress
Transcultural psychiatry, 2012Co-Authors: Luis H. Zayas, Lauren E. GulbasAbstract:The high rates of suicide attempts among adolescent Hispanic females in the United States have been well established by epidemiological and clinical studies. In this paper, we review the research history of Latina suicide attempts and their characteristics. Then we apply multi-faceted conceptual and empirical criteria found in the anthropological and psychiatric literature about Cultural idioms of distress to the suicide attempts of young Latinas. We contrast the suicide-attempt phenomenon to the well-known ataque de nervios and propose that the phenomenon may reflect a developmental or Cultural Variant of the ataque. The attempt-as-idiom proposition is intended to invite discussion that can deepen our understanding of the Cultural roots of the suicide attempts and their possible designation as Cultural idiom. Establishing the meaning of suicide attempts within a Cultural perspective can assist psychological and psychiatric research and clinical interventions.
Kiyosi Takahasi - One of the best experts on this subject based on the ideXlab platform.
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Evolution of Transmission Bias in Cultural Inheritance
Journal of theoretical biology, 1998Co-Authors: Kiyosi TakahasiAbstract:Abstract Evolution of transmission bias in Cultural inheritance is investigated using simple models of Cultural selection. Conventional models of Cultural transmission describe Cultural changes by incorporating transmission bias and non-vertical pathways into the ordinary population genetic framework. The methodology has been successful in understanding Cultural changes in terms of natural selection, but it is difficult to see from the theoretical framework how biased transmission in favor of maladaptive traits might have evolved. To show that ordinary Cultural processes lead at times to the evolution of a preference that favors a deleterious Cultural Variant, this study presents an alternative model of Cultural transmission, where Cultural elements are transmitted in a manner more like infections in epidemiological transmission. An ordinary equilibrium analysis indicates that, under certain conditions, runaway dynamics emerges and the coevolution of a maladaptive Cultural Variant and an associated preference in favor of the maladaptive Variant is observed. If the preference of an individual does not change during its ontogeny (e.g., if it is transmitted genetically), however, than Cultural selection alone does not produce such runaway dynamics, and only those preferences that favor adaptive Variants should eventually evolve. Since Cultural processes may at times result in a reduction in the fitness of individuals, simplistic adaptive interpretations of culture are unconvincing without detailed specification of the Cultural processes involved. Moreover, Cultural runaway of this kind may help to explain the existence of traits that are apparently maladaptive at the individual level but may be advantageous for the group. Inferences are also made regarding the observed differences between human and non-human social information transfer.
Bradley Walker - One of the best experts on this subject based on the ideXlab platform.
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Network Connectivity Dynamics, Cognitive Biases, and the Evolution of Cultural Diversity in Round‐Robin Interactive Micro‐Societies
Cognitive science, 2020Co-Authors: José Segovia-martín, Bradley Walker, Nicolas Fay, Monica TamarizAbstract:The distribution of Cultural Variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures. The temporal dynamics of social network connectivity, that is, the order in which individuals in a population interact with each other, has been largely unexplored. In this paper, we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of Cultural Variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, mid, and late full-population connectivity); content bias, or a preference for high-quality Variants; coordination bias, or whether agents tend to use self-produced Variants (egocentric bias), or to switch to Variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of Variant spread, with lower connectivity slowing down convergence of the population onto a single Cultural Variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, while larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high-quality Variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. We evaluate our simulations against existing data collected from previous experiments and show how our model reproduces the empirical patterns of convergence.
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Network connectivity dynamics affect the evolution of Culturally transmitted Variants.
arXiv: Social and Information Networks, 2019Co-Authors: Jose Segovia Martin, Bradley Walker, Nicolas Fay, Monica TamarizAbstract:The distribution of Cultural Variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures, which include several individual cognitive biases, demographic factors and social network structures. The temporal dynamics of social network connectivity, i.e. the order in which individuals in a population interact with each other, has been largely unexplored. In this paper we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of Cultural Variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, middle and late full-population connectivity); content bias, or a preference for high-quality Variants; coordination bias, or whether agents tend to use self-produced Variants (egocentric bias), or to switch to Variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of Variant spread, with lower connectivity slowing down convergence of the population onto a single Cultural Variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, whilst larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high quality Variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. In this way, we provide for the first time a direct connection between the order of agents' interactions and punctuational evolution.
