Santa Fe Institute

About: Santa Fe Institute is a nonprofit organization based out in Santa Fe, New Mexico, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Policies Designed for Self-Interested Citizens May Undermine "The Moral Sentiments": Evidence from Economic Experiments

Abstract: High-performance organizations and economies work on the basis not only of material interests but also of Adam Smith's "moral sentiments." Well-designed laws and public policies can harness self-interest for the common good. However, incentives that appeal to self-interest may fail when they undermine the moral values that lead people to act altruistically or in other public-spirited ways. Behavioral experiments reviewed here suggest that economic incentives may be counterproductive when they signal that selfishness is an appropriate response; constitute a learning environment through which over time people come to adopt more self-interested motivations; compromise the individual's sense of self-determination and thereby degrade intrinsic motivations; or convey a message of distrust, disrespect, and unfair intent. Many of these unintended effects of incentives occur because people act not only to acquire economic goods and services but also to constitute themselves as dignified, autonomous, and moral individuals. Good organizational and institutional design can channel the material interests for the achievement of social goals while also enhancing the contribution of the moral sentiments to the same ends.

The Diffusion of Microfinance

Abstract: To study the impact of the choice of injection points in the diffusion of a new product in a society, we developed a model of word-of-mouth diffusion and then applied it to data on social networks and participation in a newly available microfinance loan program in 43 Indian villages. Our model allows us to distinguish information passing among neighbors from direct influence of neighbors' participation decisions, as well as information passing by participants versus nonparticipants. The model estimates suggest that participants are seven times as likely to pass information compared to informed nonparticipants, but information passed by nonparticipants still accounts for roughly one-third of eventual participation. An informed household is not more likely to participate if its informed friends participate. We then propose two new measures of how effective a given household would be as an injection point. We show that the centrality of the injection points according to these measures constitutes a strong and significant predictor of eventual village-level participation.

Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change

Abstract: Biological stoichiometry theory considers the balance of multiple chemical elements in living systems, whereas metabolic scaling theory considers how size affects metabolic properties from cells to ecosystems. We review recent developments integrating biological stoichiometry and metabolic scaling theories in the context of plant ecology and global change. Although vascular plants exhibit wide variation in foliar carbon:nitrogen:phosphorus ratios, they exhibit a higher degree of 'stoichiometric homeostasis' than previously appreciated. Thus, terrestrial carbon:nitrogen:phosphorus stoichiometry will reflect the effects of adjustment to local growth conditions as well as species' replacements. Plant stoichiometry exhibits size scaling, as foliar nutrient concentration decreases with increasing plant size, especially for phosphorus. Thus, small plants have lower nitrogen:phosphorus ratios. Furthermore, foliar nutrient concentration is reflected in other tissues (root, reproductive, support), permitting the development of empirical models of production that scale from tissue to whole-plant levels. Plant stoichiometry exhibits large-scale macroecological patterns, including stronger latitudinal trends and environmental correlations for phosphorus concentration (relative to nitrogen) and a positive correlation between nutrient concentrations and geographic range size. Given this emerging knowledge of how plant nutrients respond to environmental variables and are connected to size, the effects of global change factors (such as carbon dioxide, temperature, nitrogen deposition) can be better understood.

When individual behaviour matters: homogeneous and network models in epidemiology

Abstract: Heterogeneity in host contact patterns profoundly shapes population-level disease dynamics. Many epidemiological models make simplifying assumptions about the patterns of disease-causing interactions among hosts. In particular, homogeneous-mixing models assume that all hosts have identical rates of disease-causing contacts. In recent years, several network-based approaches have been developed to explicitly model heterogeneity in host contact patterns. Here, we use a network perspective to quantify the extent to which real populations depart from the homogeneous-mixing assumption, in terms of both the underlying network structure and the resulting epidemiological dynamics. We find that human contact patterns are indeed more heterogeneous than assumed by homogeneous-mixing models, but are not as variable as some have speculated. We then evaluate a variety of methodologies for incorporating contact heterogeneity, including network-based models and several modifications to the simple SIR compartmental model. We conclude that the homogeneous-mixing compartmental model is appropriate when host populations are nearly homogeneous, and can be modified effectively for a few classes of non-homogeneous networks. In general, however, network models are more intuitive and accurate for predicting disease spread through heterogeneous host populations.

Perspective: Evolution and detection of genetic robustness.

Abstract: Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms underlying robustness are diverse, ranging from thermodynamic stability at the RNA and protein level to behavior at the organismal level. Phenotypes can be robust either against heritable perturbations (e.g., mutations) or nonheritable perturbations (e.g., the weather). Here we primarily focus on the first kind of robustness-genetic robustness-and survey three growing avenues of research: (1) measuring genetic robustness in nature and in the laboratory; (2) understanding the evolution of genetic robustness; and (3) exploring the implications of genetic robustness for future evolution.