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 & Complex network. The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Pastoralism and wealth inequality: Revisiting an old question

Abstract: Pastoralist societies are often portrayed as economically egalitarian, reflecting the volatile nature of livestock herds and the existence of multiple institutions that allow for the redistribution of wealth as a form of insurance. Motivated by an interest in the role of intergenerational transmission in structuring persistent inequality, we examine the extent of intergenerational transmission of material wealth (four measures) and embodied wealth (one measure) for four pastoral populations from different parts of the world (East Africa, West Africa, and southwest Asia). We find substantial levels of intergenerational transmission and marked economic inequality. We argue that the high correspondence between the material wealth of parents and offspring reflects the importance of the family in the transmission of wealth through bequests, positive assortment by wealth in the domains of marriage and herd management, and positive returns to scale as might occur when raising or defending large herds. We conclud...

Unique Mutational Patterns in the Envelope α2 Amphipathic Helix and Acquisition of Length in gp120 Hypervariable Domains Are Associated with Resistance to Autologous Neutralization of Subtype C Human Immunodeficiency Virus Type 1

Abstract: Autologous neutralizing antibodies (NAb) against human immunodeficiency virus type 1 generate viral escape variants; however, the mechanisms of escape are not clearly defined. In a previous study, we determined the susceptibilities of 48 donor and 25 recipient envelope (Env) glycoproteins from five subtype C heterosexual transmission pairs to NAb in donor plasma by using a virus pseudotyping assay, thereby providing an ideal setting to probe the determinants of susceptibility to neutralization. In the present study, acquisition of length in the Env gp120 hypervariable domains was shown to correlate with resistance to NAb in donor plasma (P = 0.01; Kendall's tau test) but not in heterologous plasma. Sequence divergence in the gp120 V1-to-V4 region also correlated with resistance to donor (P = 0.0002) and heterologous (P = 0.001) NAb. A mutual information analysis suggested possible associations of nine amino acid positions in V1 to V4 with NAb resistance to the donor's antibodies, and five of these were located within an 18-residue amphipathic helix (α2) located on the gp120 outer domain. High nonsynonymous-to-synonymous substitution (dN/dS) ratios, indicative of positive selection, were also found at these five positions in subtype C sequences in the database. Nevertheless, exchange of the entire α2 helix between resistant donor Envs and sensitive recipient Envs did not alter the NAb phenotype. The combined mutual information and dN/dS analyses suggest that unique mutational patterns in α2 and insertions in the V1-to-V4 region are associated with NAb resistance during subtype C infection but that the selected positions within the α2 helix must be linked to still other changes in Env to confer antibody escape. These findings suggest that subtype C viruses utilize mutations in the α2 helix for efficient viral replication and immune avoidance.

The misleading narrative of the canonical faculty productivity trajectory

Abstract: A scientist may publish tens or hundreds of papers over a career, but these contributions are not evenly spaced in time. Sixty years of studies on career productivity patterns in a variety of fields suggest an intuitive and universal pattern: Productivity tends to rise rapidly to an early peak and then gradually declines. Here, we test the universality of this conventional narrative by analyzing the structures of individual faculty productivity time series, constructed from over 200,000 publications and matched with hiring data for 2,453 tenure-track faculty in all 205 PhD-granting computer science departments in the United States and Canada. Unlike prior studies, which considered only some faculty or some institutions, or lacked common career reference points, here we combine a large bibliographic dataset with comprehensive information on career transitions that covers an entire field of study. We show that the conventional narrative confidently describes only one-fifth of faculty, regardless of department prestige or researcher gender, and the remaining four-fifths of faculty exhibit a rich diversity of productivity patterns. To explain this diversity, we introduce a simple model of productivity trajectories and explore correlations between its parameters and researcher covariates, showing that departmental prestige predicts overall individual productivity and the timing of the transition from first- to last-author publications. These results demonstrate the unpredictability of productivity over time and open the door for new efforts to understand how environmental and individual factors shape scientific productivity.

Simple model of epidemics with pathogen mutation.

Abstract: We study how the interplay between the memory immune response and pathogen mutation affects epidemic dynamics in two related models. The first explicitly models pathogen mutation and individual memory immune responses, with contacted individuals becoming infected only if they are exposed to strains that are significantly different from other strains in their memory repertoire. The second model is a reduction of the first to a system of difference equations. In this case, individuals spend a fixed amount of time in a generalized immune class. In both models, we observe four fundamentally different types of behavior, depending on parameters: (1) pathogen extinction due to lack of contact between individuals; (2) endemic infection; (3) periodic epidemic outbreaks; and (4) one or more outbreaks followed by extinction of the epidemic due to extremely low minima in the oscillations. We analyze both models to determine the location of each transition. Our main result is that pathogens in highly connected populations must mutate rapidly in order to remain viable.