Social stratification in networks: insights from co-authorship networks.

It has been observed that real-world social networks often exhibit stratification along economic or other lines, with consequences for class mobility and access to opportunities. With the rise in human interaction data and extensive use of online social networks, the structure of social networks (representing connections between individuals) can be used for measuring stratification. However, although stratification has been studied extensively in the social sciences, there is no single, generally applicable metric for measuring the level of stratification in a network. In this work, we first propose the novel Stratification Assortativity (StA) metric, which measures the extent to which a network is stratified into different tiers. Then, we use the StA metric to perform an in-depth analysis of the stratification of five co-authorship networks. We examine the evolution of these networks over 50 years and show that these fields demonstrate an increasing level of stratification over time, and, correspondingly, the trajectory of a researcher's career is increasingly correlated with her entry point into the network.

A method for assessing links between objectively measured food store scores and store & neighborhood favorability.

Worldwide, interest in research on methods to define access to healthy food at the local level has grown, given its central connection to carrying out a healthy lifestyle. Within this research domain, papers have examined the spatial element of food access, or individual perceptions about the food environment. To date, however, no studies have provided a method for linking a validated, objective measure of the food environment with qualitative data on how people access healthy food in their community. In this study, we present a methodology for linking scores from a modified Nutrition Environment Measures Survey in Stores (conducted at every store in our study site of Flint, Michigan) with perceptions of the acceptability of food stores and shopping locations drawn from seven focus groups (n = 53). Spatial analysis revealed distinct patterns in visiting and avoidance of certain store types. Chain stores tended to be rated more highly, while stores in neighborhoods with more African-American or poor residents were rated less favorably and avoided more frequently. Notably, many people avoided shopping in their own neighborhoods; participants traveled an average of 3.38 miles to shop for groceries, and 60% bypassed their nearest grocery store when shopping. The utility of our work is threefold. First, we provide a methodology for linking perceived and objective definitions of food access among a small sample that could be replicated in cities across the globe. Second, we show links between perceptions of food access and objectively measured food store scores to uncover inequalities in access in our sample to illustrate potential connections. Third, we advocate for the use of such data in informing the development of a platforms that aim to make the process of accessing healthy food easier via non-food retail based interventions. Future work can replicate our methods to both uncover patterns in distinct food environments and aid in advocacy around how to best intervene in the food environment in various locales.

Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling.

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.