Evaluating community science

Community science-scientific investigation conducted partly or entirely by non-professional scientists-has many advantages. For example, community science mobilizes large numbers of volunteers who can, at low cost, collect more data than traditional teams of professional scientists. Participation in research can also increase volunteers' knowledge about and appreciation of science. At the same time, there are worries about the quality of data that community science projects produce. Can the work of non-professionals really deliver trustworthy results? Attempts to answer this question generally compare data collected by volunteers to data collected by professional scientists. When volunteer data is more variable or less accurate than professionally collected data, then the community science project is judged to be inferior to traditional science. I argue that this is not the right standard to use when evaluating community science, because it relies on a false assumption about the aims of science. I show that if we adopt the view that science has diverse aims which are often in tension with one another, then we cannot justify holding community science data to an expert accuracy standard. Instead, we should evaluate the quality of community science data based on its adequacy-for-purpose.

A multidisciplinary understanding of polarization

This article aims to describe the last 10 years of the collaborative scientific endeavors on polarization in particular and collective problem-solving in general by our multidisciplinary research team. We describe the team's disciplinary composition-social psychology, political science, social philosophy/epistemology, and complex systems science-highlighting the shared and unique skill sets of our group members and how each discipline contributes to studying polarization and collective problem-solving. With an eye to the literature on team dynamics, we describe team logistics and processes that we believe make our multidisciplinary team persistent and productive. We emphasize challenges and difficulties caused by disciplinary differences in terms of terminology, units/levels of analysis, methodology, and theoretical assumptions. We then explain how work disambiguating the concepts of polarization and developing an integrative theoretical and methodological framework with complex systems perspectives has helped us overcome these challenges. We summarize the major findings that our research has produced over the past decade, and describe our current research and future directions. Last, we discuss lessons we have learned, including difficulties in a "three models" project and how we addressed them, with suggestions for effective multidisciplinary team research. (PsycINFO Database Record (c) 2019 APA, all rights reserved).