Research Article
Authors: Ryan Cragun, Kevin McCaffree, Ivan Puga-Gonzalez, Wesley Wildman, F. LeRon Shults
Abstract
Statistical models attempting to predict who will disaffiliate from religions have typically accounted for less than 15% of the variation in religious affiliations, suggesting that we have only a partial understanding of this vital social process. Using agent-based simulations in three “artificial societies” (one predominantly religious; one predominantly secular; and one in between), we demonstrate that worldview pluralism within one’s neighborhood and family social networks can be a significant predictor of religious (dis)affiliation but in pluralistic societies worldview diversity is less important and, instead, people move toward worldview neutrality. Our results suggest that there may be two phases in religious disaffiliation: (1) the early adopters initially disaffiliate regardless of social support, and subsequently (2) disaffiliation spreads as support for it within local social networks widens and it appears more acceptable. An important next step is for sociologists to confirm or correct the theoretical findings of this model using real-world social-network data, which will require overcoming the measurement difficulties involved in estimating each individual’s degree of local network pluralism.
Introduction
Statistical models have consistently found age, sex, educational attainment, income, race, political views, and geographic region (in the US) to be important correlates of religious non-affiliation and atheism (Glenn 1987; Hadaway 1980, 1989; Altemeyer and Hunsberger 1997; Strawn 2019). However, there are some problems with these variables as an explanation for why people leave religion. As Strawn (2019) illustrates, the ability of these variables to predict who will exit religion and who will stay has varied from study to study and from region to region (Norris and Inglehart 2004; Storm 2017, 2009; Voas 2003, 2007, 2014; Hayes 2000). Not every study has included the same variables despite these being common demographic considerations (Uecker, Regnerus, and Vaaler 2007) and some studies have focused more on people switching religions (Sherkat 2001, 2014; Hadaway and Roof 1979) than on people leaving religion altogether (Baker and Smith 2009, 2015; Cragun 2007). While useful correlates, most of these variables are either constant to the individual (e.g., race, sex, geographic region) or vary only slightly across the life course (e.g., income, political views). As a result, it is difficult to develop a causal model of how these variables lead people to disaffiliate from religions. Of greatest interest for this paper is that the amount of variation explained in who leaves religions using these variables has never been very high. This last problem is particularly important as it suggests that even when the nonreligious are a smaller percentage of the population and, thus, it should have been easier to predict who would be the earliest to leave, our ability to do so has been limited (Kanazawa 2010; Rogers 2006; Tamney, Powell & Johnson 1989).
Given the limited amount of variation explained in why people disaffiliate from religions, we wondered whether the reason why so many models so poorly predict religious exiting is because they are missing a variable that is particularly challenging to measure: religious pluralism. Religious pluralism is challenging to capture because it is an emergent property of social life at the macro-level as well as a property of individuals’ social networks. The concept of pluralism as it relates to religion and/or secular life stems from the early work of Peter Berger (1967, 1990) and suggests the following: as the proportion of individuals in one’s social network who hold different worldviews increases, the presumed plausibility of any single worldview decreases, which may lead to declining religiosity. Berger’s contention extended Durkheim’s ([1895] 2014) line of inquiry about the ways in which the division of labor (and general social fragmentation) in modernity partitioned the ‘collective conscience’ of society. In Berger’s—and for that matter Durkheim’s—conceptualization, it is more difficult for people to maintain an exclusive, strict religious worldview that marginalizes all other worldviews when they are surrounded by people who don’t think like they do (Phillips 1998).
While the concept of worldview pluralism is theoretically attractive and promising for increasing the predictive power of religious exiting models, operationalizing and measuring religious/secular pluralism has proven to be challenging (Hill & Olson 2009; Perl & Olson 2000; Voas, Olson & Crockett 2002). Recent research and advances in understanding social networks have begun to address this concern (Baker & Smith 2009; Scheitle & Smith 2011) and a recently published paper has shown that these methodological challenges can be overcome with a substantial amount of work (Olson et al. 2020). Most prior research has focused on the role of social networks in propping up religiosity (Hill 2014), reinforcing ties to congregations (Stroope 2012), helping people draw on religion for support (Merino 2014; Lim & Putnam 2010), or recruiting people into religions (Stark & Bainbridge 1980). We are aware of just two prior quantitative studies that examined the role of social networks in facilitating people’s exit from religion (Baker & Smith 2009; Gore et al. 2018; see Lee 2015 for a qualitative approach to this question).
Computer modeling and simulation is a relatively new approach to analyzing human behavior that can provide insights into the extent to which worldview pluralism is important for secularization. Agent-based simulation has a number of advantages over cross-sectional data analysis. Simulated societies can be generated with specific properties to test theories. Additionally, simulated societies that include social networks and social network interactions – data that are not always included in cross-sectional surveys – can reveal phenomena such as the worldview pluralism that exists within an agent’s social network, allowing for a clearer analysis of whether pluralism influences people’s decisions to leave religions. Additionally, similar to longitudinal studies, computer simulations can observe changes in worldviews that result from changing social networks. However, moving beyond the capacities of longitudinal studies, computer simulation experiments can also control a variety of factors in an artificial society in order to tease out the effects of specific variables. By setting the initial parametric conditions of the simulation using data drawn from sociology and psychology, researchers can test numerous social scientific theories against one another in a simulated artificial society, including the hypothesis in secularization theory that network pluralism increases secularization. Computer simulations, in effect, offer social scientists the opportunity to ‘experiment’ in ways that would otherwise be unethical or impractical, thereby providing them with the potential to answer questions that have so far been out of reach for social scientific research.
In this paper, we briefly review the literature on the variables that predict religious exiting – people who leave religion altogether (Cragun & Hammer 2011; Enstedt, Larsson & Mantsinen 2019) – and the literature on religious pluralism. We then illustrate how computer simulations have the potential to answer some questions that have eluded more traditional statistical analytic techniques. Such answers based on simulation experiments should inspire sociologists to confirm or correct the theoretical findings of this model using real-world social-network data, despite the measurement difficulties involved in estimating each individual’s degree of network pluralism.