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]]>Authors: Ryan Cragun, Kevin McCaffree, Ivan Puga-Gonzalez, Wesley Wildman, F. LeRon Shults
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.
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.
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]]>Post-Supernatural Cultures: There and Back Again Read More »
The post Post-Supernatural Cultures: There and Back Again appeared first on Modeling Religious Change.
]]>The abandonment of supernatural religious beliefs and rituals seems to occur quite easily in some contexts, but post-supernaturalist cultures require a specific set of conditions that are difficult to produce and sustain on a large scale and thus are historically rare. Despite the worldwide resurgence of supernaturalist religion, some subcultures reliably produce people who deny the existence of supernatural entities. This social phenomenon has evoked competing explanations, many of which enjoy empirical support. We synthesize six of the most influential social-science explanations, demonstrating that they provide complementary perspectives on a complex causal architecture. We incorporate this theoretical synthesis into a computer simulation, identifying conditions under which the predominant attitude toward supernaturalism in a population shifts from acceptance to rejection (and vice versa). The model suggests that the conditions for producing widespread rejection of supernatural worldviews are highly specific and difficult to produce and sustain. When those conditions combine, which is historically rare, a stable social equilibrium emerges within which post-supernaturalist worldviews are widespread; however, this equilibrium is easier to disrupt than equilibria whose cohesion is stabilized by supernatural religion due to persistent cognitive tendencies toward supernaturalism in evolved human minds.
In Scandinavian and Northern European nations today, as well as most coastal regions of the United States and many parts of Australia and New Zealand, a growing number of individuals do not believe in supernatural entities and reject religion in general. However, surveys show that supernatural beliefs are on the rise worldwide, an increase driven by resurgent religion in Africa, Asia, and most of the Americas (Berger 1999, Johnson 2010, Pew Research Center 2015). Why is widespread rejection of supernatural worldviews so rare, historically speaking? And what is so unusual about the social contexts within which post-supernaturalism becomes widespread?
Several social theories have attempted to describe pathways through which a culture can shift away from supernatural religiosity and toward post-supernaturalist secularity, many of which enjoy significant empirical support. After an exhaustive literature review, we identified the following six as being (1) the most influential, (2) the most relevant to interpreting the emergence and stabilization of post-supernatural cultures, and (3) the most empirically well supported.
Although some champions of these theories view them as inherently competitive or even mutually exclusive, we argue that these mainstream theories offer partial perspectives on a more complex architecture of causal factors driving changes in the religiosity and secularity of human populations. We are not alone. Ruiter and van Tubergen, for example, have attempted to show how (what we are calling) the existential security and supply-side paths can be “taken together” to “provide insights into differences in initial conditions, path dependency, and the reason why religious trends are sometimes reversed” (2009, p. 889). Probably the most ambitious attempt so far to produce a unified theoretical model is Stolz (2009), where correlations between aspects of some of the theories above (and some others) are explored using multi-level multiple regression modeling, though Stolz doesn’t take account of post-supernaturalism as a dependent variable. Such integrative attempts are rare, and none developed to date illustrates concretely how the causal elements of all these theories can function together. It is important to note that we selected these six theories before trying to integrate them, and let the chips fall where they may as to whether integration would be possible and whether the meaning of the resulting synthesis would tell us anything interesting about transitions between supernatural religion and post-supernaturalist secularity.
We synthesize the core elements of these theories into a consistent conceptual architecture and implement the resulting model in a system-dynamics computer simulation. This allows us, first, to demonstrate the coherence of the synthesis, as implementation in a computational simulation imposes demanding requirements of conceptual clarity and consistency. The simulation also allows us to identify plausible conditions under which a population with a majority of individuals embracing supernatural beliefs (we will use supernatural religious to refer to this posture, which explicitly excludes naturalist forms of religion; again, the focus here is on supernaturalism, not religion) changes to a population in which most individuals have learned to contest inbuilt cognitive tendencies toward supernaturalism, thereby becoming “post-supernaturalists” (we will call this posture post-supernatural secular, referring both to personal views and to a corresponding form of socio-political organization where beliefs in and practices related to supernatural agents play no role; the unwieldy name is warranted to avoid confusion). The same simulation also indicates plausible conditions under which a society moves in the opposite direction (i.e. from post-supernaturalist secular to supernaturalist religious). Moreover, our computational model provides insight into the means by which supernatural religious coalitions and secular post-supernaturalist coalitions might inhibit or catalyze social transformation in either direction.
Computational modeling and simulation is a relatively new tool in social science, where it was introduced after it proved its worth in other fields, especially engineering (see a 2005 themed issue (110/4) of American Journal of Sociology, Iannaccone and Makowsky 2007, Squazzoni 2012). Simulation is a fruitful substitute for experimentation when (as with many social issues) experiments are impossible or unethical, the periods concerned are too long, or datasets spanning many decades are not available. Conceptually, computer simulation is not so different from demographic projection: both model a set of hypothetical scenarios by working out the implications of specific assumptions.
We refer to the computer simulation presented here as FOReST (an acronym for the “future of religious and secular transitions”). FOReST indicates that the conditions for producing widespread rejection of supernaturalist religion are highly specific, hard to produce, and difficult to sustain because they are individually necessary. When those necessary conditions combine, which is historically rare, there emerges a stable social equilibrium within which most people can contest maturationally natural cognitive tendencies to embrace supernatural thinking and behaving. Because it requires steady inputs of substantial energy to contest maturationally natural cognition and behavior, this post-supernatural social equilibrium may be easier to destabilize than more common social equilibria that take advantage of maturationally natural cognitive tendencies toward supernatural beliefs and practices.
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