The new science of religious change.

Abstract

Humans have believed in gods and spirits since the earliest days of the Holocene, and many people still believe in them today. Although the existence of religious belief has been a human constant, the nature and prevalence of religion has changed dramatically throughout human history. Here we describe the emerging science of religious change. We first outline a multilevel framework for studying religious change drawn from theories of socioecological psychology and cultural evolution. We illustrate this framework with four case studies featuring two ancient religious changes (the rise of punitive religions and doctrinal rituals) and two modern religious changes (the rise of atheism and nontraditional religions). We then review useful methods for examining religious change, including ethnographic coding, agent-based modeling, and time-series analysis. Next, we explore future directions, highlighting the need for predictive forecasts, nonlinear models, and non-Western samples. We also outline ten key questions that need to be answered for a fuller understanding of religious change.

Responses of Religion and Science to the Threats of the COVID-19 Pandemic in Indonesia

“…Agama dan sains tidak berseberangan dalam merespon situasi yang terjadi selama pandemi COVID-19 di Indonesia, dan keduanya memiliki porsi masing-masing dalam memberikan penjelasan atas permasalahan yang terjadi. Jackson et al (2021) menemukan bahwa agama tidak selamanya menghambat individu dalam menerima sains yang ada. Namun, sejumlah individu yang non-religius kerap memiliki prasangka tersebut.…”

“…Religion and science are not completely in opposite corners in responding to the situation which is occuring during the COVID-19 pandemic in Indonesia, and each of them has its own place in explaining the problems which have occurred. Jackson et al (2021) found that religion does not always hinder people in accepting the existing science. Nonetheless, a number of non-religious people often have that preconception.…”

The psychology of cultural change: Introduction to the special issue.

“…Finally, this special issue aims to make methods in cultural dynamics research feel more approachable to those who may be less familiar with them. This issue contains accessible overviews of agent-based modeling (Schaller & Muthukrishna, 2021) and broad discussions of common time series methods (Jackson et al, 2021; Rotella et al, 2021; also see https://osf.io/njydv/ for annotated R code for many common time series analyses). Further, several articles identify additional overviews and tutorials for those interested in becoming more familiar with these and other methods highlighted in this issue that are not typically part of the psychologist’s statistical toolkit.…”

“…Some of the articles in this special issue focus on the "What" of cultural change-documenting shifts in specific phenomena such as prejudice (Charlesworth & Banaji, 2021), mental health (Infurna et al, 2021), individualism (Hamamura et al, 2021), social mobility (Chan et al, 2021), and religious beliefs and practices (Jackson et al, 2021). Other articles focus on the "Why"-testing theories regarding the causes of specific cultural changes, such as shifts over time in levels of individualism (Kusano & Kemmelmeier, 2021), or openness (Götz et al, 2021), or fertility (Rotella et al, 2021).…”

“…The present issue draws together new work on cultural change from scholars from a variety of areas within psychology (including social, personality, cultural, developmental, and quantitative psychology), and beyond (e.g., sociology and data science). These pieces capture a range of theoretical perspectives that have been brought to bear on how and why cultures change over time, including insights from evolutionary psychology (Jackson et al, 2021; Kusano & Kemmelmeier, 2021; Pan et al, 2021), behavioral ecology (Rotella et al, 2021), cultural evolution (Schaller & Muthukrishna, 2021), and socioecological psychology (Buttrick & Oishi, 2021). The special issue also highlights the diversity of methodological approaches in this emerging field ranging from computational modeling (Jung et al, 2021; Schaller & Muthukrishna, 2021; Pan et al, 2021), to machine learning (Sheetal & Savani, 2021; Stavrova et al, 2021), to time series analyses (Charlesworth & Banaji, 2021; Chan et al, 2021; Götz et al, 2021; Kusano & Kemmelmeier, 2021; Rotella et al, 2021).…”