Are religious beliefs psychologically different from matter-of-fact beliefs? Many scholars say no: that religious people, in a matter-of-fact way, simply think their deities exist. Others say yes: that religious beliefs are more compartmentalized, less certain, and less responsive to evidence. Little research to date has explored whether lay people themselves recognize such a difference. We addressed this question in a series of sentence completion tasks, conducted in five settings that differed both in religious traditions and in language: the US, Ghana, (...) Thailand, China, and Vanuatu. Participants everywhere routinely used different verbs to describe religious versus matter-of-fact beliefs, and they did so even when the ascribed belief contents were held constant and only the surrounding context varied. These findings support the view that people from diverse cultures and language communities recognize a difference in attitude type between religious belief and everyday matter-of-fact belief. (shrink)

Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate what (...) it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)

How and why does the moon cause the tides? How and why does God answer prayers? For many, the answer to the former question is unknown; the answer to the latter question is a mystery. Across three studies testing a largely Christian sample within the United States (N= 2524), we investigate attitudes toward ignorance and inquiry as a window onto scientific versus religious belief. In Experiment 1, we find that science and religion are associated with different forms of ignorance: scientific (...) ignorance is typically expressed as a personal unknown (“it's unknown to me”), whereas religious ignorance is expressed as a universal mystery (“it's a mystery”), with scientific unknowns additionally regarded as more viable and valuable targets for inquiry. In Experiment 2, we show that these forms of ignorance are differentially associated with epistemic goals and norms: expressing ignorance in the form of “unknown” (vs. “mystery”) more strongly signals epistemic values and achievements. Experiments 2 and 3 additionally show that ignorance is perceived to be a greater threat to science and scientific belief than to religion and religious belief. Together, these studies shed light on the psychological roles of scientific and religious belief in human cognition. (shrink)

A growing body of research suggests that scientific and religious beliefs are often held and justified in different ways. In three studies with 707 participants, we examine the distinctive profiles of beliefs in these domains. In Study 1, we find that participants report evidence and explanatory considerations (making sense of things) as dominant reasons for beliefs across domains. However, cuing the religious domain elevates endorsement of nonscientific justifications for belief, such as ethical considerations (e.g., believing it encourages people to be (...) good), affiliation (what loved ones believe), and intuition (what feels true in one's heart). Study 2 replicates these differences with specific scientific and religious beliefs held with equal confidence, and documents further domain differences in beliefs’ personal importance, openness to revision, and perceived objectivity. Study 3 replicates these differences, further finding that counter‐consensus beliefs about contentious science topics (such as climate change and vaccination) often have properties resembling religious beliefs, while counter‐religious beliefs about religion (e.g., “There is no God”) have properties that more closely resemble beliefs about science. We suggest that beliefs are held and justified within coherent epistemic frameworks, with individuals using different frameworks in different contexts and domains. (shrink)

The aim of this study was to evaluate the structure and measurement invariance of the religious identity, religious practice, and religious beliefs across cultures in six world regions (Asia, non-Western Europe, North America, Oceania, South America, and Western Europe) and across Western, Educated, Industrialized, Rich, and Democratic regions (WEIRD) and non-WEIRD world regions. Confirmatory factory analysis examined whether the hypothesized measurement model fits the data; several multi-group confirmatory factor analyses were performed to examine measurement invariance through a progressive analytic strategy (...) involving three invariance conditions of configural, metric, and scalar invariance. The results generally supported the adequate fit to the data of the three correlated factors model (religious identity-RII, religious practice-RPI, and religious beliefs—RBI); it was found to be full metric invariance for WEIRD regions (RII), North America (RII and RBI), Western Europe (RII) and Non-Western Europe (RII), and South America (RII and RBI). Finally, for RII, it was found to be full configural invariance in almost all regions, except North America and Oceania; for RPI, it was found to be full configural only in North America and Non-WEIRD regions; and for RBI, it was found to be full configural only in North America, Asia, and South America, being that women scored significantly higher than men in all three indices all over the world; finally, it was found to be configural, but not metric or scalar invariance across WEIRD and non-WEIRD world regions. (shrink)