One crucible for theories of religion is their ability to predict and explain patterns of belief and disbelief. Yet, religious nonbelief is often heavily stigmatized, potentially leading many atheists to refrain from outing themselves even in anonymous polls. We used the unmatched count technique and Bayesian estimation to indirectly estimate atheist prevalence in two nationally representative samples of 2000 U.S. adults apiece.Widely-cited telephone polls (e.g., Gallup, Pew) suggest USA atheist prevalence of only 3-11%. In contrast, our most credible indirect estimate is 26% (albeit with considerable estimate and method uncertainty). Our data and model predict that atheist prevalence exceeds 11% with greater than .99 probability, and exceeds 20% with roughly .8 probability. Prevalence estimates of 11% were even less credible than estimates of 40%, and all intermediate estimates were more credible. Some popular theoretical approaches to religious cognition may require heavy revision to accommodate actual levels of religious disbelief.Keywords: religion; atheism; social desirability; stigma; Bayesian estimation How many atheists are there? 3 How many atheists are there?I am, and I wish I weren't. Aldous Huxley, Brave New WorldReligion is a core aspect of human nature, yet a comprehensive understanding of religion must also accommodate religious disbelief. Various models seek to explain commonalities in religious cognition (e.g., Boyer, 2008) and the possible adaptive benefits of religious beliefs and practices (e.g., Norenzayan et al., 2014). These models have advanced the naturalistic science of religion, one key challenge in interdisciplinary, consilient approaches to human nature (Wilson, 1999). The scientific success of theories of religion partially hinges on the degree to which they successfully predict and explain the distribution of belief and disbelief. The study of atheists-merely people who disbelieve or lack belief in the existence of God or gods 1 -is thus a central testing ground for basic theory on the origins of religious and supernatural beliefs (Norenzayan & Gervais, 2013). Unfortunately, unbiased answers to some of the most elementary questions regarding belief and disbelief are currently unavailable. Such basic questions as: How many atheists are there?1 As a terminological aside, throughout this paper we use the term "atheist" to refer to people who disbelieve or lack belief in the existence of a god or gods. This definition is standard in the psychology, sociology, and philosophy of religion. Furthermore, it is the definition of "atheist" adopted by the Oxford English Dictionary. Operationally, we thus define people as atheists if they do not indicate belief in a god or gods. We focused on binary classification of atheists not because we necessarily view religious belief as a psychologically binary phenomenon, but rather for direct comparability with existing polling data utilizing binary measurements of this complex construct.How many atheists are there? 4Existing global atheism est...
If psychologists have recognized the pitfalls of underpowered research for decades, why does it persist? Incentives, perhaps: underpowered research benefits researchers individually (increased productivity), but harms science collectively (inflated Type I error rates and effect size estimates but low replication rates). Yet, researchers can selectively reward power at various scientific bottlenecks (e.g., peer review, hiring, funding, and promotion). We designed a stylized thought experiment to evaluate the degree to which researchers consider power and productivity in hiring decisions. Accomplished psychologists chose between a low sample size candidate and a high sample size candidate who were otherwise identical. We manipulated the degree to which participants received information about (1) productivity, (2) sample size, and (3) directly calculable Type I error and replication rates. Participants were intolerant of the negative consequences of low-power research, yet merely indifferent regarding the practices that logically produce those consequences, unless those consequences were made quite explicit.
Productive research programs have emerged, targeting the cultural, cognitive, and evolutionary origins of both religious belief and—more recently—religious disbelief. The current study examines the role of specific theoretically supported cultural learning strategies in the development of belief and disbelief in gods. Using a sample from the World Values Survey, we investigate the role that kin-biased transmission, conformist transmission, and credibility enhancing displays have on individuals’ beliefs in gods in 53 countries or regions worldwide. We test this relationship using a combination of signal detection analysis and multilevel modeling. The two separate analyses yield converging results, providing support for the necessary role of culture in the development of religious beliefs. This evidence supports models that place cultural learning (specifically context-biased transmission) central to the evolution of religious belief and disbelief, and suggest that revisions are necessary to popular cognitive byproduct frameworks that predict only a minimal role for culture.
Synthetic speech, which is generated by a computer, is widely used in both everyday situations (e.g. GPS devices; weather alerts) and the military (e.g. aviation). Synthetic speech is not identical to spoken speech, as it has a different pacing and varying pronunciations. Participants engaged in a Dichotic Listening Task in which they actively repeated information that was being presented in one ear, while ignoring their other (unattended) ear. The task was adapted and used both synthetic and spoken speech in the attended and unattended ears. It was found that when the unattended information was Spoken participants were more likely to hear an alert word ("fire") and familiar character names when engaging in a difficult task. When unattended information was in the form of Synthetic Speech less of these low-threshold words were reported by the participants. This research has important implications for the development and use of synthetic speech in high workload situations, and in alerts.
Widespread religious disbelief represents a key testing ground for theories of religion. We evaluated the predictions of three prominent theoretical approaches—secularization, cognitive byproduct, and dual inheritance—in a nationally representative (United States, N = 1,417) data set with preregistered analyses and found considerable support for the dual inheritance perspective. Of key predictors of religious disbelief, witnessing fewer credible cultural cues of religious commitment was the most potent, β = .28, followed distantly by reflective cognitive style, β = .13, and less advanced mentalizing, β = .05. Low cultural exposure predicted about 90% higher odds of atheism than did peak cognitive reflection, and cognitive reflection only predicted disbelief among those relatively low in cultural exposure to religion. This highlights the utility of considering both evolved intuitions and transmitted culture and emphasizes the dual roles of content- and context-biased social learning in the cultural transmission of disbelief (preprint https://psyarxiv.com/e29rt/ ).
Tolerance for diversity in America is often indexed by direct measures, such as self-reported "willingness to vote" polls. However, pressures to be or appear unprejudiced may bias such estimates, yielding misleading and overly optimistic inferences about tolerance in America. The current research investigated the degree to which direct and indirect measures of political candidate preferences converge and diverge across six target groups varying in acceptability of stigmatization (atheists, African Americans, Catholics, gay men and lesbians, Muslims, and women) and across relevant participant demographics. Overall, participants (N = 3000, nationally representative) reported less willingness to vote for target groups when measured indirectly, relative to directly. Additionally, the divergence between direct and indirect measures was especially evident for social groups for which overt stigmatization is normatively inappropriate. This research provides a vital benchmark that quantifies the gulf between direct and indirect measures of tolerance for various oft-stigmatized groups in America.
One crucible for theories of religion is their ability to predict and explain patterns of belief and disbelief. Yet, religious nonbelief is often heavily stigmatized, potentially leading many atheists to refrain from outing themselves even in anonymous polls. We used the unmatched count technique and Bayesian estimation to indirectly estimate atheist prevalence in two nationally representative samples of 2000 U.S. adults apiece.Widely-cited telephone polls (e.g., Gallup, Pew) suggest USA atheist prevalence of only 3-11%. In contrast, our most credible indirect estimate is 26% (albeit with considerable estimate and method uncertainty). Our data and model predict that atheist prevalence exceeds 11% with greater than .99 probability, and exceeds 20% with roughly .8 probability. Prevalence estimates of 11% were even less credible than estimates of 40%, and all intermediate estimates were more credible. Some popular theoretical approaches to religious cognition may require heavy revision to accommodate actual levels of religious disbelief.Keywords: religion; atheism; social desirability; stigma; Bayesian estimation How many atheists are there? 3 How many atheists are there?I am, and I wish I weren't. Aldous Huxley, Brave New WorldReligion is a core aspect of human nature, yet a comprehensive understanding of religion must also accommodate religious disbelief. Various models seek to explain commonalities in religious cognition (e.g., Boyer, 2008) and the possible adaptive benefits of religious beliefs and practices (e.g., Norenzayan et al., 2014). These models have advanced the naturalistic science of religion, one key challenge in interdisciplinary, consilient approaches to human nature (Wilson, 1999). The scientific success of theories of religion partially hinges on the degree to which they successfully predict and explain the distribution of belief and disbelief. The study of atheists-merely people who disbelieve or lack belief in the existence of God or gods 1 -is thus a central testing ground for basic theory on the origins of religious and supernatural beliefs (Norenzayan & Gervais, 2013). Unfortunately, unbiased answers to some of the most elementary questions regarding belief and disbelief are currently unavailable. Such basic questions as: How many atheists are there?1 As a terminological aside, throughout this paper we use the term "atheist" to refer to people who disbelieve or lack belief in the existence of a god or gods. This definition is standard in the psychology, sociology, and philosophy of religion. Furthermore, it is the definition of "atheist" adopted by the Oxford English Dictionary. Operationally, we thus define people as atheists if they do not indicate belief in a god or gods. We focused on binary classification of atheists not because we necessarily view religious belief as a psychologically binary phenomenon, but rather for direct comparability with existing polling data utilizing binary measurements of this complex construct.How many atheists are there? 4Existing global atheism est...
Widespread religious disbelief represents a key testing ground for theories of religion. We evaluated the predictions of three prominent theoretical approaches in a nationally representative (USA, N= 1417) dataset with preregistered analyses, and found considerable support for a dual inheritance (gene-culture coevolution) perspective. We found that witnessing fewer credible cultural cues of religious commitment is the most potent predictor of religious disbelief, β=0.28, followed distantly by reflective cognitive style, β= 0.13, and less advanced mentalizing, β= 0.05. Low cultural exposure to faith predicted about 90% higher odds of atheism than did peak cognitive reflection. Further, cognitive reflection predicted reduced religious belief only among individuals who witness relatively fewer credible contextual cues of faith in others. This work empirically unites four distinct literatures addressing the origins of religious disbelief, highlights the utility of considering both evolved intuitions and cultural evolutionary processes in religious transmission, emphasizes the dual roles of content- and context-biased social learning, and sheds light on the shared psychological mechanisms that underpin both religious belief and disbelief.
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