Better but still biased: Analytic cognitive style and belief bias

Trippas, Dries; Pennycook, Gordon; Verde, Michael F.; Handley, Simon J.

doi:10.1080/13546783.2015.1016450

Cited by 44 publications

(46 citation statements)

References 33 publications

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“…Experimental evidence suggests that people who are less religious and more analytic tend to be better (on average) at contesting some of the general cognitive and coalitional biases we have been discussing [19,[20][21][22]. But are they any different from religious people when it comes to evaluating the scientific consensus on climate change and reacting to the challenges of the Anthropocene?…”

Section: Climate Change Cultural Cognition and "Religion"mentioning

confidence: 99%

How to Survive the Anthropocene: Adaptive Atheism and the Evolution of Homo deiparensis

Shults

2015

Religions

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Why is it so easy to ignore the ecological and economic crises of the Anthropocene? This article unveils some of the religious biases whose covert operation facilitates the repression or rejection of warnings about the consequences of extreme climate change and excessive capitalist consumption. The evolved defaults that are most relevant for our purposes here have to do with mental credulity toward religious content (beliefs about supernatural agents) and with social congruity in religious contexts (behaviors shaped by supernatural rituals). Learning how to contest these phylogenetically inherited and culturally fortified biases may be a necessary condition for adapting to and altering our current natural and social environments in ways that will enhance the chances for the survival (and flourishing) of Homo sapiens and other sentient species. I outline a conceptual framework, derived from empirical findings and theoretical developments in the bio-cultural sciences of religion, which can help clarify why and how gods are imaginatively conceived and nurtured by ritually engaged believers. Finally, I discuss the role that "adaptive atheism" might play in responding to the crises of the Anthropocene.

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Section: Climate Change Cultural Cognition and "Religion"mentioning

confidence: 99%

How to Survive the Anthropocene: Adaptive Atheism and the Evolution of Homo deiparensis

Shults

2015

Religions

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“…The results also suggest that despite the heterogeneity found among participants and stimuli, the believability of conclusions does not generally affect people's ability to discriminate between valid and invalid syllogisms when considered across the entire corpus, partially confirming (Dube et al, 2010) original account. However, a closer inspection using individual covariates suggest a relationship between people's reasoning abilities and the way they are affected by beliefs, as suggested by Trippas et al (2013Trippas et al ( , 2014Trippas et al ( , 2015. Altogether, these results suggest that syllogistic reasoning should be analyzed using hierarchical statistical methods together with additional individual covariates.…”

Section: Theoretical Accounts Of Belief Biasmentioning

confidence: 75%

“…In this scenario, the fact that one participant performs better than the other one is enough to distort the overall shape of the ROC. Once again, this possibility is far from unexpected in light of the fact that individual differences in reasoning ability are commonly found (Stanovich, 1999;Trippas et al, 2015).…”

Section: Aggregating Across Heterogeneous Participantsmentioning

confidence: 99%

“…Also, note that additional parameters could be easily added to the model, as is routinely done with predictor variables in multiple-regression models (we provide a demonstration of this in the general discussion). For example, Trippas et al (2013Trippas et al ( , 2015 considered the relationship between individual differences variables such as cognitive ability and analytic cognitive style with SDT estimates of discriminability and response bias. The use of other predictor variables such as fMRI data have also been entertained (e.g., Roser et al, 2015).…”

Section: Hierarchical Extension Of Signal-detection Modelmentioning

confidence: 99%

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Characterizing Belief Bias in Syllogistic Reasoning: A Hierarchical-Bayesian Meta-Analysis of ROC Data

Trippas¹,

Kellen²,

Singmann³

et al. 2017

Preprint

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The belief-bias effect is one of the most-studied biases in reasoning. A recent study of the phenomenon using the signal detection theory (SDT) model called into question all theoretical accounts of belief bias by demonstrating that beliefbased differences in the ability to discriminate between valid and invalid syllogisms may be an artifact stemming from the use of inappropriate linear measurement models such as analysis of variance (Dube et al., Psychological Review, 117 (3), 2010). The discrepancy between Dube et al. 's, Psychological Review, 117(3), 831-863 (2010) results and the previous three decades of work, together with former's methodological criticisms suggests the need to revisit earlier results, this time collecting confidence-rating responses. Using a hierarchical Bayesian meta-analysis, we reanalyzed a corpus of 22 confidence-rating studies (N = 993). The results indicated that extensive replications using confidence-rating data are unnecessary as the observed receiver operating characteristic functions are not systematically asymmetric. These results were subsequently corroborated by a novel experimental design based on SDT's generalized area theorem. Although the metaanalysis confirms that believability does not influence discriminability unconditionally, it also confirmed previous results that factors such as individual differences mediate the effect. The main point is that data from previous and future studies can be safely analyzed using appropriate hierarchical methods that do not require confidence ratings. More generally, our results set a new standard for analyzing data and evaluating theories in reasoning. Important methodological and theoretical considerations for future work on belief bias and related domains are discussed.

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“…Based on the aforementioned experimental research, scholars arrive at some predictions about an individual's ability to reason and learn (Stanovich, 2012;Trippas et al, 2015;Schneider and Newman, 2015). Assuming similar perception and motor skills, four different types of learners can be deduced from this literature.…”

Section: How We Learnmentioning

confidence: 99%

Insights from ‘policy learning’ on how to enhance the use of evidence by policymakers

Witting

2017

Palgrave Commun

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This article uses the policy-oriented learning literature to provide practical insights on how to enhance the use of evidence by policymakers. After a short introduction to the field, this article presents four steps to understanding and responding to policy learning. First, all people interpret the world through the lens of their beliefs, and learn by combining heuristics and analytical processing. Second, people learn in different ways according to their roles. A novice would not be advised to learn about a specialist isue in the same way as a scientist. Instead, a modified communication strategy would be used to ensure understanding and uptake of evidence. Third, learning is a political process: we interact with our social environment and some actors-including entrepreneurs and brokers-influence the process more than others. Therefore, to encourage learning from scientific evidence we need to move beyond communication towards entrepreneurship and brokerage roles. In other words, policy-oriented learning is as much about interaction and leadership as information.

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Better but still biased: Analytic cognitive style and belief bias

Cited by 44 publications

References 33 publications

How to Survive the Anthropocene: Adaptive Atheism and the Evolution of Homo deiparensis

How to Survive the Anthropocene: Adaptive Atheism and the Evolution of Homo deiparensis

Characterizing Belief Bias in Syllogistic Reasoning: A Hierarchical-Bayesian Meta-Analysis of ROC Data

Insights from ‘policy learning’ on how to enhance the use of evidence by policymakers

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