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Two Psychologists Four Beers - Episode 105: Patchwork Politics

Episode 105: Patchwork Politics

Explicit content warning

05/17/23 • 58 min

Two Psychologists Four Beers

In heated political debates, people are often accused of being hypocrites, lacking consistent foundational values. Today, Yoel and Alexa discuss a recent paper by David Pinsof, David Sears, and Martie Haselton, that challenges the commonsense notion that political belief systems stem from our core values. Instead, the authors propose that people form alliances with others, and develop political beliefs that serve to maintain those alliances. The cohosts discuss how these alliances might form, the various biases used to defend them, and whether values are truly absent from the process. They also tackle the deeper question of whether the alliance model means that neither side is right or wrong.

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In heated political debates, people are often accused of being hypocrites, lacking consistent foundational values. Today, Yoel and Alexa discuss a recent paper by David Pinsof, David Sears, and Martie Haselton, that challenges the commonsense notion that political belief systems stem from our core values. Instead, the authors propose that people form alliances with others, and develop political beliefs that serve to maintain those alliances. The cohosts discuss how these alliances might form, the various biases used to defend them, and whether values are truly absent from the process. They also tackle the deeper question of whether the alliance model means that neither side is right or wrong.

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Previous Episode

undefined - Episode 104: Quantifying the Narrative of Replicable Science

Episode 104: Quantifying the Narrative of Replicable Science

Yoel and Alexa discuss a recent paper that takes a machine learning approach to estimating the replicability of psychology as a discipline. The researchers' investigation begins with a training process, in which an artificial intelligence model identifies ways that textual descriptions differ for studies that pass versus fail manual replication tests. This model is then applied to a set of 14,126 papers published in six well-known psychology journals over the past 20 years, picking up on the textual markers that it now recognizes as signals of replicable findings. In a mysterious twist, these markers remain hidden in the black box of the algorithm. However, the researchers hand-examine a few markers of their own, testing whether things like subfield, author expertise, and media interest are associated with the replicability of findings. And, as if machine learning models weren't juicy enough, Yoel trolls Alexa with an intro topic hand-selected to infuriate her.

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Next Episode

undefined - Episode 106: We Need to Talk About Fraud Again

Episode 106: We Need to Talk About Fraud Again

Harkening back to episode 73, Alexa and Yoel discuss recent evidence of fraud documented in the Data Colada blog post "Clusterfake." The post is the first in a series of four, which will collectively detail evidence of fraud in four papers co-authored by Harvard Business School Professor Francesca Gino. First, the co-hosts dive into the details, with Alexa soberly (in both senses of the word) explaining the revelations of calcChain. They go on to discuss the potential impact of these findings for collaborators, some of whom have begun conducting audits of work co-authored with Gino. In addition, they speculate about ways to reduce fraud that could relieve some of the burden from those who currently do this time-consuming and often thankless work. Finally, they consider what this means for a field still struggling to build a more trustworthy foundation.

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