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Why Algorithms Can’t Predict Your Love Life with Dr. Paul Eastwick
Modern dating can feel like a marketplace. We’re told we all have a “mate value,” that some people are 9s and 10s, and that the laws of evolution determine who gets chosen — and who gets rejected. But what if we’ve misunderstood what evolutionary science actually says about love?
Dr. Laurie sits down with social psychologist Dr. Paul Eastwick, author of Bonded by Evolution: The New Science of Love and Connection, to challenge some of the most pervasive myths about attraction and compatibility. Do dating app algorithms actually know who's right for you? Are we really all placed in different "leagues"? If you’ve ever wondered whether love is destiny, biology, or something you can actually create, Dr. Eastwick offers a surprising new perspective.
Resources mentioned in this episode:
Bonded by Evolution: The New Science of Love and Connection
“The Pairing Game: A Classroom Demonstration of the Matching Phenomenon”
“Matching for Attractiveness in Romantic Partners and Same-Sex Friends: A Meta-Analysis and Theoretical Critique”
“The Social Relations Model”
“Once More: Is Beauty in the Eye of the Beholder? Relative contributions of private and shared taste to judgments of facial attractiveness”
“Sex Differences in Mate Preferences Revisited: Do People Know What They Initially Desire in a Romantic Partner?”
“Northwestern Speed-dating Study I”
“Northwestern Speed-dating Study II”
“The (Mental) Ties That Bind: Cognitive Structures That Predict Relationship Resilience”
“We’re Not That Choosy: Emerging Evidence of a Progression Bias in Romantic Relationships”
“Romantic Relationship Status Biases Memory of Faces of Attractive Opposite-Sex Others: Evidence from a Reverse-Correlation Paradigm”
“Relationship Regulation in the Face of Eye Candy: a Motivated Cognition Framework for Understanding Responses to Attractive Alternatives”
“Perceived, not actual, similarity predicts initial attraction in a live romantic context: Evidence from the speed-dating paradigm”
“Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction”
“Love Factually”
See omnystudio.com/listener for privacy information.
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By Pushkin Industries
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Modern dating can feel like a marketplace. We’re told we all have a “mate value,” that some people are 9s and 10s, and that the laws of evolution determine who gets chosen — and who gets rejected. But what if we’ve misunderstood what evolutionary science actually says about love?
Dr. Laurie sits down with social psychologist Dr. Paul Eastwick, author of Bonded by Evolution: The New Science of Love and Connection, to challenge some of the most pervasive myths about attraction and compatibility. Do dating app algorithms actually know who's right for you? Are we really all placed in different "leagues"? If you’ve ever wondered whether love is destiny, biology, or something you can actually create, Dr. Eastwick offers a surprising new perspective.
Resources mentioned in this episode:
Bonded by Evolution: The New Science of Love and Connection
“The Pairing Game: A Classroom Demonstration of the Matching Phenomenon”
“Matching for Attractiveness in Romantic Partners and Same-Sex Friends: A Meta-Analysis and Theoretical Critique”
“The Social Relations Model”
“Once More: Is Beauty in the Eye of the Beholder? Relative contributions of private and shared taste to judgments of facial attractiveness”
“Sex Differences in Mate Preferences Revisited: Do People Know What They Initially Desire in a Romantic Partner?”
“Northwestern Speed-dating Study I”
“Northwestern Speed-dating Study II”
“The (Mental) Ties That Bind: Cognitive Structures That Predict Relationship Resilience”
“We’re Not That Choosy: Emerging Evidence of a Progression Bias in Romantic Relationships”
“Romantic Relationship Status Biases Memory of Faces of Attractive Opposite-Sex Others: Evidence from a Reverse-Correlation Paradigm”
“Relationship Regulation in the Face of Eye Candy: a Motivated Cognition Framework for Understanding Responses to Attractive Alternatives”
“Perceived, not actual, similarity predicts initial attraction in a live romantic context: Evidence from the speed-dating paradigm”
“Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction”
“Love Factually”
See omnystudio.com/listener for privacy information.
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