Scientific Studies of People's Relationship to Music
Data Skeptic12 Helmi 2016

Scientific Studies of People's Relationship to Music

Samuel Mehr joins us this week to share his perspective on why people are musical, where music comes from, and why it works the way it does. We discuss a number of empirical studies related to music and musical cognition, and dispense a few myths about music along the way.

Some of Sam's work discussed in this episode include Music in the Home: New Evidence for an Intergenerational Link,Two randomized trials provide no consistent evidence for nonmusical cognitive benefits of brief preschool music enrichment, and Miscommunication of science: music cognition research in the popular press. Additional topics we discussed are also covered in a Harvard Gazette article featuring Sam titled Muting the Mozart effect.

You can follow Sam on twitter via @samuelmehr.

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(601)

Student Spotlight: Aaron Payne, Data Analyst

Student Spotlight: Aaron Payne, Data Analyst

Aaron Payne, an MBA student at Georgia Tech studying business analytics and a Senior Insights Analyst at Chick-fil-A, joins Kyle Polich to talk about turning analytics into decisions that matter. They...

1 Touko 25min

The Future is Agentic in Recommender Systems

The Future is Agentic in Recommender Systems

Kyle Polich sits down with Yashar Deldjoo, research scientist and Associate Professor at the Polytechnic University of Bari, to explore how recommender systems have evolved and why trustworthiness mat...

25 Huhti 49min

Book Ratings and Recommendations

Book Ratings and Recommendations

Goodreads star ratings can be misleading as measures of "book quality," and research from Hannes Rosenbusch suggests that for many professionally published books, differences between readers often mat...

27 Maalis 39min

Disentanglement and Interpretability in Recommender Systems

Disentanglement and Interpretability in Recommender Systems

Ervin Dervishaj, a PhD student at the University of Copenhagen, discusses his research on disentangled representation learning in recommender systems, finding that while disentanglement strongly corre...

10 Maalis 30min

Collective Altruism in Recommender Systems

Collective Altruism in Recommender Systems

Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game recommendation algorithms. Kat's research r...

27 Helmi 54min

Niche vs Mainstream

Niche vs Mainstream

Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and niche algorithms. His research shows spec...

18 Helmi 34min

Healthy Friction in Job Recommender Systems

Healthy Friction in Job Recommender Systems

In this episode, host Kyle Polich speaks with Roan Schellingerhout, a fourth-year PhD student at Maastricht University, about explainable multi-stakeholder recommender systems for job recruitment. Roa...

2 Helmi 26min

Fairness in PCA-Based Recommenders

Fairness in PCA-Based Recommenders

In this episode, we explore the fascinating world of recommender systems and algorithmic fairness with David Liu, Assistant Research Professor at Cornell University's Center for Data Science for Enter...

26 Tammi 49min

Suosittua kategoriassa Tiede

rss-mita-tulisi-tietaa
rss-poliisin-mieli
tiedekulma-podcast
rss-duodecim-lehti
menologeja-tutkimusmatka-vaihdevuosiin
docemilia
rss-astetta-parempi-elama-podcast
rss-tiedetta-vai-tarinaa
rss-lapsuuden-rakentajat-podcast
utelias-mieli
sotataidon-ytimessa
radio-antro
filocast-filosofian-perusteet
rss-ranskaa-raakana
rss-kasvatuspsykologiaa-kaikille
rss-sosiopodi