Realistically, you can't build any model of behavior-environment relations if you can't (a) find the data you need and (b) integrate those data into a usable database.

In this episode of The Behavioral Data Science Podcast, we discuss the many considerations and decisions one needs to make. And, we do so by discussing a seven-year-long project Jake has been working on to build a usable database of all open-source articles published within five behavior-analytic journals.

Crucial to any behavioral data science project is identifying either (a) what behavior you want to analyze and how you'll get the data; or (b) what data you can get and what behaviors those data allow you to analyze well.

In this episode, we chat about these decisions in the context of the literally wild behavior of birds at backyard feeders.

For the interested, here's a link to the backyard ecology dashboard referenced during the episode: https://david-j-cox.github.io/backyard-ecology/

In each episode of Season 3, we take a claim from a news story, paper, or hot topic, and walk through how a behavioral data scientist would think about it: clarify the question, identify the operant and respondent principles potentially at play, design the data pipelines, choose the models, and turn the resulting insights into data-based behavior-change tools.

In this episode, we take on the claim that "late-night screen time disrupts sleep and leads teens to be more depressed".