Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville, Part 1 From the company’s creation, Netflix has relied on the scalability and accuracy of machine learning to deliver content and turn profits. One way Netflix uses machine learning is to recommend movies to its users. A model that provides accurate and tailored recommendations at [...]

Representativeness Analysis: How Our Data Reflects the Real Labor Market Dynamics This month, we will discuss the representativeness of Data@Work Research Hub data. The Data@Work Research Hub is a collection of public datasets produced by the Open Skills Project from a growing pool of public and private administrative data sources, such as job postings, resumes, [...]

Introducing the Training Provider Outcomes Toolkit Trying to find a good job training program can be daunting. How do you know if the skills they teach are valuable in the job market? And how can you be sure they’re doing a good job of teaching those skills? Especially, when the costs can be high. It [...]

Introducing the Data@Work Research Hub and Funding Opportunity With the rapid growth and adoption of technologies like artificial intelligence having uncertain and disparate effects on labor markets, the need for high-quality interdisciplinary research into labor market dynamics and workforce development has never been so urgent. While new data sources capturing detailed interactions between job seekers, [...]

Data-Driven Inspections for Safer Housing in San Jose, California The Multiple Housing team in San Jose’s Code Enforcement Office is tasked with protecting the occupants of properties with three or more units, such as apartment buildings, fraternities, sororities, and hotels. They do so by conducting routine inspections of these properties, looking for everything from blight [...]

Combining Data and Behavioral Science to Reduce Water Shut Offs Behavioral science and psychology can help explain the underlying reasons for seemingly irrational behavior which cities aim to address, such as using payday loans or committing property crimes. Unfortunately, determining the underlying causes of human behavior is difficult for a single individual, let alone an [...]

Introducing pgdedupe! Combining datasets and performing large aggregate analyses are powerful new ways to improve service across large populations. Critically important in this task is the deduplication of identities across multiple data sets that were rarely designed to work together. Inconsistent data entry, typographical errors, and real world identity changes pose significant challenges to this [...]

Connecting the Dots for Better Outcomes The most vulnerable individuals in society often struggle with long-lasting, multi-faceted challenges such as mental illness, substance abuse, chronic health conditions, and homelessness. Individuals experiencing these difficulties tend to interact with public services and departments frequently, yet many communities struggle to identify them and meet their needs in meaningful [...]

Data Science for Social Good Fellowship Update We wanted to share an update with you from the Data Science for Social Good Fellowship team. Based on the funding situation and other projects that we’re launching and continuing, we have decided not to run a DSSG summer fellowship this summer. I know this will come as [...]