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Research Improving People's Lives FAQs

Research Improving People’s Lives (RIPL) is a tech-for-social-impact nonprofit led by science and policy experts. 

We help state and local government leaders unlock the power of data and science to improve policy. We do this by developing and deploying science, technology, and data resources that help government solve immediate policy challenges while building permanent capacity to deliver continual and fact-based policy improvement.  

RIPL was originally founded by our Founding Director, Dr. Justine Hastings, as the Rhode Island Innovative Policy Lab (RIIPL) at Brown University in 2015. Together with the State of Rhode Island, we set out to build the technical and scientific resources to create top-quality research and data-driven policy in government. 

RIPL grew to become a Rhode Island-based nonprofit in 2018. We have since expanded nationwide to partner with state and local governments across the country for impact. 

RIPL works with faculty affiliates from top research universities across the country. We regularly publish scientific research, white papers, and open-source code to ensure that government can learn from implementations in other states and implement solutions at no cost.

Please visit our Research Website to see all of RIPL’s freely-available scientific papers, tools, and code repositories. 

The Data for Opportunity in Occupation Reskilling Solution — DOORS — is an easy-to-use solution that seamlessly connects jobseekers to high-impact career pathways and training opportunities.

We often call DOORS the “Netflix for Careers.” It is a first-of-its-kind tool that that puts personalized career recommendations directly at the fingertips of  Unemployment Insurance claimants and jobseekers. Powered by Machine Learning (ML), Artificial Intelligence (AI), and states’ secure administrative wage data, DOORS surfaces career paths that other jobseekers like the user have previously transitioned into successfully — meaning that they found rewarding, resilient, and better-earning jobs.

DOORS then matches users with highly relevant job openings in in-demand careers. If a jobseeker needs upskilling on the way, it connects them with recommend proven-effective reskilling opportunities and social and community services to support their journey. Users have the support of an AI-powered bot to guide their transition, and an integrated experience that allows accessible log-in across workforce systems without having to upload information multiple times to connect with a new opportunity. 

The DOORS pilot launched in Rhode Island in late 2020 using federal funding and has now expanded to Hawai’i. It is launching in three additional states in 2022 and is coming to more states across the country in 2023. 

DOORS has been covered in Politico (‘How ‘Netflix for Jobs’ could aid in the Great Resignation’ and ‘17 pandemic innovations that are here to stay’), as well as in StateScoop, Government Computer News (GCN) (‘AI-powered career recommendation engine delivers more job options’ and ‘Cutting through data silos to reduce unemployment’), PBS NewsHour, The Future of Work podcast, Forbes, and the Boston Globe. Our partners in Colorado, Hawai’i, Rhode Island, and Wisconsin have also shared coverage of their deployment of DOORS. 

RIPL has presented on DOORS to the U.S. House Committee on Education and Labor and the Equal Employment Opportunity Commission to advise how ML and AI can be used to equitably connect workers to in-demand careers and expand opportunity across the country. RIPL publishes scientific research and open-source code to ensure that governments can learn from implementations in other states and implement solutions at no cost. To learn more about the scientific and technical insights powering DOORS and the Research Data Lake, please visit our DOORS webpage.  

Sockit is a self-contained toolkit for assigning probabilistic Standard Occupational Classification (SOC) codes to free-text job titles. It is developed by Research Improving People’s Lives (RIPL).

Labor market information is often organized by codes that group together similar jobs into a hierarchy of standard occupations. The most commonly used hierarchy in the US is the Standard Occupational Classification (SOC) from O*NET.

Job seekers and employers, however, use many different variations in titles to describe a job. These real-world differences often make mapping job titles to SOC codes for research or analysis a difficult task.

In partnership with NASWA and the NLx Research Hub, RIPL developed Sockit — a freely available tool that can determine the most likely SOC code for a free-text job title using Natural Language Processing (NLP) and data science techniques. Try it for yourself here

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Media Contacts

Mintaka Angell

Chief Executive Officer

Jade Borgeson

Director of Policy and Partnerships