MIT Blueprint Labs emphasizes real-world impact. In addition to generating rigorous evidence, we spread the word and collaborate with policymakers who use our evidence-based tools.
We like to think of our work as laying the blueprint for social impact. Through several policy partnerships, Blueprint Labs aims to foster continuous interaction between rigorous research, policy design, implementation, and evaluation. We also hold regular events and host a fellowship program to convene practitioners, policymakers, and scholars. These events provide a unique space for leaders to apply the latest research to pressing policy problems.
Our studies released include working papers and published research by our faculty co-directors, faculty affiliates, and graduate students.
Media mentions include social media, radio, and newspaper discussions of our research.
Lives impacted include estimations of people impacted by our centralized assignment research (1.6 million) and vaccine distribution work (4.1 million).
Centralized assignment: Since 2003, Blueprint researchers have supported school districts developing and implementing centralized assignment systems. To calculate the number of lives impacted, we counted the number of students enrolled in the 2019-20 school year in the following cities that use centralized assignment: Boston, Chicago, Denver, Indianapolis, Newark, New Orleans, and New York City.
Vaccine distribution: At the beginning of the Covid-19 pandemic, a Blueprint Labs team used tools from the field of market design to propose mechanisms that ration vital scarce medical resources such as ventilators, anti-viral drugs, and vaccines. The interdisciplinary team collaborated with health care policymakers to introduce the concept, and now these tools are being used as part of state policy and various allocation frameworks.
To estimate the total number of people impacted by this work, we first considered the set of states that used a reserve in vaccine allocation. Next, we determined the size of the reserve from policy and media reports, approximating the start and end of the policy period from policy and media reports. We then computed the approximate number of vaccines administered and used the reserve size to determine the number of vaccines administered under the reserve for a disadvantaged population (this was the usual population the reserve targeted) in the policy period. Finally, we divided that number by 2 to get the number of lives impacted (to simplify, we assumed that each person received 2 vaccines).
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