Week 12: Two Bostons

Friday, July 17, 3:30 pm


Register now to attend the conference! Zoom login information will be shared via email prior to each session. Be sure to sign up for our email list to get updates as future panels are announced.


The Neighborhood Migration Mapper: Small-Area Moving Rates for Communities across Massachusetts
Presenter: Madeleine Daepp, Massachusetts Institute of Technology

Show abstract and co-authors


Mariana C. Arcaya, Massachusetts Institute of Technology and the Healthy Neighborhoods Consortium


What communities in the Greater Boston area face shared housing and mobility challenges? This work describes a collaboration with the Healthy Neighborhoods Study, a resident-driven participatory action research project examining the associations between urban development and health. After Resident Researchers and community partners described a dearth of small-area mobility estimates for their communities, we developed a web-based app to aid local stakeholders in understanding how people move across municipalities in the Commonwealth.

We first constructed a novel set of neighborhoods with complete coverage across the commonwealth. For Massachusetts cities, we obtained neighborhood or planning district boundaries from municipal governments; for rural and suburban areas, we overlaid regional planning authority boundaries with Metropolitan Area Planning Council community types. Data on migration from 2009 – 2019 were obtained from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel, a data set comprising a 5% sample of all U.S. adults with credit scores.

We calculated the flow of movers, normaLiz Hessed by population, for each origin-destination pair. To highlight hotspots in which flows of movers were higher than the flow that might be expected by chance, we estimated the ratio of observed versus expected movers for each origin and, separately, for each destination; we call this ratio the “Standardized Moving Ratio” (SMvR). To address concerns around anonymity and unstable rates, we used Bayesian hierarchical modeling to spatially smooth raw SMvRs. Finally, we created maps of the resulting estimates for each neighborhood both overall and stratified by individual socioeconomic advantage.

To make the resulting maps available to community organizations and residents, we developed a web app that allows users to see where people in their neighborhoods move to and from. The tool can be accessed at www.hns.media.edu:3838/migration.

Cross-Institutional and Cross-Community Collaboration. This project was produced in response to requests from the Massachusetts Department of Public Health, the Conservation Law Foundation, and other partners in the consortium with support from the Federal Reserve Bank of Boston; the metric of neighborhoods was co-developed by researchers at MAPC and MIT with feedback from all consortium partners; and the methods and user design of the mapper were informed by the contributions of resident researchers leading the participatory-action Healthy Neighborhoods Study. Moreover, we hope that this work will directly contribute to the work members of the Study are doing to co-create new directions for Boston-area communities: In the coming months, resident researchers and community organizations will be using the tool in collaborative action-oriented workshops as part of the “impact” phase of HNS.

Boston’s Invisible Borders
Presenter: Esteban Moro, Massachusetts Institute of Technology

Show abstract and co-authors

Many visible borders exist within our cities. Highways, rail tracks, school districts, or other administrative boundaries create physical barriers for people to interact in our town, creating mobility segregation, dividing communities, and increasing inequality. However, there are other invisible barriers created by the separation of different areas of income, race, or education levels. In this work, we study the existence and nature of those barriers using a large scale dataset of mobility in the Boston metro area. We found that some of the barriers coincide with physical obstacles like highways, train stations, or rivers. However, most of them can be explained by differences in house pricing, race, or economic divides. We also study the evolution of those barriers in the last years, mainly due to significant forces like gentrification or business displacement.

Perceived Racially-profiled Police Stops and Persistent Sadness and Anxiety: Findings from the 2015 and 2017 Boston Behavioral Risk Factor Surveillance System
Presenter: Johnna S. Murphy, Boston Public Health Commission

Show abstract and co-authors


Amar J. Mehta, ScD, MPH, University of Copenhagen

Daniel P. Dooley, Boston Public Health Commission


Epidemiological evidence supports the association between racism and various health outcomes but population-based evidence supporting the association between police stops due to racial discrimination and mental health is limited. We used data from the Boston Behavioral Risk Factor Surveillance System (BBRFSS) to describe the demographic and social determinant characteristics of Boston adult residents who report experience of racially-profiled police stops and to examine if the experience of being stopped by police due to perceived racial discrimination was associated with persistent sadness and persistent anxiety in the Boston adult population.

The BBRFSS is a biennial random-digit-dial household telephone survey that assesses health-related risk behaviors and socio-demographics of Boston adult residents. This cross-sectional analysis included 6,511 adults sampled from the 2015 and 2017 BBRFSS. Experience of racially-profiled police stops was determined as a positive response to the question, “Have you ever felt you were stopped by the police just because of your race or ethnic background?”. Associations between perceived racially biased police stops and measures of persistent sadness/anxiety were estimated in logistic regression adjusting for important covariates including survey year, age, sex, race/ethnicity, educational attainment, household income, and housing status.

BBRFSS data showed Black and Latino residents experience racially-profiled police stops at a much higher rate than White residents. Racially-profiled police stops were strongly associated with measures of persistent sadness and persistent anxiety, even after adjusting for covariates in this cross-sectional sample of household adult Boston residents.

Financial Well-being of Low-income Residents: An Analysis of the BEACON Survey
Presenter: Jason Ewas, City of Boston

Show abstract and co-authors


Christina Kim, BPDA Research Division; Russell Schutt, UMass Boston

Lee Hargraves, UMass Boston

Philip Brenner, UMass Boston


Last year, the Center for Survey Research at UMass Boston conducted BEACON: The Boston Panel Study (BEACON), a tool designed to measure and quantify Boston from the standpoint of its residents, across its neighborhoods and over time. The City of Boston, and the BPDA Research Division and the Economic Mobility Lab in particular, partnered with BEACON to better understand the financial well-being of low-income residents. The Lab was especially interested in getting responses from Boston residents to important questions we have no Boston-specific answers to: How many residents have a bank account? How many residents have even a small amount of emergency savings? How many have credit card debt? How much debt do they carry over month to month? And if the City develops an intervention to get un- and under-banked people affordable accounts, how would we determine its efficacy (whether people were becoming banked at greater rates)? From existing sources, it would be difficult for us to answer these questions even for dozens of people. The BEACON Survey allowed us to receive hundreds, and hopefully thousands of answers.

Because of this collaboration, we now have Boston-specific data to key questions, allowing us to develop policies and initiatives that address specific needs. For example, we previously only had MSA level data for estimates of banking access (whether people are banked, under-banked or un-banked). This survey allowed us to get more nuanced, Boston-specific data , which showed that Boston had higher rates of un- and under-banked people than the metro area. This finding gave us the knowledge to reinvigorate the Bank On Boston program. Previously, several key stakeholders had looked at the MSA numbers and said that banking access was not much of a problem in Boston, and that Bank On did not need to be a major part of the focus. Now, because of this research, Bank On Boston has moved forward with developing product standards and working with banks to conduct outreach to residents who would benefit from safe, affordable accounts.

Over time, it will also allow the City to track progress over time in a way that would otherwise be time-consuming and virtually impossible. This collaboration will continually provide new information and allow us to develop targeted policies and initiatives that support financially vulnerable residents.

Moderator: Ted Landsmark, Northeastern University