About this dataset

Context

This list ranks the 345 cities in the Massachusetts by Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Hispanic Black Population: This column displays the rank of cities in the Massachusetts by their Hispanic Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Black Population: The Hispanic Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Massachusetts Hispanic Black Population: This tells us how much of the entire Massachusetts Hispanic Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

The 2022 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

2020 Census data for the city of Boston, Boston neighborhoods, census tracts, block groups, and voting districts. In the 2020 Census, the U.S. Census Bureau divided Boston into 207 census tracts (~4,000 residents) made up of 581 smaller block groups. The Boston Planning and Development Agency uses the 2020 tracts to approximate Boston neighborhoods. The 2020 Census Redistricting data also identify Boston’s voting districts.

For analysis of Boston’s 2020 Census data including graphs and maps by the BPDA Research Division and Office of Digital Cartography and GIS, see 2020 Census Research Publications

For a complete official data dictionary, please go to 2020 Census State Redistricting Data (Public Law 94-171) Summary File, Chapter 6. Data Dictionary. 2020 Census State Redistricting Data (Public Law 94-171) Summary File

2020 Census Tracts In Boston

2020 Census Block Groups In Boston

Boston Neighborhood Boundaries Approximated By 2020 Census Tracts

Boston Voting District Boundaries

This file contains the 65 cities and towns in Massachusetts for which MBTA bus or rapid transit service is provided. This data is based off of the 2010 census. The legislative intent for some boundaries could not be mapped. Boundaries where that is true are identified in the attribute information. Name Description Data Type Example town_name Full name for the MA town or city identification. String Boston town_id MassGIS Town-ID Code (alphabetical, 1-351) Numeric 34 sum_acres Area covered by the town or city in acres. Double 31304.22 sum_square Area covered by the town or city in square miles. Double 48.91 Use constraints: This data set, like all other cartographic products may contain inherent aberrations in geography or thematical errors. The boundaries included in this data set were developed using accepted GIS methodology. Cartographic products can never truly represent real-world conditions due to several factors. These factors can include, but are not limited to: human error upon digitizing, computational tolerance of the computer, or the distortion of map symbology. Because of these factors MassGIS cannot be held legally responsible for personal or property damages resulting from any type of use of the data set. These boundaries are suitable for map display and planning purposes. They cannot be used as a substitute for the work of a professional land surveyor.MassDOT/MBTA shall not be held liable for any errors in this data. This includes errors of omission, commission, errors concerning the content of the data, and relative and positional accuracy of the data. This data cannot be construed to be a legal document. Primary sources from which this data was compiled must be consulted for verification of information contained in this data.

This layer represents all the public and many of the private roadways in Massachusetts, including designations for Interstate, U.S. and State routes. Formerly known as the Massachusetts Highway Department (MHD) Roads, then the Executive Office of Transportation - Office of Transportation Planning (EOT-OTP) Roads, the MassDOT roads layer includes linework from the 1:5,000 road and rail centerlines data that were interpreted as part of the 1990s Black and White Digital Orthophoto project. The Massachusetts Department of Transportation - Office of Transportation Planning, which maintains this layer, continues to add linework from municipal and other sources and update existing linework using the most recent color ortho imagery as a base. The attribute table includes many "road inventory" items maintained in MassDOT's linear referencing system. The data layer published in November 2018 is based on the MassDOT 2017 year-end Road Inventory layer and results of a 2014-2015 MassDOT-Central Transportation Planning Staff project to conflate street names and other attributes from MassGIS' "base streets" to the MassDOT Road Inventory linework. The base streets are continually maintained by MassGIS as part of the NextGen 911 and Master Address Database projects. MassGIS staff reviewed the conflated layer and added many base street arcs digitized after the completion of the conflation work. MassGIS added several fields to support legacy symbology and labeling. Other edits included modifying some linework in areas of recent construction and roadway reconfiguration to align to 2017-2018 Google ortho imagery, and making minor fixes to attributes and linework.In ArcSDE this layer is named EOTROADS_ARC.From this data layer MassGIS extracted the Major Roads and Major Highway Routes layers.

This data set includes all channels of engagement in which a service request is created.

Refer to this link to learn more about BOS:311: https://www.cityofboston.gov/311/

Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

Building permits help to establish compliance of construction work with the minimum standards of safety established by the State Building Code to ensure public health and safety for everyone. A building permit is required before beginning most construction, demolition, modification and repair work. The Inspectional Services Department offers permitting processes tailored for a wide variety of projects, from home repairs to building demolition.

For more information on the permitting process, visit our Inspectional Services Department Permitting Process page. To apply for a new building permit or check the status of your pending permit application, go to our City of Boston Permits and Licenses Application page.

WHAT IS THE DATASET FOR?

This dataset includes information about building permits issued by the City of Boston from 2009 to the present. Permits that are being processed or have been denied, deleted, void or revoked are not included in the dataset.

WHAT PERMIT TYPES ARE PRESENT IN THE DATASET?

This dataset includes information about the following types of building permits:

• Short Form Building Permit
• Electrical Permit
• Plumbing Permit
• Gas Permit
• Electrical Low Voltage
• Long Form/Alteration Permit
• Electrical Fire Alarms
• Certificate of Occupancy
• Electrical Temporary Service
• Amendment to a Long Form
• Erect/New Construction
• Use of Premises
• Foundation Permit

For more information on these permits and their application process, visit our Building Permits information page.

WHAT DOES EACH PERMIT APPLICATION STATUS MEAN?

• Issued: indicates that the permit has been issued on date specified as issued_date.

• Open: indicates that the permit has been issued and is still valid for the applicant (i.e. not expired yet).

• Closed: indicates that the permit was successfully issued but is not valid anymore (i.e. has expired).

• Stop work: indicates the permit was successfully issued but it stopped working due to non-compliance or other issues before the expiration date.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

Vision Zero Boston is our commitment to focus the city’s resources on proven strategies to eliminate fatal and serious traffic crashes in the city by 2030. We are inspired by the belief that even one fatality is too many. Learn more about about the Vision Zero Boston program at https://www.boston.gov/departments/transportation/vision-zero.

This dataset, provided as part of the Vision Zero Boston program, contains records of the date, time, location, and type of crash for incidents requiring public safety response which may involve injuries or fatalities. All records are compiled by the Department of Innovation and Technology from the City's Computer-Aided Dispatch (911) system and verified as having required a response from a public safety agency. To protect the privacy of individuals involved in these incidents, we do not indicate the severity of specific crashes or whether medical care was provided in any specific case.

Additional notes:

• Each incident is included only once regardless of the number of individuals involved.
• The date and time of an incident reflects when public safety response was dispatched to the location, not the crash itself.
• Records are typically updated on a monthly basis, but because the verification process involves manual confirmation of incidents, exact posting schedules may vary.
• Records may be updated after their initial posting if new information becomes available.
• Data on pedestrian and bicycle incidents is now available through December 31, 2024. Motor Vehicle incident data for July 1, 2024 to December 31, 2024 is delayed due to a change in the reporting system.

This dataset provides information about the number of properties, residents, and average property values for Massachusetts Avenue cross streets in Johnson City, NY.

This dataset provides information about the number of properties, residents, and average property values for City Point Court cross streets in South Boston, MA.

ESRI point feature class representing City of Somerville, Massachusetts police station locations.

Find data on drinking water quality in Massachusetts. This dataset shows drinking water exceedances for lead by Community Water System and year of exceedance in Massachusetts.

This data set contains information on the yearly average of the number of jobs in Somerville since 2001. The data comes from the Massachusetts Department of Economic Research's Employment and Wage (ES-202) Reports. For more information, see https://lmi.dua.eol.mass.gov/lmi/EmploymentAndWages.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Newton. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2022

Based on our analysis ACS 2022 1-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Newton, the median income for all workers aged 15 years and older, regardless of work hours, was $100,920 for males and $54,820 for females.

These income figures highlight a substantial gender-based income gap in Newton. Women, regardless of work hours, earn 54 cents for each dollar earned by men. This significant gender pay gap, approximately 46%, underscores concerning gender-based income inequality in the city of Newton.

- Full-time workers, aged 15 years and older: In Newton, among full-time, year-round workers aged 15 years and older, males earned a median income of $175,177, while females earned $103,839, leading to a 41% gender pay gap among full-time workers. This illustrates that women earn 59 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Newton, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/newton-ma-income-by-gender.jpeg" alt="Newton, MA gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Newton median household income by gender. You can refer the same here

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

This dataset provides information about the number of properties, residents, and average property values for City View Road cross streets in Brookline, MA.

The 2020 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. In New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont), the Office of Management and Budget (OMB) has defined an alternative county subdivision (generally cities and towns) based definition of Core Based Statistical Areas (CBSAs) known as New England City and Town Areas (NECTAs). NECTAs are defined using the same criteria as Metropolitan Statistical Areas and Micropolitan Statistical Areas and are identified as either metropolitan or micropolitan, based, respectively, on the presence of either an urban area of 50,000 or more population or an urban cluster of at least 10,000 and less than 50,000 population. A NECTA containing a single core urban area with a population of at least 2.5 million may be subdivided to form smaller groupings of cities and towns referred to as NECTA Divisions. The generalized boundaries in this file are based on those defined by OMB based on the 2010 Census, published in 2013, and updated in 2018.