The study analyzes the forces leading to or impeding the assimilation of 18- to 32-year-olds from immigrant backgrounds that vary in terms of race, language, and the mix of skills and liabilities their parents brought to the United States. To make sure that what we find derives specifically from growing up in an immigrant family, rather than simply being a young person in New York, a comparison group of people from native born White, Black, and Puerto Rican backgrounds was also studied. The sample was drawn from New York City (except for Staten Island) and the surrounding counties in the inner part of the New York-New Jersey metropolitan region where the vast majority of immigrants and native born minority group members live and grow up. The study groups make possible a number of interesting comparisons. Unlike many other immigrant groups, the West Indian first generation speaks English, but the dominant society racially classifies them as Black. The study explored how their experiences resemble or differ from native born African Americans. Dominicans and the Colombian-Peruvian-Ecuadoran population both speak Spanish, but live in different parts of New York, have different class backgrounds prior to immigration, and, quite often, different skin tones. The study compared them to Puerto Rican young people, who, along with their parents, have the benefit of citizenship. Chinese immigrants from the mainland tend to have little education, while young people with overseas Chinese parents come from families with higher incomes, more education, and more English fluency. Respondents were divided into eight groups depending on their parents' origin. Those of immigrant ancestry include: Jewish immigrants from the former Soviet Union; Chinese immigrants from the mainland, Taiwan, Hong Kong, and the Chinese Diaspora; immigrants from the Dominican Republic; immigrants from the English-speaking countries of the West Indies (including Guyana but excluding Haiti and those of Indian origin); and immigrants from Colombia, Ecuador, and Peru. These groups composed 44 percent of the 2000 second-generation population in the defined sample area. For comparative purposes, Whites, Blacks, and Puerto Ricans who were born in the United States and whose parents were born in the United States or Puerto Rico were also interviewed. To be eligible, a respondent had to have a parent from one of these groups. If the respondent was eligible for two groups, he or she was asked which designation he or she preferred. The ability to compare these groups with native born Whites, Blacks, and Puerto Ricans permits researchers to investigate the effects of nativity while controlling for race and language background. About two-thirds of second-generation respondents were born in the United States, mostly in New York City, while one-third were born abroad but arrived in the United States by age 12 and had lived in the country for at least 10 years, except for those from the former Soviet Union, some of whom arrived past the age of 12. The project began with a pilot study in July 1996. Survey data collection took place between November 1999 and December 1999. The study includes demographic variables such as race, ethnicity, language, age, education, income, family size, country of origin, and citizenship status.

This dataset compiles a comprehensive database containing 90,327 street segments in New York City, covering their street design features, streetscape design, Vision Zero treatments, and neighborhood land use. It has two scales-street and street segment group (aggregation of same type of street at neighborhood). This dataset is derived based on all publicly available data, most from NYC Open Data. The detailed methods can be found in the published paper, Pedestrian and Car Occupant Crash Casualties Over a 9-Year Span of Vision Zero in New York City. To use it, please refer to the metadata file for more information and cite our work. A full list of raw data source can be found below:

Motor Vehicle Collisions – NYC Open Data: https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95

Citywide Street Centerline (CSCL) – NYC Open Data: https://data.cityofnewyork.us/City-Government/NYC-Street-Centerline-CSCL-/exjm-f27b

NYC Building Footprints – NYC Open Data: https://data.cityofnewyork.us/Housing-Development/Building-Footprints/nqwf-w8eh

Practical Canopy for New York City: https://zenodo.org/record/6547492

New York City Bike Routes – NYC Open Data: https://data.cityofnewyork.us/Transportation/New-York-City-Bike-Routes/7vsa-caz7

Sidewalk Widths NYC (originally from Sidewalk – NYC Open Data): https://www.sidewalkwidths.nyc/

LION Single Line Street Base Map - The NYC Department of City Planning (DCP): https://www.nyc.gov/site/planning/data-maps/open-data/dwn-lion.page

NYC Planimetric Database Median – NYC Open Data: https://data.cityofnewyork.us/Transportation/NYC-Planimetrics/wt4d-p43d

NYC Vision Zero Open Data (including multiple datasets including all the implementations): https://www.nyc.gov/content/visionzero/pages/open-data

NYS Traffic Data - New York State Department of Transportation Open Data: https://data.ny.gov/Transportation/NYS-Traffic-Data-Viewer/7wmy-q6mb

Smart Location Database - US Environmental Protection Agency: https://www.epa.gov/smartgrowth/smart-location-mapping

Race and ethnicity in area - American Community Survey (ACS): https://www.census.gov/programs-surveys/acs

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The main aim of this research is to study the criminal mobility of ethnic-based organized crime groups. The project examines whether organized crime groups are able to move abroad easily and to reproduce their territorial control in a foreign country, or whether these groups, and/or individual members, start a life of crime only after their arrival in the new territories, potentially as a result of social exclusion, economic strain, culture conflict and labeling. More specifically, the aim is to examine the criminal mobility of ethnic Albanian organized crime groups involved in a range of criminal markets and operating in and around New York City, area and to study the relevance of the importation/alien conspiracy model versus the deprivation model of organized crime in relation to Albanian organized crime. There are several analytical dimensions in this study: (1) reasons for going abroad; (2) the nature of the presence abroad; (3) level of support from ethnic constituencies in the new territories; (4) importance of cultural codes; (5) organizational structure; (6) selection of criminal activities; (7) economic incentives and political infiltration. This study utilizes a mixed-methods approach with a sequential exploratory design, in which qualitative data and documents are collected and analyzed first, followed by quantitative data. Demographic variables in this collection include age, gender, birth place, immigration status, nationality, ethnicity, education, religion, and employment status. Two main data sources were employed: (1) court documents, including indictments and court transcripts related to select organized crime cases (84 court documents on 29 groups, 254 offenders); (2) in-depth, face-to-face interviews with 9 ethnic Albanian offenders currently serving prison sentences in U.S. Federal Prisons for organized crime related activities, and with 79 adult ethnic Albanian immigrants in New York, including common people, undocumented migrants, offenders, and people with good knowledge of Albanian organized crime modus operandi. Sampling for these data were conducted in five phases, the first of which involved researchers examining court documents and identifying members of 29 major ethnic Albanian organized crime groups operating in the New York area between 1975 and 2013 who were or had served sentences in the U.S. Federal Prisons for organized crime related activities. In phase two researchers conducted eight in-depth interviews with law enforcement experts working in New York or New Jersey. Phase three involved interviews with members of the Albanian diaspora and filed observations from an ethnographic study. Researchers utilized snowball and respondent driven (RDS) recruitment methods to create the sample for the diaspora dataset. The self-reported criteria for recruitment to participate in the diaspora interviews were: (1) age 18 or over; (2) of ethnic Albanian origin (foreign-born or 1st/2nd generation); and (3) living in NYC area for at least 1 year. They also visited neighborhoods identified as high concentrations of ethnic Albanian individuals and conducted an ethnographic study to locate the target population. In phase four, data for the cultural advisors able to help with the project data was collected. In the fifth and final phase, researchers gathered data for the second wave of the diaspora data, and conducted interviews with offenders with ethnic Albanian immigrants with knowledge of the organized crime situation in New York City area. Researchers also approached about twenty organized crime figures currently serving a prison sentence, and were able to conduct 9 in-depth interviews.

This survey of minority groups was part of a larger project to investigate the patterns, predictors, and consequences of midlife development in the areas of physical health, psychological well-being, and social responsibility. Conducted in Chicago and New York City, the survey was designed to assess the well-being of middle-aged, urban, ethnic minority adults living in both hyper-segregated neighborhoods and in areas with lower concentrations of minorities. Respondents' views were sought on issues relevant to quality of life, including health, childhood and family background, religion, race and ethnicity, personal beliefs, work experiences, marital and close relationships, financial situation, children, community involvement, and neighborhood characteristics. Questions on health explored the respondents' physical and emotional well-being, past and future attitudes toward health, physical limitations, energy level and appetite, amount of time spent worrying about health, and physical reactions to those worries. Questions about childhood and family background elicited information on family structure, the role of the parents with regard to child rearing, parental education, employment status, and supervisory responsibilities at work, the family financial situation including experiences with the welfare system, relationships with siblings, and whether as a child the respondent slept in the same bed as a parent or adult relative. Questions on religion covered religious preference, whether it is good to explore different religious teachings, and the role of religion in daily decision-making. Questions about race and ethnicity investigated respondents' backgrounds and experiences as minorities, including whether respondents preferred to be with people of the same racial group, how important they thought it was to marry within one's racial or ethnic group, citizenship, reasons for moving to the United States and the challenges faced since their arrival, their native language, how they would rate the work ethic of certain ethnic groups, their views on race relations, and their experiences with discrimination. Questions on personal beliefs probed for respondents' satisfaction with life and confidence in their opinions. Respondents were asked whether they had control over changing their life or their personality, and what age they viewed as the ideal age. They also rated people in their late 20s in the areas of physical health, contribution to the welfare and well-being of others, marriage and close relationships, relationships with their children, work situation, and financial situation. Questions on work experiences covered respondents' employment status, employment history, future employment goals, number of hours worked weekly, number of nights away from home due to work, exposure to the risk of accident or injury, relationships with coworkers and supervisors, work-related stress, and experience with discrimination in the workplace. A series of questions was posed on marriage and close relationships, including marital status, quality and length of relationships, whether the respondent had control over his or her relationships, and spouse/partner's education, physical and mental health, employment status, and work schedule. Questions on finance explored respondents' financial situation, financial planning, household income, retirement plans, insurance coverage, and whether the household had enough money. Questions on children included the number of children in the household, quality of respondents' relationships with their children, prospects for their children's future, child care coverage, and whether respondents had changed their work schedules to accommodate a child's illness. Additional topics focused on children's identification with their culture, their relationships with friends of different backgrounds, and their experiences with racism. Community involvement was another area of investigation, with items on respondents' role in child-rearing, participation on a jury, voting behavior, involvement in charitable organizations, volunteer experiences, whether they made monetary or clothing donations, and experiences living in an institutional setting or being homeless. Respondents were also queried about their neighborhoods, with items on neighborhood problems including racism, vandalism, crime, drugs, poor schools, teenag

The leading causes of death by sex and ethnicity in New York City from 2007 to 2014. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

Data Description

Year: year of the death. Leading Cause: the cause of death. Sex: the decedent's sex. Race Ethnicity: the decedent's ethnicity. Deaths: the number of people who died due to cause of death. Death Rate: the death rate within the sex and Race/ethnicity category. Age Adjusted Death Rate: the age-adjusted death rate within the sex and Race/ethnicity category.

How to used this data

These are a couple of ideas what questions can be answered with this data:

1. Are there trends within gender groups?
2. Are there trends within race/ethnicity groups?
3. Is the number of leading causes of deaths increasing or decreasing over time?

Source

Bureau of Vital Statistics and New York City Department of Health and Mental Hygiene

Nigeria has hundreds of ethnic groups that are usually divided and defined primarily by language. The country hosts more ethnic groups than any other African nation, ranking among the most ethnically-complex states in the world. Most of these ethnic groups are small and localized, with only a few playing a central role in Nigerian society. The major people groups of Nigeria are: Hausa, Fulani, Yoruba, and Igbo (Ibo).The advent of colonial rule in Nigeria brought the various ethnic groups increasingly into contact with one another. This integrative process was facilitated by the construction of connective infrastructure. This increasing development set in motion a process that led to greater contact and competition among the various ethnic groups for dominance and economic advantage. The Nigerian government has worked out tentative power-sharing arrangements to help ensure that its many ethnic groups have some say in society. However, cities remain largely segregated along ethno-religious lines and confrontation between ethnic groups is common. Often, ethnic clashes in one part of the country can set off a chain of reprisal riots and attacks in other parts of the country.Most major ethnic groups have seen the formation of ethnic-exclusive militias to protect alleged group interests and perpetrate violence against other ethnic groups. These vigilante groups continue to act with impunity for lack of stringent law enforcement in much of the state. These continued attacks and tensions among ethnic groups threaten to destabilize an already unsteady country.Hausa - Northern Nigeria is dominated by this ethnic group and is often considered unified with the Fulani through intermarriage of acculturation, generating the Hausa-Fulani as a single ethnic entity. The Hausa were predominately traders throughout the Sahara and Sahel regions but have become more concentrated in rural areas as farmers and herders. They are predominately Muslim with some of the smaller sub-groups such as the Maguzawa practicing indigenous faiths. Their religion is a key component to ethnic identity and continues to shape their role in modern Nigerian society and politics. The Hausa and Fulani were instrumental in establishing and maintaining Sharia in 11 of the country’s northern states.Fulani –The Fulani are an ethnic group of Muslims located in northern Nigeria that have often assimilated into the Hausa culture. At one point nomadic herders, they arrived in the Hausa states sometime in the early 13th century. Many have intermarried with the Hausa and have mostly adopted those customs and language, although some Fulani choose to stay "pure" by retaining a nomadic lifestyle, their own language, and cultural autonomy. The Fulani are most distinctively known for a dispute that developed between them and the local King of Gobir, which developed into a jihad ending with a Fulani conquest of the Hausa states in the early 1800s.Yoruba – The Yoruba are Christian/Muslims living in southwestern Nigeria united by their common belief that Ife is their place of origin and the Oni of Ife is their spiritual leader. Their mythology holds that "Oduduwa" created the earth and that royal houses of the Yoruba kingdoms can trace their ancestry back to "Oduduwa.” Yoruba society is organized into kingdoms, the greatest of which was called Oyo. The Oyo Empire collapsed in 1830, when Afonja, broke away from the rest of the Yoruba culture and lost his empire to the Fulani. This event occurred in close temporal proximity to the Fulani Jihad, but was not associated with it. As Islam and Christianity spread to Yorubaland over the past few centuries, the group embraced both faiths alongside its many traditional and animist beliefs. This blend and acceptance of religion survives in modern society and has mitigated some religious conflict in places where Yoruba form the majority.Igbo (Ibo) – The Igbo are the main ethnic group living in southeastern Nigeria. They have represented some of the staunchest opponents to the establishment of Sharia in the North where some minority Igbo populations exist. As opposed to Hausa-Fulani and Yoruba cultures, the Igbo were traditionally decentralized and non-hierarchical, making them more receptive to European conversion efforts.Under British colonial rule, many Igbo served in government and military roles and were later key players in the 1960 Nigerian independence movement. In January 1966, Igbo leader General Ironsi established a military coup in Nigeria to try and unify a fragmented, newly-independent Nigeria. The northern section of the country believed there was an Igbo conspiracy with the establishment of the new government. In July 1966, a counter-attack was staged by northern military officers in response to the constitution of another new government. Chaos ensued and about 50,000 Igbo were killed in northern Nigeria. To put an end to chaos and upheaval, groups in eastern Nigeria declared themselves as an independent sovereign state known as “Biafra" on 30 May 1967. The Igbo secessionist movement in Biafra led to a 30-month war (Biafran War) with the Nigerian government, in which hundreds of thousands of Igbo starved to death. After the war, Igbo were reintegrated into Nigerian society, but in a more marginalized role. Despite lingering ethnic tension, they now play an important part in southeastern Nigeria's oil trade.

ISO3 - International Organization for Standardization 3-digit country code

PEOPLEGP_1 - People group level one

PEOPLEGP_2 - People group level two

PEOPLEGP_3 - People group level three

ALT_NAME - Alternate names or spellings for people groups

SOURCE_DT - Primary source creation date

SOURCE - Primary source

Collection

This shapefile created by using Anthromapper consists of ethnic layers that have been primarily based on the 1959 Murdock map of Africa with an addition of the Anaang people group based on a general location provided by Ethnologue. Geographical terrain features, combined with a watershed model, were also used to predict the likely extent of ethnic and linguistic influence. The HGIS data and metadata were supplemented with anthropological information from peer-reviewed journals and published books. The interpretation of ethnic names often produces multiple spellings of the same people groups; therefore similarly spelled or phonetic titles may be referencing the same group.

The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

Sources (HGIS)

Anthromapper. DigitalGlobe Analytics, March 2013.

Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.

Interactive Murdock Map available at - http://worldmap.harvard.edu/africamap.

Ethnologue, “Anaang.” Last modified April 2013. Accessed April 2013. http://www.ethnologue.com

People Groups, “Nigeria.” Last modified April 2013. Accessed April 2013. http://peoplegroups.org.

Joshua Project, “Nigeria”. Last modified March 2013. Accessed April 2013. http://www.joshuaproject.net.

Sources (Metadata)

Walker, Andrew. United States Institute of Peace, "What is Boko Haram?." Last modified 2012. Accessed April 9, 2013. http://www.usip.org.

Buhayar, Noah. PBS, "Oil and Politics in Nigeria." Last modified 2007. Accessed April 8, 2013. www.pbs.org.

Bascom, William. Urbanization Among the Yoruba. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Greenberg, Joseph H. Some Aspects of Negro-Mohammedan Culture Contact Among the Hausa. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Levinson, David. Ethnic Groups Worldwide: A Ready Reference Handbook. Santa Barbara: Greenwood, 1998.

Ehwarieme, William. "Between the Devil and the Deep Blue Sea: The Displacement of Ethnicity by Corruption in Nigeria's Electoral Politics." Journal of Third World Studies. 26. no. 2 (2011): 181-206.

Paden, John. Religion and Political Culture in Kano. University of California Press: Berkeley and Los Angeles, 1973.

Suberu, Rotimi. Federalism and Ethnic Conflict in Nigeria. Washington D.C.: United States Institute of Peace, 2001.

Joshua Project, “Nigeria”. Last modified April 2013. Accessed April 2013. http://www.joshuaproject.net.

Summary File 2 contains 100-percent United States decennial Census data, which is the information compiled from the questions asked of all people and about every housing unit. Population items include sex, age, race, Hispanic or Latino origin, household relationship, and group quarters occupancy. Housing items include occupancy status, vacancy status, and tenure (owner-occupied or renter- occupied). The 100-percent data are presented in 36 population tables ("PCT") and 11 housing tables ("HCT") down to the census tract level. Each table is iterated for 250 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), and 39 Hispanic or Latino groups. The presentation of tables for any of the 250 population groups is subject to a population threshold of 100 or more people, that is, if there were fewer than 100 people in a specific population group in a specific geographic area, their population and housing characteristics data are not available for that geographic area.

These tables will stop being updated after June 1, 2023. COVID-19 vaccination reporting is expected to resume when a new COVID-19 vaccination formulation is authorized.

As 4/22/2023, CDC recommends bivalent vaccine for everyone regardless of age and whether or not the person has had prior monovalent vaccine.

This table shows the cumulative number and percentage of people who have received an updated (bivalent) COVID-19 vaccination by race/ethnicity and age group for people 5 years and over.

• Data are reported weekly on Thursday and include doses administered to Saturday of the previous week.

• All data in this report are preliminary. Data for previous weeks may be changed because of delays in reporting, deduplication, or correction of errors.

• The table groups people based on their current age and excludes people known to be deceased.

• The analyses here are based on data reported to CT WiZ which is the immunization information system for CT. Connecticut COVID-19 Vaccine Program providers are required to report to CT WiZ all COVID-19 doses administered in CT including to CT residents and to residents of other jurisdictions. CT Wiz also receives records on CT residents vaccinated in other jurisdictions and by federal entities which share data with CT WiZ electronically (currently: RI, NJ, New York City, DE, Philadelphia, NV, Indian Health Service, Department of Veterans Affairs (doses administered since 11/2022)). Electronic data exchange is being added jurisdiction-by-jurisdiction. Once a jurisdiction is added to CT WiZ, the records for residents of that jurisdiction vaccinated in CT are removed. For example, when CT residents vaccinated in NYC were added, NYC residents vaccinated in CT were removed.

• Population size estimates used to calculate cumulative percentages are based on 2020 DPH provisional census estimates*.

• Race and ethnicity data may be self-reported or taken from an existing electronic health care record. Reported race and ethnicity information is used to create a single race/ethnicity variable. People with Hispanic ethnicity are classified as Hispanic regardless of reported race. People with a missing ethnicity are classified as non-Hispanic. People with more than one race are classified as multiple races. A vaccine coverage percentage cannot be calculated for people classified as NH (non-Hispanic) Other race or NH Unknown race since there are no population size estimates for these groups. Data quality assurance activities suggest that in at least some cases NH Other may represent a missing value. Vaccine coverage estimates in specific race/ethnicity groups may be underestimated as result of the classification of records as NH Unknown Race or NH Other Race.

• Cumulative percentage estimates have been capped at 100%. Observed percentages may be higher than 100% for multiple reasons, inaccuracies in the census denominators or reporting errors.

• DPH Provisional State and County Characteristics Estimates April 1, 2020. Hayes L, Abdellatif E, Jiang Y, Backus K (2022) Connecticut DPH Provisional April 1, 2020, State Population Estimates by 18 age groups, sex, and 6 combined race and ethnicity groups. Connecticut Department of Public Health, Health Statistics & Surveillance, SAR, Hartford, CT.

Four tables of ACS demographic profiles for 2012 to 2016 at the NTA level. Four profiles include demographics, economic, housing and sociological. Column headers in this database are abbreviated. Please see the data dictionary (shown in worksheet entitled “Dictionary”) for an explanation of these abbreviated headers.

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

Link to this report's codebookUnfulfilled Promise of Racial EqualityUS states unequally distribute resources, services, and opportunities by raceThe US is failing to deliver on its promise of racial equality. While the US founding documents assert that ‘all men are created equal,’ this value is not demonstrated in outcomes across areas as diverse and varied as education, justice, health, gender, and pollution. On average, white communities receive resources and services at a rate approximately three times higher, than the least-served racial community (data on Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities, were used as available). Evidence shows that unequal treatment impacts each of these communities, however, it is most often Black and Indigenous communities that are left the furthest behind. When states are scored on how well they deliver the United Nations Sustainable Development Goals (SDGs) to the racial group least served, no state is even halfway to achieving the SDGs by 2030 (see Figure 1). To learn more about the Sustainable Development Goals, see the section “SDGs & Accountability.”One example of this inequality is in life expectancy. In Figure 2, the scatter plot on the left demonstrates a pattern in which Black and Indigenous communities, represented by orange and green dots closest to the bottom of the graph, are consistently the communities with least access to years of life. In the graph on the right, each box represents a racial population in a specific state, the boxes are organized from left to right, lowest to highest, according to the life expectancy for that group and state. The graph shows how large the gap is in life expectancy across racial communities and states, with green and orange boxes, representing Indigenous and Black communities respectively, clustered to the left of the graph.Patterns like this one, demonstrating both deep and wide racial inequalities, occur across the 51 indicators this analysis includes, covering 12 of 17 SDGs. In a similar example (Figure 3), a pattern emerges where white students are least likely to attend a school where 75 percent or more of its students receive free or reduced cost lunch when compared to all other racial groups. In the most unequal state, North Dakota, Indigenous students attend high poverty schools at a rate 42 times higher than white students. As Figure 3 shows, although the percentage of students from the least served racial group attending high poverty schools ranges from 2 percent in Vermont to 73 percent in Mississippi, the group least served, represented by the dots closest to the top of the graph, are most often Hispanic and Indigenous communities.Lack of Racial DataMore, and better, racially and ethnically disaggregated data are needed to assess delivery of racial equalityA significant barrier to evaluating progress is the unavailability of racial data across all areas of measurement. For too many important topic areas, such as food insecurity, maternal mortality and lead in drinking water, there is no racial data available at the state level. Even in the areas where there is some racial data, it is often not available for all groups (see Figure 4). Particularly missing, were measures of environmental justice; in Goals focusing on Water, Clean Energy, and Life on Land (Goals 6, 7, and 15), racial data was not found for any indicators, despite the fact that there is research indicating that clean water, for example, is unequally distributed across racial groups. The reasons for these gaps vary. For some indicators, data is not tracked through a nationally organized database, for other indicators, the data is old and out of date, and in many cases, surveys are not large enough to disaggregate by race. As was made clear with the disparate impacts of COVID-19 (for example, see CDC 2020), understanding to whom resources are being distributed has real life implications and is an important part of holding democratic institutions accountable to promises of equality.People are often left behind due to a combination of intersecting identities and factors; they remain hidden in averages. Evaluating the Leave No One Behind Agenda through the lens of gender, ability, class and other identities are undoubtedly important and urgent. Disaggregating data along two axes such as race and location—is revealing. But an even more refined analysis using multilevel disaggregation, such as looking at women and race in urban settings, would likely reveal even starker inequalities. Those are not included here and are important areas for future work. Other areas for further exploration include the use of longitudinal data to understand how these inequalities are changing over time.Though the full extent of this unequal treatment is unknown, this analysis sheds some light on the clouded story told by state averages. Whole group averages leave out important information, particularly about inequality. Racially disaggregated data is essential for holding governments accountable to the promise of racial equity. Without it, it is too easy to hide who is being excluded and left behind.SDGs and AccountabilitySDGs and AccountabilityThe SDGs can be an accountability tool to address racial inequality. This would not be the first time UN frameworks have been used to call attention to racial inequality in the US. In 1951, the Civil Rights Congress (CRC) led by William L. Patterson and Paul Robeson put a petition to the UN, named: “We Charge Genocide,” which charged that the United States government was in violation of the Charter of the United Nations and the Convention on the Prevention and Punishment of the Crime of Genocide (Figure 5). While this attempt did not succeed in charging the US government with genocide, it is a central example of how international instruments can be used to apply localized pressure to advance civil rights.All 193 member countries of the UN, including the United States, signed on to the Sustainable Development Goals in 2015, to be achieved by 2030. The Goals cover 17 wide-ranging topics, with 169 specific targets for action (Figure 6). The first agenda of the SDGs, the Leave No One Behind Agenda (LNOB), requires that those left furthest behind by governments must have the SDGs delivered to them first. The results of this project demonstrate that in a US-context, those left furthest behind would undoubtedly include Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities. The SDGs can offer a template for US states attempting to deliver on their promise of racial equality. The broad topic areas covered by the SDGs, in combination with the Leave No One Behind agenda, can be a tool to hold states accountable for addressing racial inequalities when and through developing solutions for clean water, quality education, ending hunger, delivering justice and more. This highlights an important implication of the Leave No One Behind Agenda, it is not meant to pit communities against each other, but rather to remind us how much everyone has to gain by building and advocating for sustainable communities that serve us all.Explore ResultsExplore the data from the In the Red: the US failure to deliver on a promise of racial equality in our interactive dashboards.These maps display how US states are delivering sustainability across different racial and ethnic groups. As part of the Leave No One Behind Agenda, which maintains that those who have been least served by development progress must be those first addressed through the SDGs, progress toward the goals in each state is displayed based on the racial group with the least access to resources, programs, and services in that state. In other words, the “Overall scores’’ map shows the score for the racial group least served in each state. Click on a state to toggle through the state’s performance by different SDGs, and click on an indicator to view how a state performs on a given indicator. At the indicator level, horizontal bar charts show the racial disparity in the selected indicator and state, when data is available.AboutIn the Red: the US Failure to Deliver on a Promise of Racial EqualityIn the Red: the US Failure to Deliver on a Promise of Racial Equality project highlights measurable gaps in how states deliver sustainability to different racial groups. The full report can be read here. It extends an earlier report, Never More Urgent, looking at policies and practices that have led to the inequalities described in this project. It was prepared by a group of independent experts at SDSN and Howard University.UN Sustainable Development Solutions Network (SDSN)The UN Sustainable Development Solutions Network (SDSN) mobilizes scientific and technical expertise from academia, civil society, and the private sector to support practical problem solving for sustainable development at local, national, and global scales. The SDSN has been operating since 2012 under the auspices of the UN Secretary-General Antonio Guterres. The SDSN is building national and regional networks of knowledge institutions, solution-focused thematic networks, and the SDG Academy, an online university for sustainable development.SDSN USASDSN USA is a network of 150+ research institutions across the United States and unincorporated territories. The network builds pathways toward achievement of the UN Sustainable Development Goals (SDGs) in the United States by mobilizing research, outreach, collective action, and global cooperation. SDSN USA is one of more than 40 national and regional SDSN networks globally. It is hosted by the UN Sustainable Development Solutions Network (SDSN) in New York City, and is chaired by Professors Jeffrey Sachs (Columbia University), Helen Bond (Howard University), Dan Esty (Yale University), and Gordon McCord (UC San Diego).

Associations between demographic and behavioral characteristics and each type of sexual assault since enrolling at CU/BC, by gender.

The Distance Sailing Race layer depicts race routes as mapped in the Northeast Coastal and Marine Recreational Use Characterization Study which was conducted by SeaPlan, the Surfrider Foundation, and Point 97 under the direction of the Northeast Regional Planning Body. Routes were mapped using a combination of outside research, leveraging existing data sources such as the Rhode Island Ocean Special Area Management Plan (RI OSAMP), and gathering input from race organizers and other industry experts through participatory mapping. For more information, users are encouraged to consult the metadata and final report.View Dataset on the Gateway