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This data collection was assembled to examine the geographic distribution of two-way dual language (TWDL) and one-way dual language (OWDL) bilingual education programs across Texas public school campuses during the 2020–2021 academic year. Campus-level bilingual program enrollment data were obtained from the Texas Education Agency (TEA) through a formal public information request submitted under the Texas Public Information Act. Geographic coordinate data were obtained from TEA's publicly available campus reference file for the 2021–2022 school year. Demographic context variables were drawn from the 2017–2021 American Community Survey 5-Year Estimates (U.S. Census Bureau), including county- and census tract-level data on nativity (Table B05012) and median household income (Table S1903). Geographic boundary files were obtained from the U.S. Census Bureau TIGER/Line Shapefiles (2021) at both the county and census tract levels.

The collection includes campus-level enrollment counts for six bilingual program types: TWDL, OWDL, ESL content-based, ESL pull-out, transitional bilingual early exit, and transitional bilingual late exit. Enrollment counts for small cell sizes were suppressed by TEA for privacy protection. The collection also includes derived variables consisting of normalized program enrollment ratios calculated as program-specific enrollment divided by total campus enrollment. Campus records include geographic coordinates, school type classification (public, charter, or alternative), district identifiers, and county identifiers. The collection additionally includes two derived shapefiles, one at the county level and one at the census tract level, in which TEA-restricted campus enrollment data are not present; these shapefiles contain only Census Bureau demographic variables (immigrant density and median household income) merged into TIGER/Line boundary geometry. Geographic coverage is the state of Texas. The data describe the 2020–2021 academic year.

This study evaluated the effects of demolishing or rehabilitating vacant and decaying buildings in Cleveland, Ohio and Detroit, Michigan as a violence prevention measure. Researchers used detailed longitudinal property-level data from 2011-2017 in Cleveland, Ohio and 2017 in Detroit, Michigan, to estimate the effects of demolition and rehabilitation of vacant and decaying properties under different targeting strategies and concentrations. The data produced by this study were aggregated into neighborhood-level variables of varying geographic specificity, which measure the study's primary outcome, firearm violence, and primary exposures, property demolition and rehabilitation. These data also include contextual variables reporting socioeconomic data, demographics, additional violent and nonviolent crime rates, and neighborhood composition variables (e.g. counts of commercial lots, apartments, single family homes/condominiums, etc.) at the neighborhood-level.

This dataset contains measures of the number and density of health care services per United States Census Tract or ZIP Code Tabulation Area (ZCTA) from 1990 through 2022. The dataset includes four separate files for four different geographic areas (GIS shapefiles from the United States Census Bureau).

The World Cities Culture Forum, established in 2012, is a leading global network of civic leaders from over 40 creative cities across six continents, representing a combined population of over 245 million. The forum fosters collaborations to place culture at the core of urban development, addressing 21st-century challenges such as climate change, affordable workspaces, cultural tourism, and diversity in public spaces. Through its Global Summit, partnerships, and programs like the Leadership Exchange Programme and Digital Dialogue Masterclasses, the forum promotes cultural integration in city planning. The World Cities Culture Report 2022 provides comprehensive open-source data on culture, including over 60 datasets from 40 cities.

• Contextual Data: Includes demographics such as characteristics of the overall and working-age populations (including percent who were foreign born) and of the geographical area, such as the percentage of national population living in the city and the percentage of the area devoted to parks and other public green spaces.
• Cultural Infrastructure: Provides counts (and rates) of various facilities and venues, including art galleries, artists' studios, rehearsal spaces, bars, bookshops, cinemas, community centers, concert halls, museums, nightclubs, libraries, video game arcades, and theatres.
• Participation and Tourism: Focuses on cultural participation metrics, such as cinema and theatre admissions, festival attendance, museum visits, average daily attendance at the top five art exhibits, and international tourist numbers.
• Creative Economy: Encompasses data on book publishing, creative industries employment, film festivals, restaurant ratings, and performances.
• Education: Includes statistics on public library book loans, higher education levels, international student enrollment, and specialist institutes in art and design education.

The source for each number is identified within the dataset. Data users can freely download selected datasets as .csv files.

Over half of public school buildings across the country fail to provide adequate conditions for students to learn and school staff to work. Prior research has established an evidence base of associations between high-quality school building facilities and student, staff, school, and community health and education outcomes. Recognizing this research and the need for facility improvements, Maryland has approved the 21st Century School Buildings Program, which is paid for by Baltimore City Public Schools (City Schools), the State of Maryland, and the City of Baltimore. The program will invest close to $1 billion to renovate or replace over two dozen school buildings. City Schools, with support from the Fund for Educational Excellence, selected the RAND Corporation to study the impact of new school buildings on student, staff, school, and community outcomes.

The goal of this first phase was to collect data prior to the start of the Baltimore 21st Century Building Program and conduct initial exploratory analyses of data from treatment schools (i.e., schools slated for renovation or rebuilding) and comparison schools (i.e., schools with similar student and school characteristics but not slated for renovation or rebuilding). The data compiled here are audits of the street segments immediately surrounding those target schools. These observations from Spring 2016 were collected in an effort to document the conditions and features of the neighborhoods prior to school building renovations.

This data collection describes baseline neighborhood characteristics prior to the 21st Century Buildings School Program. For more information about the Baltimore City Schools and the 21st Century School Building Program, please visit the 21st Century Schools website.

In 2014, the United States Department of Agriculture's Economic Research Service (USDA ERS) conducted the Rural Establishment Innovation Survey (REIS). This survey provides a nationally representative sample of innovation processes in rural businesses. REIS defines innovation as the introduction of new goods, services, or ways of doing business that are valued by consumers. Traditional measures from secondary data sources, such as patents or research and development (R&D) expenditures, focus on science and engineering-based innovation, which usually depict rural innovation as rare or idiosyncratic. By focusing instead on a broader definition of innovation, the REIS provides a fuller assessment of rural innovative capacity.

The main research questions for this survey were:

• Are rural firms as innovative as urban firms?
• What constraints are impeding the innovative capacity of firms?
• What strategies are innovative firms using to mitigate these constraints?

The target population for the survey was Nonmetro and metro establishments with 5 or more employees in tradable sectors (mining, manufacturing, wholesale trade, transportation and warehousing, finance, information, professional/technical/scientific services, arts and management of businesses). REIS used the Bureau of Labor Statistics (BLS) Quarterly Census of Employment and Wages Business Register for its sampling frame. Responses from 11,600 businesses were usable.

These data include responses from businesses in the Arts & Museums industry category. These businesses were oversampled by a factor of 3.3 to ensure reliable statistics.

The REIS data are restricted and require users to apply for access to the data. For permission to access to these data, visit the ERS Rural Economy Population: Business Industry page and scroll to the bottom of the page for contact information. If permission to access the data is granted, the data can be viewed through the NORC data enclave.

This project seeks to identify sources of ethnic and racial conflict and protest in urban America from 1954 through 1992. The data on collective events are coded using The New York Times. Detailed coding rules produced a chronological dataset that allows researchers to:

1. Analyze the location and timing of both conflicts (confrontations between two or more ethnic populations) and protests (marches, mass meetings, demonstrations on behalf of one ethnic group, expressing grievances related to discrimination or racial policy).

2. Specifically analyze a type of protest (e.g., civil rights movement activity, or urban race riots) and the potential dynamic relationship of different types of protests and conflicts.

3. Identify any ethnic, nationality, or racial characteristics of participants who were the targets and/or instigators of each protest and conflict.

4. Analyze information on each event's location, size, targets, police presence, arrests, damage or injuries, and the content of claims directed against government authorities, police, and other groups.

This study was designed as an exploratory study to understand fear of gang crime among residents living in an urban area plagued by gangs. During the Summer of 1997, six focus groups were conducted in Santa Ana, California -- two in lower income neighborhoods, two in middle income neighborhoods, and two in upper income neighborhoods. After the focus groups ended, participants were asked to take disposable cameras with them and take pictures of examples of neighborhood factors that prompted them to fear gangs and then mail them back to me in a postage-paid envelope.

The research questions guiding this study were: How do the fear-of-crime perspectives apply to fear of gang crime specifically? When worrying about gang crime, do different people focus primarily on different problems (e.g., some diversity or some disorder), or do the same people think about all of these factors? Findings first showed that all four theoretical perspectives on fear of crime applied to the same people at once, rather than to different people (e.g., some being worried about racial and ethnic differences but others about disorder). Second, findings illustrated specifically how these residents connected the factors into one thought process leading to fear of gangs. Residents in these groups clearly believed that ethnic and cultural diversity, or in this case, recent "illegal" Latino immigrants, brought disorder, which in turn caused community decline and brought gangs. This thought process led to personal fear of gang-related victimization. Their beliefs about these causal connections were primarily influenced by their knowledge and observations that gangs in the area were Latino; by direct observation of area diversity disorder, and decline; and by experience living in their changing neighborhoods over time. In addition, beliefs were fueled by indirect victimization, or knowledge gained primarily through acquaintances such as neighbors and community policing officers.

This collection provides information on 731 married wives of couples living in the Detroit metropolitan area in 1955. Data are provided on the frequency and interaction of respondents with their relatives, as well as their attitudes on family. The collection is a combination of two studies: A DESCRIPTION OF URBAN KINSHIP PATTERNS by Morris Axelrod, and THE URBAN FAMILY by Robert Blood. Data are provided on the frequency of and reasons for large family gatherings, the nature of help that the respondent's family received from relatives, the nature of help that the respondent gave to relatives, and the nature of the relationship with the respondent's relatives on both sides of the family. Other questions explored respondents' family attitudes. They were asked about the division of labor and decision-making processes in their homes, their interactions with their spouses, including communication between them and the causes and methods of handling disagreements, and their attitudes toward marriage in general. In addition, the respondents were asked about expected family size and what they felt the advantages were of having children. Also probed was their use of leisure time. Demographic variables specify age, sex, race, education, marital status, occupation, family income, length of residence in the Detroit area, home ownership, and religious preferences.

The purpose of this project was to measure and estimate the distribution of personal income in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components: payments in kind valued at market prices, agricultural output produced for self-consumption valued at market prices, the value of food and other direct subsidies, and the imputed value of housing services. The rural component of this collection consists of two data files, one in which the individual is the unit of analysis (Part 1) and a second in which the household is the unit of analysis (Part 2). Individual rural respondents reported on their employment status, level of education, Communist Party membership, type of employer (e.g., public, private, or foreign), type of economic sector in which they were employed, occupation, whether they held a second job, retirement status, monthly pension, monthly wage, and other sources of income. Demographic variables include relationship to householder, gender, age, and student status. Rural households reported extensively on the character of the household and residence. Information was elicited on type of terrain surrounding the house, geographic position, type of house, and availability of electricity. Also reported were sources of household income (e.g., farming, industry, government, rents, and interest), taxes paid, value of farm, total amount and type of cultivated land, financial assets and debts, quantity and value of various crops, amount of grain purchased or provided by a collective, use of chemical fertilizers, gasoline, and oil, quantity and value of agricultural machinery, and all household expenditures (e.g., food, fuel, medicine, education, transportation, and electricity). The urban component of this collection also consists of two data files, one in which the individual is the unit of analysis (Part 3) and a second in which the household is the unit of analysis (Part 4). Individual urban respondents reported on their economic status within the household, Communist Party membership, sex, age, nature of employment, and relationship to the household head. Information was collected on all types and sources of income from each member of the household whether working, nonworking, or retired, all revenue received by owners of private or individual enterprises, and all in-kind payments (e.g., food, durable goods, and nondurable goods). Urban households reported total income (including salaries, interest on savings and bonds, dividends, rent, leases, alimony, gifts, and boarding fees), all types and values of food subsidies received, and total debt. Information was also gathered on household accommodations and living conditions, including number of rooms, total living area in square meters, availability and cost of running water, sanitary facilities, heating and air-conditioning equipment, kitchen availability, location of residence, ownership of home, and availability of electricity and telephone. Households reported on all their expenditures including amounts spent on food items such as wheat, rice, edible oils, pork, beef and mutton, poultry, fish and seafood, sugar, and vegetables by means of coupons in state-owned stores and at free market prices. Information was also collected on rents paid by the households, fuel available, type of transportation used, and availability and use of medical and child care.

The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

The purpose of this project was to measure and estimate the distribution of income in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components: payments in kind valued at market prices, agricultural output produced for self-consumption valued at market prices, the value of ration coupons and other direct subsidies, and the imputed value of housing. The rural component of this collection consists of two data files, one in which the individual is the unit of analysis and a second in which the household is the unit of analysis. Individual rural respondents reported on their employment status, level of education, Communist Party membership, type of employer (e.g., public, private, or foreign), type of economic sector in which employed, occupation, whether they held a second job, retirement status, monthly pension, monthly wage, and other sources of income. Demographic variables include relationship to householder, gender, age, and student status. Rural households reported extensively on the character of the household and residence. Information was elicited on type of terrain surrounding the house, geographic position, type of house, and availability of electricity. Also reported were sources of household income (e.g., farming, industry, government, rents, and interest), taxes paid, value of farm, total amount and type of cultivated land, financial assets and debts, quantity and value of various crops (e.g., grains, cotton, flax, sugar, tobacco, fruits and vegetables, tea, seeds, nuts, lumber, livestock and poultry, eggs, fish and shrimp, wool, honey, and silkworm cocoons), amount of grain purchased or provided by a collective, use of chemical fertilizers, gasoline, and oil, quantity and value of agricultural machinery, and all household expenditures (e.g., food, fuel, medicine, education, transportation, and electricity). The urban component of this collection also consists of two data files, one in which the individual is the unit of analysis and a second in which the household is the unit of analysis. Individual urban respondents reported on their economic status within the household, Communist Party membership, sex, age, nature of employment, and relationship to the household head. Information was collected on all types and sources of income from each member of the household whether working, nonworking, or retired, all revenue received by owners of private or individual enterprises, and all in-kind payments (e.g., food and durable and non-durable goods). Urban households reported total income (including salaries, interest on savings and bonds, dividends, rent, leases, alimony, gifts, and boarding fees), all types and values of food rations received, and total debt. Information was also gathered on household accommodations and living conditions, including number of rooms, total living area in square meters, availability and cost of running water, sanitary facilities, heating and air-conditioning equipment, kitchen availability, location of residence, ownership of home, and availability of electricity and telephone. Households reported on all of their expenditures including amounts spent on food items such as wheat, rice, edible oils, pork, beef and mutton, poultry, fish and seafood, sugar, and vegetables by means of both coupons in state-owned stores and at free market prices. Information was also collected on rents paid by the households, fuel available, type of transportation used, and availability and use of medical and child care.

The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

The purpose of this project was to measure and estimate the distribution of personal income and related economic factors in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components. Data were collected through a series of questionnaire-based interviews conducted in rural and urban areas at the end of 2002. There are ten separate datasets. The first four datasets were derived from the urban questionnaire. The first contains data about individuals living in urban areas. The second contains data about urban households. The third contains individual-level economic variables copied from the initial urban interview form. The fourth contains household-level economic variables copied from the initial urban interview form. The fifth dataset contains village-level data, which was obtained by interviewing village leaders. The sixth contains data about individuals living in rural areas. The seventh contains data about rural households, as well as most of the data from a social network questionnaire which was presented to rural households. The eighth contains the rest of the data from the social network questionnaire and is specifically about the activities of rural school-age children. The ninth dataset contains data about individuals who have migrated from rural to urban areas, and the tenth dataset contains data about rural-urban migrant households. Dataset 1 contains 151 variables and 20,632 cases (individual urban household members). Dataset 2 contains 88 variables and 6,835 cases (urban households). Dataset 3 contains 44 variables and 27,818 cases, at least 6,835 of which are empty cases used to separate households in the file. The remaining cases from dataset 3 match those in dataset 1. Dataset 4 contains 212 variables and 6,835 cases, which match those in dataset 2. Dataset 5 contains 259 variables and 961 cases (villages). Dataset 6 contains 84 variables and 37,969 cases (individual rural household members). Dataset 7 contains 449 variables and 9,200 cases (rural households). Dataset 8 contains 38 variables and 8,121 cases (individual school-age children). Dataset 9 contains 76 variables and 5,327 cases (individual rural-urban migrant household members). Dataset 10 contains 129 variables and 2,000 cases (rural-urban migrant households).

The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

This repeated cross-sectional national telephone survey of households was conducted as part of the evaluation of the Robert Wood Johnson Foundation's Urban Health Initiative (UHI), a long-term effort to improve the health, safety, and well-being of children and youth in five economically distressed cities in the United States: Baltimore, MD, Detroit, MI, Oakland, CA, Philadelphia, PA, and Richmond, VA. The UHI Survey of Adults and Youth (SAY) included a variety of questions, asked of both parents and their 10-18 year old children, regarding children's health, safety, perceptions of neighborhoods and schools, family relations, quality of city services, and other issues. SAY surveyed 3 types of households -- households without children, households with children aged 0-9 years, and households with children aged 10-18 years -- in up to 14 geographic areas, including the 5 UHI program cities, 9 comparison cities demographically similar to the UHI cities, the suburban regions of these cities, the most populous 100 United States cities, and the rest of the country. There were 3 waves of SAY fielded during the course of the UHI project: during the 1998-1999, 2001-2002, and 2004-2005 school years.

The vast majority of survey items in SAY are from other national surveys, including the National Longitudinal Survey of Youth, the Youth Risk Behavior Survey, and the National Health Interview Survey. The survey instrument was revised between waves, but about 50 percent of the instrument remained the same across all 3 waves. All adult respondents (both parents and nonparents) were first asked questions about services and general conditions in their city. Parents were then asked additional questions about their children, their children's schools, child-related services in their communities, neighborhood and city conditions, and brief question segments about randomly selected children in various age groups. If one or more 10-18 year olds lived in the household, and if the parent respondent gave permission, up to two 10-18 year olds in the household were then interviewed about their schools, neighborhoods, peer group activities and behaviors, out-of-school time, relations with adults, and other topics.

There is a separate data file for each wave, and each record contains all of the data for a given household, i.e., the data collected from one adult and up to two 10-18 year olds.