This data provides estimates of Internet, broadband, and mobile use at the subnational level from 1997-2014. While the U.S. Bureau of the Census has collected data on Internet use over the years, estimates below the state level did not exist until the introduction of the new American Community Survey in 2013. The datasets here fill these gaps with estimates over time for cities, counties, metropolitan areas and states. They also provide demographic breakdowns for the 2013 and 2014 American Community Survey data, beyond what is available on the census website. The datasets can be used to draw comparisons across geographic locations and across time, to track inequality, change, and the impact of Internet use. Collectively, they show major differences across cities, as well as between urban and rural counties. Time series data indicate the flattening of growth in recent years, leading to the persistence of inequalities across places and demographic groups. Multilevel models are used to estimate the percentage of Internet use across counties, principal cities, and metropolitan areas with the CPS and ACs data. A group of random intercept logistic regressions (a type of multilevel model) are constructed for each of the Internet-related variables, namely, home Internet access, home broadband, mobile Internet, and fully-connected household (with broadband and mobile). Estimates are based on the U.S. Bureau of the Census Current Population Survey data for 1997, 2998, 200, 2001, 2003, 2007, 2009, 2010, 2011, and 2012 and the U.S. Bureau of the Census American Community Survey 2013 and 2014, with estimates for missing years imputed via linear interpolation. Estimates for home Internet access are available for 1997-2014, home broadband use for 2000-2014, and mobile use and fully-connected Internet use for 2011-2014. Data available for different geographies is described below. Current Population Survey Data, 1997-2012: Internet use time series, three-year averages, time series for rate of change in Internet use, three-year averages for the rate of change, and yearly summary statistics are available for approximately 330 counties (with some variation over years), the 50 largest Metropolitan Statistical Areas (MSAs), principal cities in the 50 largest MSAs, and the 50 states. American Community Survey Data, 2013-2014: Using Summary Tables of the American Community Survey available in FactFinder, estimates for home Internet access and home broadband are provided by race, ethnicity, education, age, and employment status for 50 states, 817 counties, 381 MSAs, 383 principal cities in 2013 and 387 principal cities in 2014. Using microdata, estimates are developed for home Internet access, home broadband, mobile Internet, and fully connected households broken down by race, ethnicity, education, age, family income, and language skill. The microdata estimates are available for 50 states, 417 counties, 260 MSAs and 102 principal cities in 2013. See Codebook for a more complete description of the datasets, data sources, survey questions, and methods. See the Center for Policy Informatics at Arizona State University website at policyinformatics.asu.edu/broadband-data-portal/home for visualization (maps and graphs) and for further information about this project.

2013-2023 Virginia Disability Characteristics by Census Tract. Contains estimates and margins of error.

Special data considerations: Large negative values do exist (more detail below) and should be addressed prior to graphing or aggregating the data. A null value in the estimate means there is no data available for the requested geography.

A value of -888,888,888 indicates that the estimate or margin of error is not applicable or not available.

U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table S1810 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

Philadelphia Council District Health Dashboard - Dataset and Codebook

Description

This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.

Background

Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.

Data Sources

• US Census Bureau American Community Survey (ACS) 5-year estimates (2018-2022)
• Open Data Philly (2015-2024)

Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.

Dataset Contents

Files:

• data_v1.csv - Main dataset containing health indicators by Philadelphia City Council District
• codebook_v1.csv - Complete metadata and variable documentation

Methodology

• Population-weighted aggregation for demographic/socioeconomic variables
• Area-weighted aggregation for environmental variables
• Count aggregation for incident data
• City averages calculated as population-weighted across districts

Geographic Coverage

• Unit: Philadelphia City Council Districts (n=10)
• Period: 2018-2022 (ACS), 2015-2024 (Open Data Philly)

Applications

Supports policy analysis, community advocacy, academic research, and public health planning at the district level.

Contact

Authors

Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl

Funding

Transform Academia for Equity grant from Robert Wood Johnson Foundation

Keywords

Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis

Abstract (en): These data are being released as a preliminary version to facilitate early access to the study for research purposes. This collection has not been fully processed by ICPSR at this time, and data are released in the format provided by the principal investigators. As the study is processed and given enhanced features by ICPSR in the future, users will be able to download the updated versions of the study. Please report any data errors or problems to user support, and we will work with you to resolve any data-related issues. The American National Election Study (ANES): 2016 Pilot Study sought to test new instrumentation under consideration for potential inclusion in the ANES 2016 Time Series Study, as well as future ANES studies. Much of the content is based on proposals from the ANES user community submitted through the Online Commons page, found on the ANES home page. The survey included questions about preferences in the presidential primary, stereotyping, the economy, discrimination, race and racial consciousness, police use of force, and numerous policy issues, such as immigration law, health insurance, and federal spending. It was conducted on the Internet using the YouGov panel, an international market research firm that administers polls that collect information about politics, public affairs, products, brands, as well as other topics of general interest. The purpose of this study was to test questions for inclusion on the ANES 2016 Time Series, as well as other future ANES studies. Respondents were selected from the YouGov panel survey administered on the Internet. Response to these surveys are on a volunteer basis. The data are not weighted. This collection contains two weight variables, WEIGHT and WEIGHT_SPSS. The variable WEIGHT is the weight for analysis that is intended to generalize to the population. The variable WEIGHT_SPSS is the weight recommended to be used by SPSS users not using the Complex Samples procedures and will account for the smaller effective sample size. For more information on weights, please see the ANES 2016 Pilot Study Codebook and User Guide found within the zip package, as well as visit the ANES Data Center Web site. United States citizens age 18 or older. Smallest Geographic Unit: state The study was conducted on the Internet using the YouGov panel. The YouGov panel consists of a large and diverse set of over a million respondents who have volunteered to complete surveys online and who regularly receive invitations to do so. They receive points usually worth about 21 to 50 cents for each survey they complete. The points are redeemable for various gift cards, a YouGov t-shirt, or UNICEF a donation. A respondent has to complete about 40 surveys to be eligible for any reward. Respondents were selected from the YouGov panel by sample matching. Matching is intended to make the individuals who complete the survey represent the population on the variables used for matching. Respondents were matched to United States citizens in the 2010 American Community Survey (ACS) sample by gender, age, race, and education, and to the November 2010 Current Population Survey (CPS) for voter registration and turnout status, and to the 2007 Pew Religious Life Survey on interest in politics and party identification. 1,200 individuals from the YouGov panel were selected for the ANES Pilot Study to match the target population defined by the ACS, CPS, and Pew surveys. After data collection the sample was weighted by YouGov using propensity scores using a logistic regression with age, gender, race/ethnicity, years of education, region, and party identification included in the model. For more information on sampling, please see the ANES 2016 Pilot Study Codebook and User Guide found within the zip package, as well as visit the ANES Data Center Web site. web-based surveyThis collection has not been fully processed by ICPSR. All of the files are available in one zipped package. This collection will be fully curated at a later date. For more information on the ANES 2016 Pilot Study, please refer to the ANES Data Center Web site.

Abstract (en): The purpose of this data collection was to provide an appropriate theoretical and empirical approach to concepts, measures, and methods in the study of Black Americans. Developed with input from social scientists, students, and a national advisory panel of Black scholars, the survey investigates neighborhood-community integration, services, crime and community contact, the role of religion and the church, physical and mental health, self-esteem, life satisfaction, employment, the effects of chronic unemployment, the effects of race on the job, interaction with family and friends, racial attitudes, race identity, group stereotypes, and race ideology. Demographic variables include education, marital status, income, employment status, occupation, and political behavior and affiliation. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Black United States citizens 18 years of age or older. National multistage probability sample. The sample is self-weighting. Every Black American household in the continental United States had an equal probability of being selected. Wave 1 was administered to 2,107 respondents, Wave 2 to 951 respondents (including 935 from Wave 1), Wave 3 to 793 respondents (including 779 from Wave 2), and Wave 4 to 659 respondents (including 1 from Wave 1, 28 from Wave 2, and 623 from Wave 3). 1997-11-13 The SAS and SPSS data definition statements have been reissued, and the codebook is being released as a PDF file. PDF questionnaires for Waves 1-4 also have been added to the collection. The Crosswave Variable Listing is now machine-readable and is part of the PDF codebook. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. National Institute of Mental Health. (1) Data for Wave 1 of this study supersede the data released in NATIONAL SURVEY OF BLACK AMERICANS, 1979-1980 (ICPSR 8512). (2) Users should note that data for the "state and county" codes (Variables 1405, 1407, and 1410) were entered in COUNTY/STATE order and not STATE/COUNTY order, i.e., the first three digits are the county code and the last two digits are the state code. This is the reverse of how Note 3 of the codebook describes the interpretation of these variables. (3) Variables for Wave 2 begin at V3001, Wave 3 begins at V4001, and Wave 4 begins at V5001. (4) The codebook and questionnaires are provided as Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

Philadelphia Council District Health Dashboard - Dataset and Codebook

Description

This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.

Background

Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.

Data Sources

• US Census Bureau American Community Survey (ACS) 5-year estimates (2018-2022)
• Open Data Philly (2015-2024)

Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.

Dataset Contents

Files:

• data_v1_1.csv - Main dataset containing health indicators by Philadelphia City Council District
• codebook_v1_1.csv - Complete metadata and variable documentation

Methodology

• Population-weighted aggregation for demographic/socioeconomic variables
• Area-weighted aggregation for environmental variables
• Count aggregation for incident data
• City averages calculated as population-weighted across districts

Geographic Coverage

• Unit: Philadelphia City Council Districts (n=10)
• Period: 2018-2022 (ACS), 2015-2024 (Open Data Philly)

Applications

Supports policy analysis, community advocacy, academic research, and public health planning at the district level.

Contact

Authors

Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl

Funding

Transform Academia for Equity grant from Robert Wood Johnson Foundation

Keywords

Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis

This file contains data from 1968 relating to the daily traffic flow through federally managed canals in Canada (Rideau, Trent, Carillon, Sainte-Anne de Bellevue, Saint-Ours Chambly, St. Peters and Canso). These datasets have been converted from their legacy file structures and encoding schemes so they can be used by contemporary computers that are based upon the ASCII character-encoding scheme. Each dataset will require specialized software such as a statistical tool, to interpret and analyze the content in each file. The attached codebook describes the file’s structure and defines the variables contained in each field. Each code book is a compilation of the summary description of the dataset as provided by the creating department. As such, it is available in English only.

This file contains data collected in 1977 on motel users visiting Gros Morne National Park. These datasets have been converted from their legacy file structures and encoding schemes so they can be used by contemporary computers that are based upon the ASCII character-encoding scheme. Each dataset will require specialized software such as a statistical tool, to interpret and analyze the content in each file. The attached codebook describes the file’s structure and defines the variables contained in each field. Each code book is a compilation of the summary description of the dataset as provided by the creating department. As such, it is available in English only.

Abstract (en): The purpose of this study was to collect extensive information on the sexual experiences and other social, demographic, attitudinal, and health-related characteristics of adults in the United States. The survey collected information on sexual practices with spouses/cohabitants and other sexual partners and collected background information about the partners. Major areas of investigation include sexual experiences such as number of sexual partners in given time periods, frequency of particular practices, and timing of various sexual events. The data cover childhood and adolescence, as well as adulthood. Other topics in the survey relate to sexual victimization, marriage and cohabitation, and fertility. Respondents were also queried about their physical health, including history of sexually transmitted diseases. Respondents' attitudes toward premarital sex, the appeal of particular practices such as oral sex, and levels of satisfaction with particular sexual relationships were also studied. Demographic items include race, education, political and religious affiliation, income, and occupation. Noninstitutionalized United States population aged 18-59 able to complete an interview in English. Multistage area probability sample designed to give each household an equal probability of inclusion. Two samples were obtained: a cross-sectional sample (3,159 cases), and an oversample (273 cases) intended to increase the number of Blacks and Hispanics in the study. Overall response rate was 78.6 percent of the 4,369 eligible respondents selected for inclusion in the study. 2008-04-17 Duplicate value labels were removed from the SPSS setup. Three incorrect and superfluous value labels for variable FIRSTVI were removed from the SPSS setup, codebook, and frequencies. ICPSR produced a Stata setup and SAS, SPSS, Stata, and tab-delimited versions of the data. In addition, the codebook and frequencies were converted to PDF format. Funding insitution(s): Ford Foundation. Robert Wood Johnson Foundation (18403). Henry J. Kaiser Family Foundation. Rockefeller Foundation. Andrew W. Mellon Foundation. John D. and Catherine T. MacArthur Foundation. New York Community Trust. American Foundation for AIDS Research. personal interviews and self-administered questionnaires

This file contains data from 1969 relating to the daily traffic flow through federally managed canals in Canada (Rideau, Trent, Carillon, Sainte-Anne de Bellevue, Saint-Ours Chambly, St. Peters and Canso). These datasets have been converted from their legacy file structures and encoding schemes so they can be used by contemporary computers that are based upon the ASCII character-encoding scheme. Each dataset will require specialized software such as a statistical tool, to interpret and analyze the content in each file. The attached codebook describes the file’s structure and defines the variables contained in each field. Each code book is a compilation of the summary description of the dataset as provided by the creating department. As such, it is available in English only.

This file contains data from a 1971 survey undertaken to gather information on non-resident tourist parties exiting Nova Scotia.

These datasets have been converted from their legacy file structures and encoding schemes so they can be used by contemporary computers that are based upon the ASCII character-encoding scheme. Each dataset will require specialized software such as a statistical tool, to interpret and analyze the content in each file. The attached codebook describes the file’s structure and defines the variables contained in each field. Each code book is a compilation of the summary description of the dataset as provided by the creating department. As such, it is available in English only.