This data collection contains the basic information about all counties in the coterminous United States needed for mapping county-based data. It provides an interface between ICPSR datasets and the mapping programs SAS/GRAPH, SURFACE II, and SYMAP. Cloropleth and isopleth maps can be produced by match-merging this dataset with any other dataset (special facilities exist for ICPSR datasets) and running the merged data against a cartographic program. Isopleth mapping programs, using the latitude and longitude coordinates provided for each county seat, can produce maps of ICPSR data. Cloropleth mapping of county-level data can be accomplished after merging by running the merged dataset through SAS/GRAPH. The variables provide state Federal Information Processing (FIPS) codes, county FIPS codes, county names/county seat names, the month, day, and year in which each county was created, the latitude and longitude of county seats, as well as the ICPSR state and county codes.

The County Longitudinal Template is a tool that enables researchers to allow for temporal changes in the geographic boundaries of counties in the United States. These data provide a decade-by-decade account of the administrative status of each county, starting in 1990 and tracing each census period back through 1840. The first four variables are the county name, ICPSR state code, FIPS code, and ICPSR county code. These four variables allow the researcher to select the counties for the state in question. The next 16 variables are ID variables for each census year, 1990 back to 1840. The last 13 variables are boundary change flags for each census year from 1960 to 1840.

This dataset was created to facilitate the conversion of Uniform Crime Reporting (UCR) Program state and county codes to Federal Information Processing Standards (FIPS) state and county codes. The four UCR agency-level data files archived at ICPSR in Uniform Crime Reporting Program Data: United States contain UCR state and county codes as geographic identifiers. Researchers who wish to use these data with other sources, such as Census data, may want to convert these UCR codes to FIPS codes in order to link the different data sources. This file was created to facilitate this linkage. It contains state abbreviations, UCR state and county codes, FIPS state and county codes, and county names for all counties present in the UCR data files since 1990. These same FIPS codes were used to create the UCR County-Level Detailed Arrest and Offense files from 1990-1996.

The U.S. Census Bureau TIGER/Line® files in this data collection were originally distributed by the Inter-university Consortium for Political and Social Research (ICPSR) through its TIGER/Line file web site, which was decommissioned in 2018 (archived version: https://web.archive.org/web/20090924181858/http://www.icpsr.umich.edu/TIGER/index.html). There, users could download various versions of the U.S. Census Bureau's TIGER (Topologically Integrated Geographic Encoding and Referencing) database. The TIGER/Line files do not include demographic data, but they do contain geographic information that can be linked to the Census Bureau’s demographic data. Due to file number limitations in openICPSR, the original data collections have been bundled into single zip packages. A single TIGER_directory.txt file listing the original files and the original directory structure is included with the root directory. Documentation files are also included as standalone subdirectories in each collection so users do not need to download entire zip bundles to view documentation. The TIGER/Line data are stored in compressed format in subdirectories by state name. There is one TIGER/Line file (in a compressed format) for each county or county equivalent. The file names consist of TGR + the 2-digit state FIPS (Federal Information Processing Standards) code + the 3-digit county FIPS code (i.e. TGR01031.ZIP for Coffee County, Alabama). Each state folder contains individual county files.The individual county files include one file for each record type included for that county with the following name convention: tgr01031.rt1. The convention follows the order described above with each file having a suffix which includes 'rt' (record type) followed by its designation (in this case record type 1). Each county file also contains its own metadata record.If present, documentation files for the TIGER/Line data are stored in a directory named '0docs' which is located in the 'Parent Directory'. This directory appears at the top of the index of state subdirectories for each edition of the TIGER/Line files. The documentation includes a complete list of FIPS state and county codes.

This aggregate data collection provides the April 1, 1980, total corrected census population figures and the July 1, 1982, population estimates for all counties in the United States. The five variables are Federal Information Processing Standard (FIPS) state code, FIPS county code, county name, total corrected population count for April 1, 1980, and July 1, 1982, population estimate.

The Consolidated Federal Funds Report CFFR data, obtained from federal government agencies, cover federal expenditures or obligations for the following categories: grants, salaries and wages, procurement contracts, direct payments for individuals, other direct payments, direct loans, guaranteed or insured loans, and insurance. Information available in the CFFR Data File (Part 1) includes FIPS geographic code, state abbreviated name, county name, place name, population, congressional district code, program identification code, object/assistance type code, agency code, and amount in whole dollars. For each unique FIPS code all programs are listed, and for each program all records with different object categories are listed. The CFFR Program Identification File (Part 2) contains program identification codes and their respective program titles. The CFFR Federal Agency File (Part 3) contains all four-digit (FIPS-95) codes identifying specific agencies. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03147.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The Consolidated Federal Funds Report CFFR data, obtained from federal government agencies, cover federal expenditures or obligations for the following categories: direct payments for retirement and disability, other direct payments, grants, procurement contracts, salaries and wages, direct loans, guaranteed or insured loans, and insurance. Information available in the CFFR Data File (Part 1) includes FIPS geographic code, state abbreviated name, county name, place name, population, congressional district code, program identification code, object/assistance type code, agency code, and amount in whole dollars. For each unique FIPS code all programs are listed, and for each program all records with different object categories are listed. The CFFR Program Identification File (Part 2) contains program identification codes and their respective program titles. The CFFR Federal Agency File (Part 3) contains four-digit (FIPS-95) codes identifying specific agencies. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03150.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The Consolidated Federal Funds Report (CFFR) data, obtained from federal government agencies, cover federal expenditures or obligations for the following categories: direct payments for retirement and disability, other direct payments, grants, procurement contracts, salaries and wages, direct loans, guaranteed or insured loans, and insurance. Information available in the CFFR Data File (Part 1) includes FIPS geographic code, state abbreviated name, county name, place name, population, congressional district code, program identification code, object/assistance type code, agency code, and amount in whole dollars. For each unique FIPS code all programs are listed, and for each program all records with different object categories are listed. The CFFR Program Identification File (Part 2) contains program identification codes and their respective program titles. The CFFR Federal Agency File (Part 3) contains four-digit (FIPS-95) codes identifying specific agencies. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03179.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The IPUMS Contextual Determinants of Health (CDOH) data series includes measures of disparities, policies, and counts by state or county for historically marginalized populations in the United States including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons as well as women. The IPUMS CDOH data are made available through ICPSR/DSDR for merging with the National Couples' Health and Time Study (NCHAT), United States, 2020-2021 (ICPSR 38417) by approved restricted data researchers. All other researchers can access the IPUMS CDOH data via the IPUMS CDOH website. Unlike other IPUMS products, the CDOH data are organized into multiple categories related to Race and Ethnicity, Sexual and Gender Minority, Gender, and Politics. The CDOH measures were created from a wide variety of data sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and Myers Abortion Facility Database). Measures are currently available for states or counties from approximately 2015 to 2020. The Gender measures in this release include the state-level earnings ratio, which compares the median earnings of full-time wage and salary workers identifying as male to the median earnings of full-time wage and salary workers identifying as female in a given state in a given year. To work with the IPUMS CDOH data, researchers will need to first merge the NCHAT data to DS1 (MATCH ID and State FIPS Data). This merged file can then be linked to the IPUMS CDOH datafile (DS2) using the STATEFIPS variable.

This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines. The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, gender, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee.

The Geographic Names Information System (GNIS) was developed by the United States Geological Survey (USGS) to meet major national needs regarding geographic names and their standardization and dissemination. This dataset consists of standard report files written from the National Geographic Names Data Base, one of five data bases maintained in the GNIS. A standard format data file for each of the fifty States, the District of Columbia and the four Insular Territories of the United States is included, as well as a file that provides a Cross-Reference to USGS 7.5 x 7.5 minute quadrangle maps. The records in the data files are organized in an alphabetized listing of all of the names in a particular state or territory. The other variables available in the dataset include: Federal Information Processing Standard (FIPS) state/county codes, Geographic Coordinates-- latitude and longitude to degrees, minutes, and seconds followed by a single digit alpha directional character, and a GNIS Map Code that can be used with the Cross-Reference file to provide the name of the 7.5 x 7.5 minute quadrangle map that contains that geographic feature.

This dataset contains records for each public elementary and secondary education agency in the 50 states, District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), as reported to the National Center for Education Statistics by the state education agencies. Each record provides state and federal identification numbers, agency's name, address, and telephone number, county name and FIPS code, agency type code, supervisory union number, grade span, number of schools operated by the agency, counts of students in selected categories of residency, and other codes for selected characteristics of the agency.

This data collection contains FIPS codes for state, county, county subdivision, and place, along with the 1990 Census tract number for each side of the street for the urban cores of 550 counties in the United States. Street names, including prefix and/or suffix direction (north, southeast, etc.) and street type (avenue, lane, etc.) are provided, as well as the address range for that portion of the street located within a particular Census tract and the corresponding Census tract number. The FIPS county subdivision and place codes can be used to determine the correct Census tract number when streets with identical names and ranges exist in different parts of the same county. Contiguous block segments that have consecutive address ranges along a street and that have the same geographic codes (state, county, Census tract, county subdivision, and place) have been collapsed together and are represented by a single record with a single address range.

This study represents one of four research projects on service delivery systems in metropolitan areas, covering fire protection (DECISION-RELATED RESEARCH ON THE ORGANIZATION OF SERVICE DELIVERY SYSTEMS IN METROPOLITAN AREAS: FIRE PROTECTION [ICPSR 7409]), public health (DECISION-RELATED RESEARCH ON THE ORGANIZATION OF SERVICE DELIVERY SYSTEMS IN METROPOLITAN AREAS: PUBLIC HEALTH [ICPSR 7374]), solid waste management (DECISION-RELATED RESEARCH ON THE ORGANIZATION OF SERVICE DELIVERY SYSTEMS IN METROPOLITAN AREAS: SOLID WASTE MANAGEMENT [ICPSR 7487]), and police protection (the present study). All four projects used a common unit of analysis, namely all 200 Standard Metropolitan Statistical Areas (SMSAs) that, according to the 1970 Census, had a population of less than 1,500,000 and were entirely located within a single state. In each project, a limited amount of information was collected for all 200 SMSAs. More extensive data were gathered within independently drawn samples of these SMSAs, for all local geographical units and each administrative jurisdiction or agency in the service delivery areas. Two standardized systems of geocoding -- the Federal Information Processing Standard (FIPS) codes and the Office of Revenue Sharing (ORS) codes -- were used, so that data from various sources could be combined. The use of these two coding schemes also allows users to combine data from two or more of the research projects conducted in conjunction with the present one, or to add data from a wide variety of public data files. The present study used five major clusters of variables to investigate the delivery of police services: service conditions, the legal structure, organizational arrangements, manpower levels, and expenditure levels. Information about specific services such as patrol, traffic control, criminal investigation, radio communications, adult pre-trial detention, entry-level training, and crime laboratory analysis was collected at the local jurisdiction level in a random sample of 80 SMSAs. Part 1 summarizes in matrix form the relationships between all consumers and producers for each type of service in a given SMSA. Part 2 provides data about 1,885 consuming units, or service areas, defined as mutually exclusive geographical divisions of each SMSA that received police services. Part 3 contains information for 1,761 police agencies, defined as service producers, with functions and duties that may overlap several jurisdictions.

The Consolidated Federal Funds Report CFFR data, obtained from federal government agencies, cover federal expenditures or obligations for the following categories: grants, salaries and wages, procurement contracts, direct payments for individuals, other direct payments, direct loans, guaranteed or insured loans, and insurance. Information available in the CFFR Data File (Part 1) includes FIPS geographic code, state abbreviated name, county name, place name, population, congressional district code, program identification code, object/assistance type code, agency code, and amount in whole dollars. For each unique FIPS code all programs are listed, and for each program all records with different object categories are listed. The CFFR Program Identification File (Part 2) contains program identification codes and their respective program titles. The CFFR Federal Agency File (Part 3) contains all four-digit (FIPS-95) codes identifying specific agencies. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03148.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Abstract (en): This dataset contains records for each public secondary and elementary education agency in the United States and its outlying areas (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1985-1986. Reporting agencies serve instructional levels from pre-kindergarten through grade 12, or the equivalent span of instruction in ungraded or special education districts. Regional Educational Service Agencies, supervisory unions, and county superintendents are also represented. Variables include state and federal ID numbers, agency name, address, city, and ZIP code, FIPS county and out-of-state indicators, instructional operating status, agency type, grade span, metropolitan statistical area (MSA) ID and status, and board of control selection code. 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: Checked for undocumented or out-of-range codes.. All public elementary and secondary education agencies in operation during 1985-1986 in the 50 states, the District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). The codebook is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

Abstract (en): This poll, fielded December 10-13 2009, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked to give their opinions of President Barack Obama and his handling of the presidency, the federal budget deficit, health care, the situation in Afghanistan, unemployment, global warming, and the economy. Respondents were asked whether the Obama Administration or the Republicans in Congress could be trusted to do a better job handling the economy, health care reform, the situation in Afghanistan and energy policy. Several questions addressed health care including whether respondents supported the health care system being developed by Congress and the Obama Administration, whether they believed health care reform would increase the federal budget deficit, whether government should lower the age requirement for Medicare, and what the respondents' plan preference was for people who are not insured. Noneconomic questions focused on the role of the United States in Afghanistan, confidence in the Obama Administration in the handling of Afghanistan and the Taliban, and the environment. Other questions focused on the topics of health care in the United States, job availability, personal finances as well as opinions on professional golfer Tiger Woods. Demographic variables include sex, age, race, political political philosophy, party affiliation, education level, religious preference, household income, and whether respondents considered themselves to be a born-again Christian. The data contain a weight variable (WEIGHT) that should be used in analyzing the data. The weights were derived using demographic information from the Census to adjust for sampling and nonsampling deviations from population values. Until 2008 ABC News used a cell-based weighting system in which respondents were classified into one of 48 or 32 cells (depending on sample size) based on their age, race, sex, and education; weights were assigned so the proportion in each cell matched the Census Bureau's most recent Current Population Survey. To achieve greater consistency and reduce the chance of large weights, ABC News in 2007 tested and evaluated iterative weighting, commonly known as raking or rim weighting, in which the sample is weighted sequentially to Census targets one variable at a time, continuing until the optimum distribution across variables (again, age, race, sex, and education) is achieved. ABC News adopted rim weighting in January 2008. Weights are capped at lows of 0.2 and highs of 6. 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: Standardized missing values.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Persons aged 18 and over living in households with telephones in the contiguous 48 United States. Households were selected by random-digit dialing. Within households, the respondent selected was the youngest adult living in the household who was home at the time of the interview. Please refer to the codebook documentation for more information on sampling. computer-assisted telephone interview (CATI)The data available for download are not weighted and users will need to weight the data prior to analysis.The variables PCTBLACK, PCTASIAN, PCTHISP, MSAFLAG, CSA, CBSA, METRODIV, NIELSMKT, BLOCKCNT, STATE, CONGDIST, and ZIP were converted from character variables to numeric.To preserve respondent confidentiality, codes for the variables FIPS (FIPS County) and ZIP (ZIP Code) have been replaced with blank codes.System-missing values were recoded to -1.The CASEID variable was created for use with online analysis.Several codes in the variable CBSA contain diacritical marks.Value labels for unknown codes were added in variables MSA, CSA, CBSA, COLLEDUC, and METRODIV. The data collection was produced by Taylor Nelson Sofres of Horsham, PA. Original reports using these data may be found via the ABC News Polling Unit Web site and via the Washington Post Opinion Surveys and Polls Web site.

The CFFR covers federal expenditures or obligations for the following categories: grants, salaries and wages, procurement contracts, direct payments for individuals, other direct payments, direct loans, guaranteed or insured loans, and insurance. Information available in the CFFR Data File includes the government identification code, program identification code, object/assistance type code, amount in whole dollars, and FIPS code. For each unique government unit code all programs are listed, and for each program all records with different object categories are listed. The Geographic Reference File contains the names and governmental unit codes for all state, county, and subcounty areas in the country. In addition, the file contains associated geographic codes (FIPS, GSA, MSA, and Census Bureau place codes), the 1988 population, and the congressional districts serving each government unit. The Program Identification File contains program identification codes and their respective program titles. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09718.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Researchers have long been able to analyze crime and law enforcement data at the individual agency level (see UNIFORM CRIME REPORTING PROGRAM DATA: [UNITED STATES] [ICPSR 9028]) and at the county level (see, for example, UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1997 [ICPSR 2764]). However, analyzing crime data at the intermediate level, the city or place, has been difficult. To facilitate the creation and analysis of place-level data, the Bureau of Justice Statistics (BJS) and the National Archive of Criminal Justice Data (NACJD) created the Law Enforcement Agency Identifiers Crosswalk. The crosswalk file was designed to provide geographic and other identification information for each record included in either the Federal Bureau of Investigation's Uniform Crime Reports (UCR) files or BJS's Directory of Law Enforcement Agencies. The main variables for each record are the UCR originating agency identifier number, agency name, mailing address, Census Bureau's government identification number, UCR state and county codes, and Federal Information Processing Standards (FIPS) state, county, and place codes. These variables make it possible for researchers to take police agency-level data, combine them with Bureau of the Census and BJS data, and perform place-level, jurisdiction-level, and government-level analyses.

Abstract (en): This special topic poll, fielded October 16-20, 2008, is part of a continuing series of monthly surveys that solicit public opinion on a range of political and social issues. The topic of this survey was government performance in the state of Maryland, slot machines, and the budget deficit. Residents of Maryland were asked about the job performance of Governor Martin O'Malley and whether they approved of the way he is handling his job as governor. Respondents identified the most important issues facing the state of Maryland, whether the state was moving in the right direction, and rated the condition of the state economy. Respondents were also asked what the chances were that they would vote in the upcoming presidential election. Several questions asked for respondents' opinions on Question Two on the state ballot: the constitutional amendment about slot machines in Maryland. Respondents were asked whether they approved of having slot machines in Maryland, what was the main reason they either approved or disapproved of slot machines, and if the slots plan passed, they thought it would help the state's budget situation. Respondents were queried on their thoughts of the direction of the nation's economy as well as their own family's financial situation. Respondents were asked about their impressions of the candidates for Maryland governor in 2010, and who they would vote for in the election. Demographic variables include sex, age, race, household income, education level, voter registration status, political party affiliation, political philosophy, religious preference, religiosity, union membership, whether respondent is a born-again Christian, and the presence of children under age 18 living at the residence. The data contain a weight variable (WEIGHT) that should be used in analyzing the data. The data were weighted using demographic information from the Census to adjust for sampling and non-sampling deviations from population values. Respondents customarily were classified into one of 48 cells based on age, race, sex, and education. Weights were assigned so the proportion in each of these 48 cells matched the actual population proportion according to the Census Bureau's most recent Current Population Survey. 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: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Persons aged 18 and over living in households with telephones in the state of Maryland. Households were selected by random-digit dialing. Within households, the respondent selected was the adult living in the household who last had a birthday and who was home at the time of the interview. Please refer to the codebook documentation for more information on sampling. 2010-11-09 Updated codebook. computer-assisted telephone interview (CATI)The data available for download are not weighted and users will need to weight the data prior to analysis.The variables PCTBLACK, PCTASIAN, PCTHISP, MSAFLAG, CSA, CBSA, METRODIV, NIELSMKT, BLOCKCNT, and ZIP were converted from character variables to numeric.To preserve respondent confidentiality, codes for the variables FIPS (FIPS County) and ZIP (ZIP Code) have been replaced with blank codes.System-missing values were recoded to -1.The CASEID variable was created for use with online analysis. The data collection was produced by Taylor Nelson Sofres of Horsham, PA. Original reports using these data may be found via the ABC News Polling Unit Web site and via the Washington Post Opinion Surveys and Polls Web site.