The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was released on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics will be released in the summer of 2011. The data in these particular RGIS Clearinghouse tables are for all Census Tracts in New Mexico. There are two data tables. One provides total counts by major race groups and by Hispanic ethnicity, while the other provides proportions of the total population for these same groups. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

Abstract

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

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Documentation

Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier. In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The historic US 1910 census data was collected in April 1910. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

Section 2

This dataset was created on 2020-01-10 23:47:27.924 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1910 households: The Integrated Public Use Microdata Series (IPUMS) Complete Count Data are historic individual and household census records and are a unique source for research on social and economic change.

IPUMS 1910 persons: This dataset includes all individuals from the 1910 US census.

In Austria a population census takes place every 10 years; this census contains a program of important statistical data on population and employment. They roughly corresponds to the information in the Mikrozensus standard survey but are more detailed (for instance with question on the connection of the place of residence and the workplace, questions on education, confession, etc.) Population and Mikrozensus are closely linked which the name already implies: Mikrozensus means a small-scale population census; this should demonstrate that what the population census reports only every 10 years, the Mikrozensus reports through the method of ongoing sampling. These ongoing sample are also collected in the years of the population census. The Mikrozensus however is far more detailed than the survey program of the population census because the Mikrozensus special surveys offer the possibility of asking questions which are fare beyond the scope of the population census. This complementary function of Mikrozensus and population census becomes especially obvious in the June-survey: certain questions that could not be posed in the population census due to the limited program were answered in the Mikrozensus via sampling. These were the topics: questions on the social stratification of the population questions on fertility and succession of birth questions on the silent Human Resources Probability: Stratified: Proportional Face-to-face interview

Abstract copyright UK Data Service and data collection copyright owner.

The objectives of the project were :
to prepare the case for the ESRC/JISC purchase of 2001 Census datasets and to prepare the case for a Census Programme and suggest directions it might take;
to prepare options for ESRC/JISC on the dissemination of the datasets;
to prepare proposals to the Census Offices on Census questions, methods and products;
to prepare proposals to the Census Offices on collaborative ventures;
to advise on a strategy for negotiations with the Census Offices.

A similar survey, for the 1991 Census, was conducted in 1987 by Marsh, C. et al : the data from this study are held at the Data Archive under SN:2460.
Main Topics:

The dataset contains the responses of 140 academic users of census data on their views about the 2001 Census of population. Questions were asked under the following four themes :
1. Topics and questions proposed for the 2001 Census.

1. Proposed changes in concepts for the 2001 Census.
   
2. Proposed changes in outputs for the 2001 Census : Area Statistics, Samples of Anonymised Records (SARS), Migration Statistics, Workplace Statistics, the ONS Longitudinal Study - inclusion of the 2001 Census, boundary data, look up tables, flexible outputs from the 2001 Census.
   
3. ESRC/JISC Census Programme services : registration procedures, help with census data, documentation and training, methods of access, software for extraction and analysis of census data, shape of the ESRC/JISC Census Programme after 2001.
   
   Measurement Scales
   The main scale used was a five-part categorisation of usefulness/importance for the respondent's research :
   essential; highly desirable; of interest; very low priority; not of interest.

Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2015 American Community Survey (ACS). Question 45 asks: “What kind of work was this person doing?” Question 46 asks: “What were this person’s most important activities or duties?” These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person’s job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job. These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development, and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

This dataset contains model-based census tract level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 27 measures at the census tract level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

About this dataset

Context

The dataset tabulates the population of College Springs by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of College Springs across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 56.68% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the College Springs is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of College Springs total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for College Springs Population by Race & Ethnicity. You can refer the same here

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in these particular RGIS Clearinghouse tables are for New Mexico and all census tracts in the state. There are two data tables in this file. Table DC10_00586 shows the number of households by the following categories--total households; total family households; husband-wife family households; total other family households; male householder, no wife present; female householder, no husband present; total nonfamily households; nonfamily households with householder living along; and finally, nonfamily households with householder not living alone. Table DC10_00587 shows percent distribution of households for each of these same categories. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in these particular RGIS Clearinghouse tables are for New Mexico and all census tracts. There are two data tables in this file. Table DC10_00215 shows counts of males by eighteen 5-year age groups. Table DC10_00216 shows percent distribution of males by eighteen 5-year age groups. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

The Congressional District Summary File contains the data compiled from the questions asked of all people and about every housing unit in the 2010 Census. The Congressional District Summary File (113th Congress) (CD113) contains the data compiled from the questions asked of all people and about every housing unit in the 2010 Census. Population items include sex, age, race, Hispanic or Latino origin, household relationship, household type, household size, family type, family size, and group quarters. Housing items include occupancy status, vacancy status, and tenure (whether a housing unit is owner-occupied or renter-occupied). The file contains subject content identical to that shown in the 2010 Census Summary File 1.

Population size estimates of people who identify with particular race(s) in Alaskan Communities/Places and aggregation at Boroughs - CDAs and State level for recent 5-year American Community Survey (ACS) intervals. The 5-year interval data sets are published approximately 1/2 a period later than the End Year listed - for instance the interval ending in 2019 is published in mid-2021.Source: US Census Bureau, American Community SurveyThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: US Census Bureau - Why We Ask About RaceUSE CONSTRAINTS: The Alaska Department of Commerce, Community, and Economic Development (DCCED) provides the data in this application as a service to the public. DCCED makes no warranty, representation, or guarantee as to the content, accuracy, timeliness, or completeness of any of the data provided on this site. DCCED shall not be liable to the user for damages of any kind arising out of the use of data or information provided. DCCED is not the authoritative source for American Community Survey data, and any data or information provided by DCCED is provided "as is". Data or information provided by DCCED shall be used and relied upon only at the user's sole risk. For information about the American Community Survey, click here.

The following data were used for the Department of Water Resources' (DWR) Disadvantaged Communities (DAC) Mapping Tool: https://gis.water.ca.gov/app/dacs/. The data source is from the US Census (American Community Survey), that may include attribute table additions by DWR. The DAC Mapping Tool was designed, and the related datasets made publicly available, to assist in the evaluation of DACs throughout the state, as may relate to the various Grant Programs within the Financial Assistance Branch (FAB) at DWR. The definition of DAC may vary by grant program (within FAB, DWR or grant programs of other public agencies). As such, users should be familiar with the specific requirements for meeting DAC status, based on the particular grant solicitation/program of interest.

For more information related to the Grant Programs within the Financial Assistance Branch, visit: https://water.ca.gov/Work-With-Us/Grants-And-Loans/IRWM-Grant-Programs https://water.ca.gov/Work-With-Us/Grants-And-Loans/Sustainable-Groundwater

Additional questions or requests for information related to the DAC datasets (or the DAC Mapping Tool) should be directed to: dwr_irwm@water.ca.gov.

For more information on DWR's FAB programs, please visit: https://water.ca.gov/Work-With-Us/Grants-And-Loans/IRWM-Grant-Programs

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Foreign born excludes people born outside the United States to a parent who is a U.S. citizen..Tables for Workplace Geography are only available for States; Counties; Places; County Subdivisions in selected states (CT, ME, MA, MI, MN, NH, NJ, NY, PA, RI, VT, WI); Combined Statistical Areas; Metropolitan and Micropolitan Statistical Areas, and their associated Metropolitan Divisions and Principal Cities. Tables B08601, B08602, B08603, and B08604 are also available for Place parts and County Subdivision parts for the 5-year ACS datasets..Workers include members of the Armed Forces and civilians who were at work last week..Industry titles and their 4-digit codes are based on the 2022 North American Industry Classification System. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in...

This dataset contains model-based Census tract level estimates for the PLACES project by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. It represents a first-of-its kind effort to release information uniformly on this large scale. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. This data only covers the health of adults (people 18 and over) in East Baton Rouge Parish. All estimates lie within a 95% confidence interval.

R functions called by reproduce-results-script.R. (R 8 kb)

The data on relationship to householder were derived from answers to Question 2 in the 2015 American Community Survey (ACS), which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs.

The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multi-generational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.

Household – A household includes all the people who occupy a housing unit. (People not living in households are classified as living in group quarters.) A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other people in the building and which have direct access from the outside of the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living arrangements.

Average Household Size – A measure obtained by dividing the number of people in households by the number of households. In cases where people in households are cross-classified by race or Hispanic origin, people in the household are classified by the race or Hispanic origin of the householder rather than the race or Hispanic origin of each individual.

Average household size is rounded to the nearest hundredth.

Comparability – The relationship categories for the most part can be compared to previous ACS years and to similar data collected in the decennial census, CPS, and SIPP. With the change in 2008 from “In-law” to the two categories of “Parent-in-law” and “Son-in-law or daughter-in-law,” caution should be exercised when comparing data on in-laws from previous years. “In-law” encompassed any type of in-law such as sister-in-law. Combining “Parent-in-law” and “son-in-law or daughter-in-law” does not represent all “in-laws” in 2008.

The same can be said of comparing the three categories of “biological” “step,” and “adopted” child in 2008 to “Child” in previous years. Before 2008, respondents may have considered anyone under 18 as “child” and chosen that category. The ACS includes “foster child” as a category. However, the 2010 Census did not contain this category, and “foster children” were included in the “Other nonrelative” category. Therefore, comparison of “foster child” cannot be made to the 2010 Census. Beginning in 2013, the “spouse” category includes same-sex spouses.

Poverty-related data with margins of error based on status determination at Alaskan Borough/CDA level for recent 5-year American Community Survey (ACS) intervals. The 5-year interval data sets are published approximately 1/2 a period later than the End Year listed - for instance the interval ending in 2019 is published in mid-2021.Source: US Census Bureau, American Community SurveyThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: US Census Bureau, Poverty DataUSE CONSTRAINTS: The Alaska Department of Commerce, Community, and Economic Development (DCCED) provides the data in this application as a service to the public. DCCED makes no warranty, representation, or guarantee as to the content, accuracy, timeliness, or completeness of any of the data provided on this site. DCCED shall not be liable to the user for damages of any kind arising out of the use of data or information provided. DCCED is not the authoritative source for American Community Survey data, and any data or information provided by DCCED is provided "as is". Data or information provided by DCCED shall be used and relied upon only at the user's sole risk.For information about the American Community Survey, click here.

Attitude of the German population and of critics of the census to the census after census day on 31 May 1987. Political attitudes. Topics: political interest; satisfaction with democracy in the Federal Republic; government orientation toward its own interests or public interest; perceived protection of rights to freedom by the political system and the current Federal Government; satisfaction with the job of the Federal Government; attitude to the census; receipt of a written request to fill out the questionnaire; intent to participate in the census before start of counting; personal willingness to participate in the census even given voluntary participation; assumed level of non-participation in the census; attitude to the census in one´s circle of friends and acquaintances; conversations about the census in social surroundings after conclusion of the survey and time of last conversation; knowledge about contents of the census survey; additionally expected questions; questions that one would not gladly answer; response or boycott behavior during the survey; attitude to government statistics; attitude to punishment of census boycotters and knowledge of cases of refusal; assumed willingness of the population to participate as well as honesty of responses given voluntary participation in the census; voluntarily providing selected personal data; preference for census or providing data already available by government offices; assumed benefit or damage from discussions about the census in the media and reasons for this assessment; attitude to earlier calls for boycott and to the time of survey; judgement on the success of the boycott movement; attitude to selected arguments for and against the census; benefit of a census; attitude to the obligation to provide information; census boycott as protest against the government; census participation as democratic duty; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; understanding of democracy and comparison of this right with reality in the Federal Republic; party preference; violation of fundamental rights by measures of authorities perceived personally or by persons from social surroundings; attitude to technology; perceived insecurity in contact with authorities and attitude to government offices; concerns regarding misuse of personal census data; trust in observance of data protection; attitude to storage of personal data; importance of data protection; assumed observance of data protection regulations; knowledge of cases of data misuse and source of information about such violations; assumed willingness to participate in a future census; attitude to opinion polls (scale); willingness to participate in a microcensus survey; willingness to provide information from one´s private sphere to friends, neighbors, census bureaus and scientific surveys; attitude to selected government statistics; willingness to respond in order to make statistics possible; fear of data misuse; concerns regarding misuse of personal data by selected institutions and government offices (scale); attitude to selected illegal actions (scale); religiousness (scale); attitude to questions of belief and the meaning of life (scale); belief in supernatural, inexplicable events as well as horoscopes and telepathy. Demography: month of birth; year of birth; sex; religious denomination; school education; employment; college in vicinity of place of residence; students in residential area; possession of a telephone. Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person causing the intervention; attitude to the census of other persons present during interview; presence of further persons in other rooms; reliability and willingness of respondent to cooperate. Additionally encoded were: length of interview; date of interview; identification of interviewer; sex of interviewer; age of interviewer. Einstellung der bundesdeutschen Bevölkerung und von Volkszählungskritikern zur Volkszählung nach dem Stichtag am 31. Mai 1987. Politische Einstellungen. Themen: Politisches Interesse; Zufriedenheit mit der Demokratie in der Bundesrepublik; Interessen- oder Gemeinwohlorientierung der Regierung; empfundener Schutz der Freiheitsrechte durch das politische System und die gegenwärtige Bundesregierung; Zufriedenheit mit der Arbeit der Bundesregierung; Einstellung zur Volkszählung; Erhalt einer schriftlichen Aufforderung zum Ausfüllen des Fragebogens; Teilnahmeabsicht an der Volkszählung vor Beginn der Zählung; eigene Bereitschaft zur Teilnahme an der Volkszählung, auch bei freiwilliger Teilnahme; vermutete Höhe der Nichtbeteiligung an der Volkszählung; Einstellung zur Volkszählung im Freundes- und Bekanntenkreis; Gespräche über die Volkszählung im sozialen Umfeld nach Abschluß der Erhebung und Zeitpunkt des letzten Gesprächs; Kenntnisse über die Inhalte der Volkszählungsbefragung; zusätzlich erwartete Fragen; Fragen, die ungern beantwortet wurden; Antwort- bzw. Boykottverhalten bei der Erhebung; Einstellung zu staatlichen Statistiken; Einstellung zu einer Bestrafung von Volkszählungsboykotteuren und Kenntnis von Verweigerungsfällen; vermutete Teilnahmebereitschaft der Bevölkerung sowie der Antwortehrlichkeit bei Freiwilligkeit der Teilnahme an der Volkszählung; freiwillige Weitergabe ausgewählter persönlicher Daten; Präferenz für Volkszählung oder Weitergabe von bereits vorliegenden Daten durch die Ämter; vermuteter Nutzen oder Schaden der Diskussion über die Volkszählung in den Medien und Gründe für diese Einschätzung; Einstellung zu früheren Boykottaufrufen und zum Befragungszeitpunkt; Beurteilung des Erfolgs der Boykottbewegung; Einstellung zu ausgewählten Argumenten für und gegen die Volkszählung; Nutzen einer Volkszählung; Einstellung zur Auskunftspflicht; Volkszählungsboykott als Protest gegen den Staat; Volkszählungsteilnahme als demokratische Pflicht; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; vermutete Position der Bevölkerungsmehrheit auf einem Links-Rechts-Kontinuum; Demokratieverständnis und Vergleich dieses Anspruchs mit der Wirklichkeit in der Bundesrepublik; Parteipräferenz; persönlich oder von Personen des sozialen Umfelds empfundene Verletzung der Grundrechte durch Behördenmaßnahmen; Einstellung zur Technik; empfundene Unsicherheiten bei Behördenkontakten und Einstellung gegenüber Ämtern; Befürchtungen hinsicht lich einer Zweckentfremdung der persönlichen Volkszählungsdaten; Vertrauen in die Einhaltung des Datenschutzes; Einstellung zur Speicherung personenbezogener Daten; Wichtigkeit des Datenschutzes vermutete Einhaltung der Datenschutzbestimmungen; Kenntnis von Fällen des Datenmißbrauchs und Informationsquelle über solche Verstöße; vermutete Teilnahmebereitschaft an einer zukünftigen Volkszählung; Einstellung zu Meinungsumfragen (Skala); Teilnahmebereitschaft an einer Mikrozensus-Erhebung; Weitergabebereitschaft von Informationen aus der Privatsphäre an Freunde, Nachbarn, statistische Ämter und in wissenschaftlichen Umfragen; Einstellung zu ausgewählten staatlichen Statistiken; Antwortbereitschaft, um Statistiken zu ermöglichen; Angst vor Datenmißbrauch; Befürchtungen hinsichtlich einer Zweckentfremdung der persönlichen Daten durch ausgewählte Institutionen und Ämter (Skala); Einstellung zu ausgewählten illegalen Handlungen (Skala); Religiosität (Skalometer); Einstellung zu Glaubensfragen und zum Sinn des Lebens (Skala); Glaube an übersinnliche, unerklärliche Ereignisse sowie an Horoskope und Telepathie. Demographie: Geburtsmonat; Geburtsjahr; Geschlecht; Konfession; Schulbildung; Berufstätigkeit; Hochschule in Wohnortnähe; Studenten in der Wohngegend; Telefonbesitz. Interviewerrating: Anwesenheit Dritter beim Interview und Person, die die Anwesenheit erwünschte; Eingriffe Dritter in das Interview und Person, die die Intervention herbeiführte; Einstellung der beim Interview zusätzlich anwesenden Person zur Volkszählung; Anwesenheit weiterer Personen in anderen Räumen; Kooperationsbereitschaft und Zuverlässigkeit des Befragten. Zusätzlich verkodet wurde: Interviewdauer; Interviewdatum; Intervieweridentifikation; Interviewergeschlecht; Intervieweralter. Re-interview of the persons interviewed in the second panel wave (ZA Study No. 1589) as well as of persons interviewed in the first panel wave (ZA Study No. 1588), but not contacted in the survey of the second panel wave. Wiederbefragung der in der 2. Panel-Welle befragten Personen (ZA-Studien-Nr. 1589) sowie von Personen, die in der 1. Panel-Well interviewt wurden (ZA-Studien-Nr. 1588), bei der Befragung der 2. Panel-Welle aber nicht angetroffen wurden.

Description of the experiment setting: location, influential climatic conditions, controlled conditions (e.g. temperature, light cycle)In Fall of 2023 the USDA Food and Nutrition Service (FNS) conducted the fourth Farm to School Census. The 2023 Census was sent via email to 18,833 school food authorities (SFAs) including all public, private, and charter SFAs, as well as residential care institutions, participating in the National School Lunch Program. The questionnaire collected data on local food purchasing, edible school gardens, other farm to school activities and policies, and outcomes and challenges of participating in farm to school activities. A total of 12,559 SFAs submitted a response to the 2023 Census.Processing methods and equipment usedThe 2023 Census was administered solely via the web. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. This process involved examining the data for logical errors and removing implausible values. The study team linked the 2023 Census data to information from the National Center of Education Statistics (NCES) Common Core of Data (CCD). Records from the CCD were used to construct a measure of urbanicity, which classifies the area in which schools are located.Study date(s) and durationData collection occurred from October 2, 2023 to January 7, 2024. Questions asked about activities prior to, during and after SY 2022-23. The 2023 Census asked SFAs whether they currently participated in, had ever participated in or planned to participate in any of 32 farm to school activities. Based on those answers, SFAs received a defined set of further questions.Study spatial scale (size of replicates and spatial scale of study area)Respondents to the survey included SFAs from all 50 States as well as American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and Washington, DC.Level of true replicationUnknownSampling precision (within-replicate sampling or pseudoreplication)No sampling was involved in the collection of this data.Level of subsampling (number and repeat or within-replicate sampling)No sampling was involved in the collection of this data.Study design (before–after, control–impacts, time series, before–after-control–impacts)None – Non-experimentalDescription of any data manipulation, modeling, or statistical analysis undertakenEach entry in the dataset contains SFA-level responses to the Census questionnaire for SFAs that responded. This file includes information from only SFAs that clicked “Submit” on the questionnaire. (The dataset used to create the 2023 Farm to School Census Report includes additional SFAs that answered enough questions for their response to be considered usable.)In addition, the file contains constructed variables used for analytic purposes. The file does not include weights created to produce national estimates for the 2023 Farm to School Census Report.The dataset identified SFAs, but to protect individual privacy the file does not include any information for the individual who completed the questionnaire. All responses to open-ended questions (i.e., containing user-supplied text) were also removed to protect privacy.Description of any gaps in the data or other limiting factorsSee the full 2023 Farm to School Census Report [https://www.fns.usda.gov/research/f2s/2023-census] for a detailed explanation of the study’s limitations.Outcome measurement methods and equipment usedNone