Whites have become decreasingly likely to support the Democratic Party. I show this shift is being driven by two mechanisms. The first mechanism is the process of ideological sorting. The Democratic Party has lost support among conservative whites because the relationships between partisanship, voting behavior, and policy orientations have strengthened. The second mechanism relates to demographic changes. The growth of liberal minority populations has shifted the median position on economic issues to the left and away from the median white citizen’s position. The parties have responded to these changes by shifting their positions and whites have become less likely to support the Democratic Party as a result. I test these explanations using 40 years of ANES and DW-NOMINATE data. I find that whites have become 7.7-points more likely vote for the Republican Party and mean white partisanship has shifted .25 points in favor of the Republicans as a combined result of both mechanisms.

This statistic shows the demographic and socio-economic factors most likely to shape global industries according to executive respondents from large companies worldwide, as of July 2015. 44% of executives believe that the changing nature of work or flexible work will cause major change in their industry by 2020.

This comprehensive dataset, derived from the United Nations World Urbanization Prospects 2018, provides detailed insights into the global demographic shifts from 1950 to 2050. It covers a wide range of data points including total, urban, and rural populations, alongside growth rates and urbanization trends across different regions, subregions, and countries.

Dataset Files WUP2018-F01-Total_Urban_Rural.xls: Population counts for urban and rural areas as of mid-2018, including percentages. WUP2018-F02-Proportion_Urban.xls: Historical and projected percentages of urban populations from 1950 to 2050. WUP2018-F03-Urban_Population.xls: Urban population figures from 1950 to 2050. WUP2018-F04-Rural_Population.xls: Rural population figures from 1950 to 2050. WUP2018-F05-Total_Population.xls: Total population figures from 1950 to 2050. WUP2018-F06-Urban_Growth_Rate.xls: Annual urban population growth rates from 1950 to 2050. WUP2018-F07-Rural_Growth_Rate.xls: Annual rural population growth rates from 1950 to 2050. WUP2018-F08-Total_Growth_Rate.xls: Total population growth rates from 1950 to 2000. WUP2018-F09-Urbanization_Rate.xls: Changes in the rate of urbanization from 1950 to 2050. WUP2018-F10-Rate_Proportion_Rural.xls: Changes in the proportion of rural populations from 1950 to 2050. WUP2018-F18-Total_Population_Annual.xls: Detailed annual total population data from 1950 to 2050. WUP2018-F19-Urban_Population_Annual.xls: Detailed annual urban population data from 1950 to 2050. WUP2018-F20-Rural_Population_Annual.xls: Detailed annual rural population data from 1950 to 2050. WUP2018-F21-Proportion_Urban_Annual.xls: Detailed annual urban population percentages from 1950 to 2050. Potential Uses This dataset is invaluable for researchers, policy makers, urban planners, and sociologists interested in understanding the dynamics of urbanization and its impacts on global development. The data can be used for:

Analyzing trends in urban and rural growth. Forecasting future demographic shifts. Planning for infrastructure, services, and resources in rapidly urbanizing regions. Studying regional differences in development and urbanization.

Better understanding of the changing relationship between human populations and climate is a global research priority. The 20th century in the contiguous United States offers a particularly well-documented example of human demographic expansion during a period of radical socioeconomic and environmental change. One would expect that as human society has been transformed by technology, we would become increasingly decoupled from climate and more dependent on social infrastructure. Here we use spatially-explicit models to evaluate climatic, socio-economic and biophysical correlates of demographic change in the contiguous United States between 1900 and 2000. Climate-correlated variation in population growth has caused the U.S. population to shift its realized climate niche from cool, seasonal climates to warm, aseasonal climates. As a result, the average annual temperature experienced by U.S. citizens between 1920 and 2000 has increased by more than 1.5°C and the temperature seasonality has decreased by 1.1°C during a century when climate change accounted for only a 0.24°C increase in average annual temperature and a 0.15°C decrease in temperature seasonality. Thus, despite advancing technology, climate-correlated demographics continue to be a major feature of contemporary U.S. society. Unfortunately, these demographic patterns are contributing to a substantial warming of the climate niche during a period of rapid environmental warming, making an already bad situation worse.

Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as education, nationality, religion, and ethnicity. Educational institutions usually treat demography as a field of sociology, though there are a number of independent demography departments. These methods have primarily been developed to study human populations, but are extended to a variety of areas where researchers want to know how populations of social actors can change across time through processes of birth, death, and migration. In the context of human biological populations, demographic analysis uses administrative records to develop an independent estimate of the population

Migration, Homeownership, Social Trust

Social Transition in the North (STN), was a four-year research study funded by the National Science Foundation (NSF; OPP-9213137 and OPP-9496351). STN was a longitudinal study analyzing four circumpolar regions, two in Russia (Chukotka and Kamchatka) and two in Alaska (Nana and Aleutian-Pribilof Islands), looking at demographic, epidemiologic, and domestic social transitions (Mason, 2004). Demographic transitions were the study of change in mortality and birth rate. Epidemiologic transitions were studied by watching the change of infectious disease and increase of lifestyle diseases. The third transition was domestic, and is summarized as the redefinition of family, family member roles, and the family’s role within the community. The overall goal was to predict future changes, especially of high-risk conditions, and encourage institutional change that would improve services for these conditions. During the final year of the study, while in the Russian region of Chukotka, the principal investigators, two additional research staff, and 10 villagers, died in a tragic boating accident in September of 1995. It was decided that the documents would be given to the Institute for Circumpolar Health Studies (ICHS) at the University of Alaska Anchorage where they are now housed. If researchers are interested in accessing any STN material, a data use agreement will be set in place with the following requirements: to submit an application the UAA IRB, to honor the content of the original consent forms, and in their UAA IRB application specify how they intend to be responsive to the NSF Principles for the Conduct of Research in the Arctic. Further, ICHS will require a copy of UAA IRB's approval prior to release of STN materials. Anyone interested in accessing the data can also contact: Dr. Janet Johnston (jmjohnston2@alaska.edu) or the University of Alaska at Anchorage Institute for Circumpolar Health Studies (uaa_ichs@alaska.edu)

Retirement Communities Market Outlook

The global retirement communities market size was valued at approximately USD 250 billion in 2023 and is projected to reach around USD 400 billion by 2032, growing at a CAGR of about 5%. This growth is primarily driven by the aging global population, an increase in life expectancy, and changing lifestyle preferences among seniors. The shift towards comprehensive care and the integration of health and wellness services within retirement communities have further fueled this market's expansion. As societies worldwide continue to experience demographic shifts, the demand for retirement communities that offer a blend of healthcare, hospitality, and recreational amenities is expected to surge, underpinning the robust growth trajectory of the sector.

The burgeoning aging population is one of the primary growth factors for the retirement communities market. As advances in healthcare continue to improve life expectancy, a significant proportion of the global population is projected to fall within the senior age bracket, necessitating adequate living solutions for them. This demographic shift is particularly pronounced in developed regions such as North America and Europe, where a considerable percentage of the population is transitioning into retirement age. Additionally, emerging economies in Asia Pacific are also witnessing an increase in the elderly population, driven by improved healthcare infrastructure and living standards. This demographic evolution necessitates the development of retirement communities equipped with facilities that cater to both the healthcare and lifestyle needs of seniors.

Another significant growth factor is the increased financial independence and spending power among seniors. With many from the baby boomer generation having accrued substantial savings and investments, there is a growing willingness to spend on quality living environments that provide comfort, security, and access to healthcare and recreational activities. This financial capability, coupled with the desire for a community living environment that offers social interaction and reduces isolation, is a key driver for the retirement communities market. Furthermore, these communities are increasingly incorporating technology to enhance the quality of life for residents, with features such as telemedicine, smart home technologies, and digital health monitoring, which are appealing to the tech-savvy senior demographic.

Moreover, the changing societal norms and lifestyle preferences among the elderly are also contributing to the market's growth. TodayÂ’s seniors are more active and health-conscious than ever before, seeking retirement communities that offer wellness programs, fitness centers, and social activities that align with their lifestyle choices. The emphasis on holistic well-being has led to a rise in integrated community models that provide a continuum of care, from independent living to assisted living and nursing care, allowing seniors to age in place with dignity and peace of mind. This trend is expected to intensify in the coming years, further propelling the growth of the retirement communities market globally.

In recent years, the concept of Smart Communities has emerged as a transformative force within the retirement sector. These communities leverage advanced technologies to create interconnected environments that enhance the quality of life for residents. By integrating smart home devices, IoT solutions, and data-driven services, Smart Communities offer personalized and efficient living experiences. This technological integration not only improves safety and convenience for seniors but also promotes sustainable living practices. As the demand for tech-savvy solutions grows, retirement communities are increasingly adopting smart technologies to meet the evolving expectations of their residents, positioning themselves at the forefront of innovation in senior living.

Regionally, North America currently holds the largest share of the retirement communities market, driven by a well-established infrastructure, high disposable incomes, and a significant aging population. Europe follows closely, benefiting from similar demographic trends and a strong emphasis on social welfare programs for the elderly. Meanwhile, the Asia Pacific region is anticipated to exhibit the highest growth rate over the forecast period, fueled by rapid urbanization, economic growth, and increasing healthcare investments. Countries such as China, Japan, and India are at the forefront of this expansion, as they adapt to th

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.

This dataset was created to support the 2016 Social Pulse in Latin America and the Caribbean: Realities & Perspectives. The publication highlights specific indicators where progress has been made such us "race and ethnicity," and areas where large gaps remain. Also, the new dynamic between generations: "poverty and family structure," examines demographic shifts in the region, including the evolution of family living arrangements and trends in the age profile of poverty.

Changes in demographics will fundamentally shift the types of consumers that insurers need to target, as well as the types of products they need to provide. An aging population will put increased strain on state pensions and social services like public healthcare. A declining middle class due to median incomes not increasing as fast as other core goods and services means young people are buying a house, getting married, and starting families at later points in life. And a larger proportion of the population living in urban areas leads to increased health risk due to pollution, poor hygiene, and other urban lifestyle factors. These three factors will help shape the insurance industry going forward. Read More

Supplementary Information Files for Socio-economic groups moving apart: An analysis of recent trends in residential segregation in Australia's main capital citiesWe study changes in the spatial distribution and segregation of socio-economic groups in Australia using a new data set with harmonised census data for 1991 and 2011. We find a general increase in residential segregation by education and occupation groups across the major capital cities in Australia. Importantly, these trends cannot be explained in general by changes in the demographic structure of groups and areas but rather by the rise in the over and underrepresentation of groups across areas. In particular, our analysis reveals clear diverging trends in the spatial configuration of high and low socio-economic groups as measured by their occupation and education. Whereas high-skilled groups became more concentrated in the inner parts of cities, the low-educated and those working in low-status occupations became increasingly overrepresented in outer areas. This pattern is observed in all five major capital cities, but it is especially marked in Sydney, Melbourne and Brisbane.

The Stata data file "CAP_Demographics_Jumla_Kavre_recoded.dta” and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Kavre in the central hills of Nepal during April 2022 and in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project.

The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. Researchers from KLL and UCL trained the adolescents to record basic socio-demographic information about themselves and their households including caste/ethnicity, religion, education, water sources, assets, household characteristics, and income sources. The form also asked about their access to mobile phones or other devices and internet and their concerns with respect to climate change. The resulting data describe the participants in the citizen science project, but their names and addresses have been removed. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Tables 2 and 3 of this paper.

Mobile Social Software Market Outlook

The global mobile social software market size was valued at approximately $29.5 billion in 2023 and is expected to grow at a compound annual growth rate (CAGR) of 22.3% to reach around $115.6 billion by 2032. The market's growth is primarily driven by the increasing penetration of smartphones and high-speed internet, coupled with the rising demand for social connectivity through digital platforms.

One of the critical growth factors for the mobile social software market is the widespread adoption of smartphones and mobile devices. With smartphone penetration reaching unprecedented levels globally, more individuals are accessing social software through these devices. The convenience and accessibility provided by mobile platforms have revolutionized how people interact, share content, and stay connected, leading to an increasing reliance on mobile social software. Additionally, the advancements in mobile internet infrastructure, such as the rollout of 5G networks, are enabling faster and more reliable connectivity, further boosting the usage and functionality of mobile social software.

Another significant driver of market growth is the increasing emphasis on digital communication and social interaction, especially among younger demographics. Millennials and Generation Z, who are digitally native, have a strong preference for mobile-based social interactions. This demographic shift is compelling social software developers to focus more on mobile platforms, leading to innovations and enhancements in user experience. Moreover, the COVID-19 pandemic accelerated the adoption of digital communication tools as physical distancing measures became the norm, highlighting the importance of mobile social software in maintaining social connections during times of crisis.

The rise of multimedia content creation and sharing is also contributing to the market's expansion. Platforms that facilitate the sharing of images, videos, and live streams are witnessing robust growth. Users are increasingly engaging with visual content, driven by the desire for richer and more immersive social interactions. As a result, mobile social software is evolving to support high-quality multimedia sharing capabilities, enhancing user engagement and retention. Furthermore, the integration of augmented reality (AR) and virtual reality (VR) features in social software is creating new opportunities for immersive social experiences, further propelling market growth.

Social Network platforms have become an integral part of daily life, offering users the ability to connect, share, and communicate with others across the globe. These platforms have evolved from simple communication tools to complex ecosystems that support a wide range of interactions, including multimedia sharing, live streaming, and community building. The rise of social networks has also influenced consumer behavior, with many users relying on these platforms for news, entertainment, and social engagement. As a result, businesses are increasingly leveraging social networks for marketing and customer engagement, recognizing their potential to reach vast audiences and gather valuable consumer insights. The continuous innovation in social network features and functionalities is driving user engagement and expanding the market's reach.

From a regional perspective, the Asia Pacific region is expected to dominate the mobile social software market, driven by the large and growing user base in countries like China, India, and Japan. North America and Europe are also significant markets due to high smartphone penetration and advanced internet infrastructure. In contrast, regions like Latin America and the Middle East & Africa are witnessing gradual adoption, primarily driven by increasing internet accessibility and mobile device penetration. Each region presents unique opportunities and challenges, influencing the market dynamics and growth trajectories.

Component Analysis

The mobile social software market is segmented into software and services. The software component includes various applications and platforms that facilitate social interactions, such as social networking apps, instant messaging services, content sharing platforms, and location-based services. This segment is witnessing significant growth due to continuous innovation and the development of new features that enhance user experience. Companies are investing heavily in research and development to introduce cutt

This dataset provides a range of demographic and socio-economic variables for Registration Sub-Districts (RSDs) in England and Wales, 1851-1911. The measures have mainly been derived from the computerised individual level census enumerators' books (and household schedules for 1911) for England and Wales enhanced under the I-CeM project. I-CeM does not currently include data for 1871, although the project has been able to access a version of the data for that year it does not contain information necessary to calculate many of the variables presented here. Users should therefore beware that 1871 does not contain data for many of the variables. Additional data, for some indicators, has been derived from the tables summarising numbers of births and deaths by year and areas, which were published by the Registrar General in his quarterly, annual and decennial reports of births, deaths and marriages. More information on the data, including overviews of the geographical patterns and changes over time, can be found on the Populations Past – Atlas of Victorian and Edwardian Population website, which provides an interactive mapping facility for these data. The second half of the nineteenth century was a period of major change in the dynamics of the British population. This was a time of transformation from a relatively 'high pressure' demographic regime characterised by medium to high birth and death rates towards a 'low pressure' regime of low birth and death rates, a transformation known as the 'demographic transition'. This transition was not uniform across England and Wales: certain places and social groups appear to have led the declines while others lagged behind. Exploring these geographical patterns can provide insights into the process of change and the influence of economic and geographical factors. This project aimed to utilise the individual-level data of the Integrated Census Microdata (I-CeM) project to calculate age-specific fertility rates both for a range of fine geographical units covering England and Wales and for occupational groups and then to investigate the relationships between these rates and other socioeconomic variables. This was to provide, for the first time, widespread information of the age patterns of fertility which render insight into ‘starting’, ‘spacing’ or ‘stopping’ fertility regulating behaviour. A time series of such measures across geographical and social space is also vital when trying to identify how new forms of behaviour spread through the population. This database contains a variety of measures of fertility, marriage and infant and child mortality, and also a range of socio-economic indicators (related to households, age structure, and social class) for the 2000+ Registration Sub Districts (RSDs) in both England and Wales, for each census year between 1851 and 1871. Most of these data can be mapped using our interactive website www.populationspast.org. This data collection was derived from near complete count individual level census data, from which we have created demographic and socio-economic indicators at a Registration Sub-District level, using a variety of demographic and statistical techniques. For a few variables, birth and death summary data (at Sub-Registration District level) were also used.

The DSS Payment Demographic data set is made up of:

Selected DSS payment data by

• Geography: state/territory, electorate, postcode, LGA and SA2 (for 2015 onwards)

• Demographic: age, sex and Indigenous/non-Indigenous

• Duration on Payment (Working Age & Pensions)

• Duration on Income Support (Working Age, Carer payment & Disability Support Pension)

• Rate (Working Age & Pensions)

• Earnings (Working Age & Pensions)

• Age Pension assets data

• JobSeeker Payment and Youth Allowance (other) Principal Carers

• Activity Tested Recipients by Partial Capacity to Work (NSA,PPS & YAO)

• Exits within 3, 6 and 12 months (Newstart Allowance/JobSeeker Payment, Parenting Payment, Sickness Allowance & Youth Allowance)

• Disability Support Pension by medical condition

• Care Receiver by medical conditions

• Commonwealth Rent Assistance by Payment type and Income Unit type have been added from March 2017. For further information about Commonwealth Rent Assistance and Income Units see the Data Descriptions and Glossary included in the dataset.

From December 2022, the "DSS Expanded Benefit and Payment Recipient Demographics – quarterly data" publication has introduced expanded reporting populations for income support recipients. As a result, the reporting population for Jobseeker Payment and Special Benefit has changed to include recipients who are current but on zero rate of payment and those who are suspended from payment. The reporting population for ABSTUDY, Austudy, Parenting Payment and Youth Allowance has changed to include those who are suspended from payment. The expanded report will replace the standard report after June 2023.

Additional data for DSS Expanded Benefit and Payment Recipient Demographics – quarterly data includes:

• A new contents page to assist users locate the information within the spreadsheet

• Additional data for the ‘Suspended’ population in the ‘Payment by Rate’ tab to enable users to calculate the old reporting rules.

• Additional information on the Employment Earning by ‘Income Free Area’ tab.

From December 2022, Services Australia have implemented a change in the Centrelink payment system to recognise gender other than the sex assigned at birth or during infancy, or as a gender which is not exclusively male or female. To protect the privacy of individuals and comply with confidentialisation policy, persons identifying as ‘non-binary’ will initially be grouped with ‘females’ in the period immediately following implementation of this change. The Department will monitor the implications of this change and will publish the ‘non-binary’ gender category as soon as privacy and confidentialisation considerations allow.

Local Government Area has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2022 boundaries from June 2023.

Commonwealth Electorate Division has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

SA2 has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

From December 2021, the following are included in the report:

• selected payments by work capacity, by various demographic breakdowns

• rental type and homeownership

• Family Tax Benefit recipients and children by payment type

• Commonwealth Rent Assistance by proportion eligible for the maximum rate

• an age breakdown for Age Pension recipients

For further information, please see the Glossary.

From June 2021, data on the Paid Parental Leave Scheme is included yearly in June releases. This includes both Parental Leave Pay and Dad and Partner Pay, across multiple breakdowns. Please see Glossary for further information.

From March 2017 the DSS demographic dataset will include top 25 countries of birth. For further information see the glossary.

From March 2016 machine readable files containing the three geographic breakdowns have also been published for use in National Map, links to these datasets are below:

• Statistical Area 2 - SA2

• Commonwealth Electoral Division - CED

• Local Government Area - LGA

Pre June 2014 Quarter Data contains:

Selected DSS payment data by

• Geography: state/territory; electorate; postcode and LGA

• Demographic: age, sex and Indigenous/non-Indigenous

Note: JobSeeker Payment replaced Newstart Allowance and other working age payments from 20 March 2020, for further details see: https://www.dss.gov.au/benefits-payments/jobseeker-payment

For data on DSS payment demographics as at June 2013 or earlier, the department has published data which was produced annually. Data is provided by payment type containing timeseries’, state, gender, age range, and various other demographics. Links to these publications are below:

• Statistical Paper series

Concession card data in the March and June 2020 quarters have been re-stated to address an over-count in reported cardholder numbers.

28/06/2024 – The March 2024 and December 2023 reports were republished with updated data in the ‘Carer Receivers by Med Condition’ section, updates are exclusive to the ‘Care Receivers of Carer Payment recipients’ table, under ‘Intellectual / Learning’ and ‘Circulatory System’ conditions only.

About this dataset

Context

The dataset tabulates the Social Circle population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Social Circle across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Social Circle was 5,330, a 1.22% increase year-by-year from 2022. Previously, in 2022, Social Circle population was 5,266, an increase of 2.69% compared to a population of 5,128 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Social Circle increased by 1,767. In this period, the peak population was 5,330 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Social Circle is shown in this column.
• Year on Year Change: This column displays the change in Social Circle population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Social Circle Population by Year. You can refer the same here

The POPLINK database contains personal records entered from parish registers from large parts of the Västerbotten county and the inland of Norrland. The database covers parish registers from the end of the 17th century until 1950. The personal records stem from different types of parish registers such as catechetical registers, birth and baptism registers, banns and marriage registers, migrations registers, and death registers.

These datasets, ranging from birth to death, provides possibilities to link together individuals and generations. The life stories of individuals as well as family histories can be tracked. Moreover, the dataset offers the possibility to study demographical and socio-economic changes over time across different regions and parishes.

The purpose of the POPLINK database is to provide detailed individual records from church books between the late 1600s and around 1950 for research. It enables studies on demography, social structures, and historical development in Sweden. POPUM offers data on, among other things, population development, migration patterns, economic changes, industrialization, agricultural communities, small-scale farming, Sámi history, and urbanization.

The database is a resource in many areas of research. Not least because of the possibility to link together POPLINK with other modern registers. This means, among other things, that the life sciences can investigate how nature and nurture influence the development of our most common national diseases, such as cardiovascular diseases, cancer, and diabetes. Within the social sciences and the humanities, the increasing access to personal records brings about an opportunity for new perspectives on the rise of the welfare state and the time that shaped the modern Sweden.

POPLINK is a research database, which means that only academic researchers can be given access. In some cases it requires approval from The Swedish Ethical Review Authority.

Replication data for the demographic change example in Chapter 2 of Spatial Analysis for the Social Sciences.

The social and demographic data included in this collection consist of a single data file for each decennial year between 1870 and 2000, covering 10 of the 12 Great Plains states. Information on a variety of social and demographic topics was gathered to historically characterize populations living in counties within the United States Great Plains, in terms of: (1) urban, rural, and total population, (2) vital statistics, (3) net migration, (4) age and sex, (5) nativity and ancestry, (6) education and literacy, (7) religion, (8) industry, and (9) housing and other characteristics. These data include selected material compiled as part of the United States population census. The United States Census of Population and Housing has been conducted since 1790 on a regular schedule that is decennial. The county-level social and demographic data produced by the United States government as a result constitute a consistent series of measures capturing changes in the United States population's size, composition, and other characteristics. A subset of the variables available from the short and long-form survey questionnaires of the United States Census of Population and Housing (as compiled for counties) were extracted from previously existing digital files. Besides the decennial census of the population, county-level data were drawn from an assortment of existing digital files as well as sources that were manually digitized. Other data include compilations of county-level information gathered from various federal agencies and private organizations as well as the agriculture and economic censuses. Supplementing these compilations are manually digitized consumer market data, religious data, and vital statistics, including information about births, deaths, marriage, and divorce.