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In the International Classification of Functioning, Disability and Health (ICF) 2001, the World Health Organization (WHO) defines disability as: ‘an umbrella term for impairments, activity limitations and participation restrictions. It denotes the negative aspects of the interaction between an individual (with a health condition) and that individual's contextual factors (environmental and personal factors)’, with environmental factors including assistance from other people, from equipment and from formal sources. WHO previously defined disability, in the context of health experience, as “any restriction or lack (resulting from impairment) of ability to perform an action in the manner or within the range considered normal for a human being” (World Health Organization, 1980, p. 28).

The purpose of this paper is to compare the new Census 2011 results with the results of the previous Censuses and assess the progress in trends of population growth, literacy rate, and sex ratio imbalance and also to highlight the critical socioeconomic issues based on short‐term trends and patterns.

The paper is structured in a “commentary and perspective” format. The paper assesses key demographic and socioeconomic features of India's population using 2011 Census data, and compares progress in population and social trends with the results of previous Censuses. The paper also uses data from the National Family Health Survey (2005‐2006) and the United Nations World Population Prospects (2008) to complement Census results and understand the underlying reasons for the progress or deterioration in critical demographic and socioeconomic indicators.

The provisional results of the 2011 Census data reveal a mixed bag of insights. On the positive side, there has been steady progress in population stabilization and a swift ascent in female literacy since 1991. These encouraging trends, among others, represent major driving forces of demographic and economic returns for India in the coming decades. However, on the negative side, the 2011 Census reveals a deplorable deterioration in the female‐male ratio of the child population aged 0‐6 years, despite India's enforcement of targeted policy measures following the 2001 Census. The country needs to take careful stock of this issue, as its advancing demographic transition and changing socioeconomic circumstances are rapidly translating into an adverse trend of girl child discrimination.

This study compares India's most recent two Censuses and provides original analytical insights into India's progress in population stabilization and development, and the setbacks it faces in terms of gender inequalities. Region and state‐wise analyses are additional contributions based on disaggregated state level data from the recent two Censuses.

The US fertility transition in the nineteenth century is unusual. Not only did it start from a very high fertility level and very early in the nation’s development, but it also took place long before the nation’s mortality transition, industrialization, and urbanization. This paper assembles new county-level, household-level, and individual-level data, including new complete-count IPUMS microdata databases of the 1830–1880 censuses, to evaluate different theories for the nineteenth-century American fertility transition. We construct cross-sectional models of net fertility for currently-married white couples in census years 1830–1880 and test the results with a subset of couples linked between the 1850–1860, 1860–1870, and 1870–1880 censuses. We find evidence of marital fertility control consistent with hypotheses as early as 1830. The results indicate support for several different but complementary theories of the early US fertility decline, including the land availability, conventional structuralist, ideational, child demand/quality-quantity tradeoff, and life cycle savings theories.

The neighborhoods north and northwest of downtown St Louis are blighted by their abundance of substandard, abandoned, and demolished housing. Crime, poverty, and unemployment are high while family stability, educational achievement, and health outcomes are low. These conditions are not unique to St Louis, but can be found in neighborhoods in every city in America. How did this happen? What factors led to the demise of these neighborhoods? This chapter examines the history of St Louis along with theories of neighborhood succession to identify possible explanations for the city's collapse.

The purpose of this paper is to identify bank deserts in the USA in 2009 and 2015, separately for inner city, suburban, and rural areas. It also identifies correlations between bank deserts, population characteristics, market competition, and payday lending restrictions, both cross-sectionally and over time.

FDIC data on bank office locations are used to identify bank deserts, defined as the 5 percent of census tracts with the greatest distance from the centroid to the nearest office. Those data are matched to both American Community Survey data to identify population characteristics, to a list of states with payday lending prohibitions, and to levels of market competition. An alternative measure of bank deserts corrects for population density. Geography is analyzed, mean characteristics compared, and random effects regressions capture static and dynamic correlates.

Population density explains approximately half of bank distance variance. Bank deserts appear more often in southern and western states, and expanded significantly in inner cities while contracting in rural areas. Regression results suggest that African Americans were overall and increasingly likely to live in bank deserts and Native Americans were overall more likely to live in rural bank deserts. Rural poverty is linked to bank deserts, and the effects of competition are complex.

The space for policy intervention exists in African American inner cities and Native American rural communities.

The relative measure of bank deserts is novel, as are dynamic estimates and random effects analysis of correlates.

1991 has seen a new census and local authorities will be keen to analyse the changes which have occurred since the last census. Their analysis will be helped by the introduction of Geographical Information Systems which have been recommended by the Chorley Report. The findings of ten in‐depth interviews with local authority officers within planning departments are examined in this pilot study. These officers were asked about Geographical Information Systems, the Population Census and the Census of Distribution.

Community health clinics serving the poor and underserved are geographically expanding due to changes in U.S. health care policy. This paper describes the experience of a collaborative alliance of health care providers in a large metropolitan area who develop a conceptual and mathematical decision model to guide decisions on expanding its network of community health clinics.

Community stakeholders participated in a collaborative process that defined constructs they deemed important in guiding decisions on the location of community health clinics. This collaboration also defined key variables within each construct. Scores for variables within each construct were then totaled and weighted into a community-specific optimal space planning equation. This analysis relied entirely on secondary data available from published sources.

The model built from this collaboration revolved around the constructs of demand, sustainability, and competition. It used publicly available data defining variables within each construct to arrive at an optimal location that maximized demand and sustainability and minimized competition.

This is a model that safety net clinic planners and community stakeholders can use to analyze demographic and utilization data to optimize capacity expansion to serve uninsured and Medicaid populations.

Communities can use this innovative model to develop a locally relevant clinic location-planning framework.

A definition of data called data as assemblage is presented. The definition accommodates different forms and meanings of data; emphasizes data subjects and data workers; and reflects the sociotechnical aspects of data throughout its lifecycle of creation and use. A scalable assemblage model describing the anatomy and behavior of data, datasets and data infrastructures is also introduced.

Data as assemblage is compared to common meanings of data. The assemblage model's elements and relationships also are defined, mapped to the anatomy of a US Census dataset and used to describe the structure of research data repositories.

Replacing common data definitions with data as assemblage enriches information science and research data management (RDM) frameworks. Also, the assemblage model is shown to describe datasets and data infrastructures despite their differences in scale, composition and outward appearance.

Data as assemblage contributes a definition of data as mutable, portable, sociotechnical arrangements of material and symbolic components that serve as evidence. The definition is useful in information science and research data management contexts. The assemblage model contributes a scale-independent way to describe the structure and behavior of data, datasets and data infrastructures and supports analyses and comparisons involving them.