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The Census of Population and Housing is an important source of demographic information. Since its inception in 1790, the decennial census has been through several revisions, causing changes in its content, statistical methodology, and distribution. These alterations reflect changes in technology, society, and economy. One of the most exciting features of the 1990 census is its availability on CD‐ROM. Another important advance for the 1990 census is the creation of TIGER/Line files, which provide digital boundary maps to support the census features.

The purpose of this paper is to assess whether additional information about a community’s level of social capital can help to better predict a return rate from that area, in order to better target resources to improve mail-in responses.

Two-sample two-stage least squares is used to apply determinants of six different measures of social capital from the Social Capital Community Benchmark Survey to observations in the Decennial Census (DC) which are then aggregated to the census tract level. The probability of a census tract having a high level of each social capital measure is estimated. Multivariate regression is used to identify the importance of high community social capital for predicting census mail-in return rates.

The analysis reveals that a higher level of trust contributes the most to increasing return rates and a high level of political activism decreases return rates. Additionally, higher levels of sociability contribute negatively to DC return rates, which is consistent with sociability being linked to a more insular (i.e. family and friends) focus.

While contributing statistically significantly to the predictability of census tract response rates, the cost of acquiring measures of social capital for each census tract may not to be viewed worth the gain in predictive power.

Higher levels of trust contribute positively to survey participation, suggesting that any social, economic or political environment that diminishes trust will undercut civic engagement. Political activism and (insular) sociability decrease participation.

This paper combines non-public and public data to obtain measures of social capital along more dimensions than are typically studied, and finds that not all types of social capital are related to feelings of social integration in the same way.

This chapter uses the historian’s method of micro-history to rethink the significance of the Supreme Court decision Muller v. Oregon (1908). Muller is typically considered a labor law decision permitting the regulation of women’s work hours. However, this chapter argues that through particular attention to the specific context in which the labor dispute took place – the laundry industry in Portland, Oregon – the Muller decision and underlying conflict should be understood as not only about sex-based labor rights but also about how the labor of laundry specifically involved race-based discrimination. This chapter investigates the most important conflicts behind the Muller decision, namely the entangled histories of white laundresses’ labor and labor activism in Portland, as well as the labor of their competitors – Chinese laundrymen. In so doing, this chapter offers an intersectional reading of Muller that incorporates regulations on Chinese laundries and places the decision in conversation with a long line of anti-Chinese laundry legislation on the West Coast, including that at issue in Yick Wo v. Hopkins (1886).

It is generally difficult for the government to come up with any meaningful programs for persons with disabilities (PWDs) unless statistics to that effect have been made available. Disability Statistics in Uganda is one of those areas of social statistics which has been growing at a slow pace in the past compared to other socioeconomic indicators, but now is an area of growing concern and picking up steadily. Censuses have remained the major data providers for disability statistics and the first of which was the 1991 census. The 2002 census similarly collected information on PWDs, and this information is to be widely disseminated at national and lower levels. Both censuses were conducted by the Uganda Bureau of Statistics (UBOS). UBOS has collected similar but a little more detailed information on disability using two household surveys.

However for effective program design, implementation and resource allocation for PWDs, a lot needs to be done in terms of harmonizing the concepts on disability with the International Classification of Functional Disability and Health (ICF). The power of the census results is that it provides data to the lowest administrative level. Conducting a fully fledged national survey for PWDs will provide adequate baseline data for meaningful purposes and priority issues for government and other users.

This report provides information on the various sources of disability data and how concepts are defined by each institution. It highlights the Uganda Bureau of Statistics, Ministry of Education and Sports (Annual School Census and the Department for Special Needs), Ministry of Gender, Labour and Social Development (Community-Based Rehabilitation Program) and the Ministry of Health as data collecting institutions. It is noted that each institution use different concepts and methodology for data collection. Engaging both users and producers in the disability data production process, encouraging regular dialogue and establishing collaborative arrangements with local and international research institutions are avenues for utilizing the scarce resources for the development of disability statistics. The focus and direction of the development of disability statistics in Uganda calls for a sustained system of monitoring intervention that government and other development partners have to put in place.

The issues raised in this report will facilitate the process of harmonisation of concepts and definitions used while collecting disability data. It is noted that except for the Community-Based Rehabilitation Information pilot system under the Ministry of Gender, Labour and Social Development, there is little or no use at all of the ICF. The pilot system is ongoing and is expected to expand to other districts. It is hoped that this will enrich the process of harmonizing concepts with the Integrated Community-Based Rehabilitation Information System to provide meaningful results. The process of coordination is hereby called for.

This study examines a sharp decline of school attendance among white children in the Southern US after the Civil War. According to Census data, the school-attendance rate among whites in the Confederate states declined by almost half from 1860 to 1870, whereas the rate in Northern states was approximately stable. This shock left the South approximately three decades behind its antebellum trend. We account for little of this drop with household variables plausibly affected by the War. However, a select few county-level variables (notably the drop in wealth) explains around half of the decline, which suggests a systemic explanation. We adopt a model-based approach to decomposing the decline in schooling into demand versus supply factors. On the supply side, the region saw a decline in wealth and public resources, but we observe a stable relationship between time in school and literacy or adult occupation, which is not consistent with a contracting constraint on school quantity or quality. Nevertheless, further research is required to determine how much the contraction in school access affected attendance. On the demand-side, we present suggestive evidence of a decline in the return to school (measured by the relative wage of engineers to laborers). Relatedly, we see a “brain drain”: in longitudinally linked census samples, educated Southerners were more likely to migrate out of the South after the War.

The application of forecasting to health care is not new. A frequent issue in many Inpatient Rehabilitation Facilities (IRFs) is the fluctuating and unpredictable census. With scarce resources, particularly physical therapists and occupational therapists, this unpredictability makes appropriate scheduling of these resources challenging. This research addresses the issue of patient admissions in an inpatient rehabilitation facility attached to an 861 bed level-one trauma hospital. The goal is to develop a predictive model for the IRF's Census to assist in resource planning (e.g., labor, beds, and materials).

This article seeks to demonstrate a technique for using a Geographic Information System (GIS) to analyze US Census data to better understand potential library users and improve library service planning.

A GIS was used to link variables such as age, race, income, and education from the 2000 US Census with service area maps of two proposed branch libraries. Thematic maps were created for each of the census variables to display demographic information about potential library users within a three‐mile radius of the proposed libraries.

The GIS maps and their associated attribute data enhanced the ability to analyze and compare the demographics of potential users in the two library areas and identify significant differences. The data on age, race, education and income for residents in the two areas were combined with known library use indicators to help plan library services with the potential to attract different populations in the local community.

Provides practical information about downloading US Census data into a GIS to be able to present demographic data about potential library users both visually and quantitatively.