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This paper seeks to provide researchers and librarians with an overview of the US Census Bureau's American Community Survey (ACS), with a specific focus on practical issues that users must face when choosing and using ACS datasets.

Each of the following issues are explored subsequent to a general overview of the ACS: choosing among census datasets from different census programs, interpreting and choosing between the different ACS period estimates, selecting census geography, understanding and recalculating margins of error, and accessing the data. Samples of ACS tables and formulas for creating derived estimates are used to illustrate how to interpret and work with the data.

The ACS datasets are fundamentally different from the decennial census as they are period estimates created from rolling sample surveys. The ACS has a steeper learning curve; this complexity is due in part to the number of choices users must make between datasets, but the primary challenge is learning how to understand and work with estimates as opposed to population counts.

While other papers have discussed the benefits and challenges of the ACS, this paper is structured around the practical issues that researchers must face when using it. Special consideration is given to calculating derived estimates using spreadsheet formulas, as this is a key task that many users will need to perform and spreadsheets are the most likely tool users will employ to manipulate the data.

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.

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.

In the United States, many arguments for mass transport often focus on its benefits to the environment or in terms of congestion relief. This chapter instead looks at direct micro-scale and meso-scale economic and social benefits by identifying occupations, industries, and demographic groups that are both growing and can benefit from transit. In using this form of local-scale identification of unique economic circumstances, government planners, elected officials, and academics can create a practical, GIS-focused approach to increase the utility and acceptance of mass transportation in the United States.

Using a GIS-based approach with US Census and US Labor Department data, the chapter focuses on local growth sectors in the economy, then identifying their transit-usage patterns. Additionally some GIS are used to identify concentration areas of both occupations and transit usage, along with areas of likely employment for those individuals. Locally this creates “micro-climates” or hot spots for favorable views and usage of transport. These micro-climates can be duplicated in other similar areas to increase utilization, and therefore return on investment, of public transportation.

For denser areas, affluent downtowns, and areas which are accessible to hospitals and universities, the primary growth engines of the current US labor market, transit has a positive correlated relationship. Additionally, recent immigrant groups, particularly those with limited English speaking ability, have also shown a correlated growth in transit usage. By identifying these areas with GIS, transit can better align its services to needs and improve it return on investment.

The United States has had a fifty-year-long negative view of public transport outside of major urban areas. By identifying groups with positive correlated use of transit, the return on investment and public perception of its use and environmental sustainability can mesh with land use planning and perceived quality of the service. In so doing, transit use may be encouraged.

The United States is faced with very high petrol prices relative to its history, and somewhat lesser incomes among its sub-age-30 work cohorts. This has encouraged density. However, in order to provide for this increased demand, there must be an increase in both supply and politically perceived value in its investment. This chapter seeks to be an early pragmatic model in valuing public transport at a local level.

Purpose: For deaf people who use American Sign Language (ASL), including cancer survivors, there are documented reports of difficulties in accessing and understanding health information. More than five years ago, a local breast cancer knowledge study with deaf signers found that only 23% of this sample cited the Internet as a source of health information. More research is needed to understand the current trends of a nationwide adult sample of deaf people’s experience with seeking and understanding health information across technology-mediated platforms.

Methodology/Approach: The Health Information National Trends Survey in American Sign Language survey included sections on health status, Internet use, and social media. We used several approaches to recruit deaf people across the USA, including Hawaii, Alaska, and Puerto Rico. The survey was administered online, in person, or through videophone. Following data cleaning, we conducted multiple logistic regression analyses, controlling for demographic factors associated with eHealth-seeking behaviors. The outcome variables of interest were Internet use and sharing health information on social media.

Findings: A total of 713 deaf people in USA (M = 49 years old; SD = 19) provided informed consent and took the survey. Half of the participants had a college degree. Twenty percent of the sample included those who self-identified as lesbian, gay, or bisexual and 38% who were people of color. White, educated, or younger deaf adults were more likely to cite the Internet as the first source of health information. Although all sub-groups were comparable in using social media, younger or ASL/English bilingual deaf adults were more likely to actively share health information through social media. While perceived trust in health information on the Internet did not differ across subgroups within the deaf sample, frustration in finding and understanding information was strongly linked to increasing age as well as those who prefer using ASL only. Users of YouTube for health-related information were likely to be younger or female.

Conclusions: Deaf users of eHealth information are diverse in terms of language usage, which affects their perception of accessing and using health information across technology-mediated platforms. While using YouTube for health appears to be accessible to deaf people, further improvements are needed to make health information sharing through social media inclusive of people who prefer ASL only. The addition of multimodal delivery features (text, audio, and video) in social networking sites has the strong potential to improve health information access and inclusion for all groups, including deaf ASL users. To make online health information inclusive of all groups, materials need to be accessible and easy to understand by all groups.

The purpose of this paper is to describe empirical research intended to fill the perceived gap in practical guidance methodologies for assessing resilience.

To do so, an interdisciplinary team of researchers studied landslide risk in four different communities of Central and Eastern Nepal using a case study approach. Two case studies on flood-affected communities were developed for comparison sake in more urban areas. Methods combined qualitative participatory approaches to develop indicators of resilience as well as a household survey and focus group discussions for collecting data on the indicators.

What the research results demonstrate is a relatively straightforward and simple means for obtaining data on the state of a community's resilience as a relatively simple “snapshot” of resilience at one period in time, assuming that resilience is an outcome that can be improved over time with the “right” set of interventions.

The main limitation of this research is that it focussed mainly on outcome indicators; although some process indicators of resilience were identified (i.e. grazing management practices, skills training, organizational skills and learning through education), these need to be more comprehensive and validated through community consultations.

The paper provided data and a straightforward methodology for measuring resilience and has thus contributed to the literature on this topic, while providing practical ideas for future research on resilience building measures and indicators.

The assessment of ecosystem services (ES) in urban areas can be an important policy instrument for both strategic directives at national and regional levels and concrete actions at municipality level. A unifying underpinning framework that combines different administrative levels through a common, consistent basis would greatly facilitate the mainstreaming of such an instrument. Three key concepts underpin this framework: urban ecosystems, nature-based solutions (NBS), and ES. First, NBS are acknowledged as the ecological assets that in the urban context can provide ES, meant as complex processes made possible through the existence of natural and seminatural systems at various scales. Second, the classification of urban ecosystems needs to be consistent with the treatment of urban areas in ecosystem accounting and with NBS levels of intervention and primary objectives. Third, by serving societal challenges, it is important to clearly frame the strategic drivers of change: whether it concerns management practices of current land use or radical conversions in land use. Finally, once such a framework will be in place, it can facilitate sustainability assessment in urban ecosystems by quantifying the presence of NBS, whose creation/maintenance assure the delivery of ES. The purpose of this chapter is to theoretically frame an ES-based approach, but this is only a first step. Many more steps are required on to concretely put this framework in practice at different administrative levels, such as strategic planning and policy setting (at national level), and urban, peri-urban, and coastal development (at municipal level).

Postdocs make up a significant portion of the biomedical workforce. However, data about the postdoctoral position are generally scarce, and no systematic study of the landscape of individual postdoc salaries in the USA has previously been carried out. The purpose of this study was to assess actual salaries for postdocs using data gathered from US public institutions; determine how these salaries may vary with postdoc title, institutional funding and geographic region; and reflect on which institutional and federal policy measures may have the greatest impact on salaries nationally.

Freedom of Information Act Requests were submitted to US public universities or university systems containing campuses with at least 300 science, engineering and health postdocs, according to the 2015 National Science Foundation’s Survey of Graduate Students and Postdoctorates in Science and Engineering. Salaries and job titles of postdocs as of December 1, 2016, were requested.

Salaries and job titles for nearly 14,000 postdocs at 52 US institutions around December 1, 2016, were received. Individual postdoc names were also received for approximately 7,000 postdocs, and departmental affiliations were received for 4,000 postdocs. This exploratory study shows evidence of a postdoc gender pay gap, a significant influence of job title on postdoc salary and a complex relationship between salaries and the level of institutional National Institutes of Health/NSF funding.

These results provide insights into the ability of institutions to collate and report out annualized salary data on their postdocs, highlighting difficulties faced in tracking and reporting data on this population by institutional administration. Ultimately, these types of efforts, aimed at increasing transparency regarding the postdoctoral position, may lead to improved support for postdocs at all US institutions and allow greater agency for postdocs making decisions based on financial concerns.