The unequal commute: Comparing commuting patterns across income and racial worker subgroups

The spatial dimension of the journey-to-work has important implications for land use and development policymaking and has been widely studied. One thrust of this research is concerned with the disaggregation of workers into subgroups for understanding disparities in commute. Most of these studies, however, were limited to the disaggregation by single socioeconomic class. Hence, this research aims to examine commuting disparities across commuter subgroups stratified by two socioeconomic variables—income and race—using a visual analytics approach. By applying the doubly constrained spatial interaction model to the 2014 Longitudinal Employer-Household Dynamics data, this research first synthesizes commuting flows for Downtown Houston workers across income-race subgroups at the tract level in Harris County, Texas, USA. It then uses bivariate choropleth mapping to visualize the spatial distributions of major Downtown Houston commuter neighborhoods by income-race classes, and significant commuting disparities are identified across income-race subgroups. The results highlight the importance of considering income and race simultaneously for commuting research. The visualization could help policymakers clearly identify the unequal commute across worker subgroups and inform policymaking.

A Critical and Extensive Review of the Historical Rise and the Contemporary Resurgence of Interest in Positivism in Geography

The positivist methods of explaining geographical phenomena enjoyed prominence and revolutionized the methods of geographical research up to the 1950s where the criticisms were largely that the methods cannot account for any role in human geography and the subsequent rise of humanism as an alternative mode of explanation. These critiques and the introduction of many concepts in humanism inadvertently slowed down the progress in seeking for acceptable scientific methods to explain human experiences in geographical research. These criticisms in the 1980s and 90s reduced the popularity and application of the quantitative methodologies which were powerful research techniques in human geography. Geography by its nature is a dual discipline with one half on physical and the other on human geography. Human geographers have used quantitative methodologies to study a multitude of topics including demographics, migration, housing and settlement patterns and ethnic segregation. Human activities like migration, journey to work, retail capital patronage, have adopted some element of scientific laws and models have been focused on transportation, migration, settlement development, innovation diffusion, population growth and distribution, urban land use etc. The shortcomings of the philosophy of humanism have not provided a good alternative in explaining geographical phenomenon and has over time become the gains of the positivist school of thought. The resurgence in the interest in positivism as a tool for explanation of geographical phenomena bores down from the fact that the humanistic methods is laced with subjectivity, the language of discourse is abstract and difficult to comprehend while the logical sequence of the positivist methods make the approach real and achievable.

Managing a Law Firm Research Service from Home: from ‘What's Zoom?’ to Trainee Induction Week from a Bedroom

In this article Ian Hunter considers his experiences, learning points and recommendations on running an international law firm research service from home for 6 months, after being sent home at one hour's notice. In the article he considers working from home, including the psychological benefits of having a ‘journey’ to work, providing a research service and a library service, managing a team and the use of communications technology.

It’s getting late today, please do the laundry: The influence of long-distance commuting on the division of domestic labor

The study examines the effect of long-distance commuting on the division of domestic labor in heterosexual couples. A long journey to work can affect other areas of life. Commuters often have lower life satisfaction and their intimate relationships may be impaired by mental stress. When looking at domestic labor the question arises of who is in charge of managing the household and childcare. Do women still adopt the “lion’s share of housework” or take over the “second shift” if they spend part of the day on long commutes to work and back home? A long commute is defined as a journey to work of at least 45 minutes, daily or several times a week. We present the results of pooled regression analysis and fixed effects regressions conducted on data from the German Panel Analysis of Intimate Relationships and Family Dynamics (pairfam) for the years 2013, 2015, and 2016. The pooled analysis suggests a moderate association between a woman’s long commute and her partner’s engagement in housework and childcare, especially when she commutes daily. Instead of living ‘reversed roles’, the partners share such tasks. However, when the association between a woman’s long commute and her partner’s engagement in childcare is estimated exclusively with fixed regression, it remains significant. If the man is a long-distance commuter, most often his partner is solely responsible for all household tasks. Relative labor market position and income distribution within the couples, as well as adherence to gender roles explain the effects of long-distance commuting on labor division.

Negative Spatial Autocorrelation: One of the Most Neglected Concepts in Spatial Statistics

Negative spatial autocorrelation is one of the most neglected concepts in quantitative geography, regional science, and spatial statistics/econometrics in general. This paper focuses on and contributes to the literature in terms of the following three reasons why this neglect exists: Existing spatial autocorrelation quantification, the popular form of georeferenced variables studied, and the presence of both hidden negative spatial autocorrelation, and mixtures of positive and negative spatial autocorrelation in georeferenced variables. This paper also presents details and insights by furnishing concrete empirical examples of negative spatial autocorrelation. These examples include: Multi-locational chain store market areas, the shrinking city of Detroit, Dallas-Fort Worth journey-to-work flows, and county crime data. This paper concludes by enumerating a number of future research topics that would help increase the literature profile of negative spatial autocorrelation.