Same-occupation couples: new estimates

Alexander Fishkov, Ph.D. student Computer Science

In this post, we will revisit the topic of occupation and marriage dependency, and same-occupation couples in particular. Recently, new five-year American Community Survey data was released by IPUMS USA. This is the most comprehensive version of the survey, having the widest coverage of the population (even in smaller areas).

Same-occupation couples

As before, agricultural workers and farmers have a strong tendency to marry within their field: more than 25 percent. Comparatively, management and sales professionals only marry within their field 20 and 17 percent of the time respectively. The lowest rates of same-occupation marriages are found among construction, repair and extraction workers.

Marriage preferences of different occupations

On the chart above, each link (arc) represents the number of couples of different occupations. Circular segments around the chart group people by occupation. You can click on them to hide particular occupations. After that, occupation label will appear in the list of filters and you will be able to enable it again. You can also hide some links on the chart by setting the minimum number of couples using the slider. Note that some occupations may disappear entirely from the chart if this value is too high.

High-level view

In this chart, we extracted a “heavy” subgraph of the original diagram showing the strongest connections (in which more than 10 percent of one occupation prefer the other). Nodes represent occupational groups, with the size of each node indicating the number of workers in our scope. Links between nodes show the proportion of “source” occupation workers married to a person from the “target” occupation.

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About Alexander Fishkov

Alexander Fishkov, Ph.D. student Computer Science

Alexander is a Ph.D. student in Computer Science. He currently holds B.S. and M.S. degrees in Applied Math. He has experience working for industry major companies performing research in the fields of machine learning, data mining and natural language processing. In his free time, Alexander enjoys hiking, Nordic skiing and traveling.

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