Why I believe in Family Science

Today I am publishing the first publicly available ranking of Human Development and Family Science programs in North America, at least the first ranking that I am familiar with.  Why did I go to the trouble of creating this ranking? Because I believe in human development, and in particular, family science, and you should too.

photo credit: Alain Bachellier via photopin cc

photo credit: Alain Bachellier via photopin cc

When I first got my job at Ohio State, I did not like the name of our department. Human Development and Family Science?  My degrees from Illinois and Penn State were both in Human Development and Family Studies. In all honesty, I thought family science was some kind of strange term for scholars that studied families, but were not rigorous researchers. What came to mind were cross-sectional, community-based studies, where the major topic of interest was some abstract concept associated with some other abstract concept. At the point I was hired, I had just gotten done working with an economist for two years, so my use of the term endogenous was at an all time high, as was my dismissal of scholarship that I put in the “family science” category. Sometimes I would talk about my program as “family studies” because I was embarrassed of the term.

Over time, however, the term family science has grown on me. Family science used to seem like this exclusive term, whereby you had to be in a particular club, or get your PhD from a particular program, to be a “family scientist”. But, now that I have learned more about family science, I realize that it is actually an inclusive term. Actually, my article using econometrics to examine the mental health consequences of cohabitation vs. marital dissolution is family science. And so is my article looking at how playing with a “fake baby” determines your co-parenting after the real baby is on the scene. Family science is diverse, interesting, and includes a range of research topics related to the family, from family demography to family psychology, from qualitative to quantitative methods, from large, secondary datasets to small, community samples.

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