Hi all, We hope that you can join us for the first Applied Statistics Workshop of the term this Wednesday, January 26th when we will be happy to have Maya Sen from the Department of Government. She will be presenting joint work with Adam Glynn, also in the Department of Government. You will find an abstract below. As always, we will serve a light lunch and the talk will begin around 12:15p. (Note that this talk is not on the website schedule yet due to technical issues.) "Female Socialization: How Having Daughters Affect Judges' Voting on Women's Issues" (with Adam Glynn) Maya Sen Department of Government CGIS K354 (1737 Cambridge St.) Wednesday, January 26th 12 noon Abstract: Social scientists have long maintained that women judges might behave different than their male colleagues (e.g., Boyd et al. (2010)). This is particularly true when it comes to highly charged social issues such as gender discrimination, sexual harassment, and the status of gender as a suspect classification under federal law. Less studied has been the role that a judge's family might have on judicial decision making. For example, we may think that a male judge with daughters might have different views of gender discrimination and sexual harassment than a male judge without any daughters. This paper takes a look at the question causally by leveraging the hypothesis that, conditional on the number of total number of children, the probability of a judge having a boy or a girl is independent of any covariates (Washington 2008). Looking at data from the U.S. Courts of Appeals, we find that conditional on the number of children, judges with daughters consistently vote in a more conservative fashion on gender issues than judges without daughters. This effect is particularly strong among Republican appointed judges and is robust and persists even once we control for a wide variety of factors. Our results more broadly suggest that personal experiences -- as distinct from partisanship -- may influence how elite actors make decisions, but only in the context of substantively salient issues. Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/