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/