Feminist Approaches to Measurement and Evaluation

Measurement and evaluation are foundational to the data and statistics used in public administration practice. But can these concepts be understood and practiced through a feminist lens? How does feminist theory and practice inform the collection of public data, the data questions public administrators ask, and the way that data is used in decision making? Acknowledging the social situatedness of this data, we will explore how feminist principles can be used along with “traditional” data science tools to improve understanding of current issues facing citizens.

This is a course about developing applied skills in data analysis for public administration officials, while engaging directly with the social implications of public data science. Students will learn and practice basic statistical data analysis skills and concepts, including probability distributions, mean and median, variance, standard deviation, standard error of the mean, hypotheses and P-values, type I/II errors and power, t-tests, one-way ANOVA, chi-square test and Fisher’s exact test, and odds ratios.

While understanding these statistical concepts is critical, we will focus on applying them to actual public administration data in a practical way. Through cooperative practice and shared learning, we will learn the most effective ways to explain key concepts and limitations of public data with a non-technical policymaker audience, and incorporate the questions of data feminism into decisions about data collection and reporting.