  Background: Contemporary software development organizations lack diversity
and the ratios of women in Free and open-source software (FOSS) communities are
even lower than the industry average. Although the results of recent studies
hint the existence of biases against women, it is unclear to what extent such
biases influence the outcomes of software development tasks.
  Objective: This study aims to conceptually replicate two recent studies
investigating gender biases in FOSS communities \textit{ to identify whether
the outcomes of or participation in code reviews (or pull requests) are
influenced by the gender of a developer.} In particular, this study focuses on
two outcome aspects (i.e., code acceptance, and review interval) and one
participation aspect (i.e., code review participation) of code review
processes.
  Method: We will augment the dataset used in the original studies with code
reviews /pull requests created during recent years. Using this dataset, we will
train multivariate regression models to accurately model the influences of
developers' genders on code acceptance, review intervals, and code review
participation.
