This repository contains some libraries to help with trying to model the statistics of hiring faculty as well as a python notebook showing the use of this code to answer a question about hiring strategy.
Being a particle physicist, I'm natrually inclined to answer statistical questions with Monte Carlo methods. This code attempts to apply those methods to the question of faculty hiring. The python notebook included in the repository specifically tries to answer the question, "What hiring strategy should one use when trying to hire equitably for gender?" (I will apologize in advance because this code assumes gender is binary, so that the mathematical definition of equity can be 50% of each gender.)
You can run the "hiring strategy" notebook interactively here: |logo|
You can run the "department" notebook interactively here: |logo2|
And you can run a notebook with different voting methods implement here: |logo3|
.. |logo| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/klannon/faculty_hiring/master?filepath=notebooks%2Fsearch_strategy.ipynb
.. |logo2| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/klannon/faculty_hiring/master?filepath=notebooks%2Fdepartment.ipynb
.. |logo3| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/klannon/faculty_hiring/master?filepath=notebooks%2Ftennessee_example.ipynb
This project has been set up using PyScaffold 3.2.3. For details and usage information on PyScaffold see https://pyscaffold.org/.