Welcome! I'm really excited to see you here! Thank you for taking the time to contribute! Reading for Gender Bias welcomes all contributions from anyone willing to work in good faith. No contribution is too small and all contributions are valued.
This document is a set of guidelines for contributing to Reading for Gender Bias on GitHub. These are guidelines, not rules. This guide is meant to make it easy for you to get involved.
Implicit gender bias in evaluations negatively impacts women at every stage of her career. The goal of this project is to create a web-based text analysis tool that scans and reveals language bias associated with evaluations and letters of recommendation written for trainees and applicants. The tool will provide a summary of potential changes to the writer to help them remove bias. The hope is that by bringing awareness to the existence of implicit bias, we can change how evaluations for women are drafted and judged, thereby providing a concrete way to tackle gender disparities.
This project adheres to Mozilla Community Participation Guidelines. By participating, you are expected to uphold this code. Please report unacceptable behavior to mollie@biascorrect.com.
To run the current code:
- Ensure you have a python installation on your system
- Obtain a copy of the repository
- Set up a python virtual environment for the project (optional but recommended)
- Go to the project directory and run
pip install .
To install the project so that changes are reflected in the installed script and library, run pip install -e ..
For your reference, the entire automated test suite can be found in the tests directory.
Installation:
- In order to use the test suite, you must have the python packages
pytestandpylintinstalled on your machine. - To install these, run
pip install -e .[dev]. - Or, to install them individually, run
pip install pytestandpip install pylint.
To test all of the detectors at once, execute ./run_tests.sh. This script calls pytest and pylint.
To run an individual detector test, run (for example) pytest tests/test_publication_detector.py.
Unsure where to begin contributing to Reading for Gender Bias? You can start by looking at good first issue and help wanted issues.
We are using python for our programming language. There is a folder of letters for testing code here.
You can also take a look at the Roadmap to get a sense of where we are going and to start making your own milestones and issues.
Please reach out if you have questions. I am new to programming, but will try to answer your questions as completely and quickly as I can. I am also in class, so if you don't immediately hear from me, it's not you, it is definitely me.
Once you've identified one of the issues above that you feel you can contribute to, you're ready to make a change to the project repository!
- Fork this repository. This makes your own version of this project you can edit and use.
- Make your changes! You can do this in the GitHub interface on your own local machine. Once you're happy with your changes...
- Submit a pull request. This opens a discussion around your project and lets the project lead know you are proposing changes.
First time contributing to open source? Check out this free series, How to Contribute to an Open Source Project on GitHub.
Please stay on the lookout for any potential issues that might cause problems for the project. These could be problems in code, content omissions, or issues with the functionality or design.
Notice a mistake? Please file any bugs, requests, or questions in our issue tracker!
- Use a clear and descriptive title for the issue to identify the problem.
- Describe the problem and where you encountered it.
Have questions? Reach out to me on Slack, readingforbias.slack.com, twitter, or by email mollie@biascorrect.com.
Please add your name and to the contributors list. I want to be certain that everyone's contribution is recognized!
Thank you!