Gender Decoder is a simple tool that checks the text of job ads to see if it includes any subtly gender-coded language.

'subtly gender-coded language' refers to language that reflects stereotypes about men and women, like women being more nurturing and men more aggressive. A 2011 research paper showed that subtly masculine-coded language in ads can put women off applying for jobs.

For more info, or to use the tool: https://gender-decoder-nextjs.vercel.app/

This project is a port of the original project (written in python) to Next.js + added support for multiple languages.

All of the credit should go to Kat Matfield and the original project.

The original project hade a MIT license but I decided to change that for this implementation. It's now GNU GPLv3.

First, install and setup the environment:

yarn install
yarn prepare  # installs the git commit and push hooks

Run the development server:

yarn dev

Open http:https://localhost:3000 with your browser to see the result.

Start by adding a new locale to the Next.js application updating the locales keys in the following files:

• next.config.js
• lingui.config.js

The wordlists are located in src/decoder/wordlist/{locale}.ts with the locale corresponding to the language.

To add a new language simply copy a wordlist and modify it to the new language.

Run yarn lang:extract to extract all of the strings that needs translation. Then simply update the generated files under src/translations/locales/{locale}/messages.ps.

Run yarn lang:compile to manually compile the language (it will also be done when running yarn build)

The easiest way to deploy this app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.