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://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.