for improving gender options in dropdowns
See here: https://help.github.com/articles/using-pull-requests/
And submit here: https://github.com/anne-decusatis/genderamender/pulls
Code of Conduct here: https://github.com/anne-decusatis/genderamender/blob/master/code_of_conduct.md
(You can also submit an issue here: https://github.com/anne-decusatis/genderamender/issues)
Please keep in mind: words like "cis" and "trans" are ADJECTIVES, NOT NOUNS. Your users should be able to pick more than one list item.
See the simplest of examples in action here: https://anne-decusatis.github.io/genderamender/examples/simple.html
Tech companies have historically been pretty terrible at recognizing and supporting gender diversity in their users. We thought that if there was a standard to point to that was easy to follow, tech companies might start to follow it. It's on GitHub so anyone can contribute - we don't claim to know everything about gender.
I (Anne) work for a tech company that takes into account our users' gender in recommendations. Everyone except me thought it was enough to have "male", "female", and "other" (only using "male" and "female" in recs) - I wanted some kind of self-identification for people. The hashtag #genderUX happened on Twitter around then, and I showed several of my coworkers http://43epnd.axshare.com/gender.html. We're a social networking company, and people kept saying things like "well, we need at least the orange one" or "we need this to work for most people (who are male or female)." When I filed a bug saying that our gender options were broken, I was told "this is really a product decision, you need a product manager," but all the product managers were busy. Eventually I got someone in Trust and Safety on board, but we didn't always have the same perspective on what was necessary to be inclusive and show our good intent.
A couple weeks later, I got in touch with my old friend Rowan, and was telling them about my frustrations, and asked them what they thought an ideal set of gender options would be. Then, we started trying to implement it in a way that didn't require a lot of complicated text processing.
@rowanlupton and @precisememory