Textio

@rrhoover @jensenharris People want every use case! We recently created a beta explicitly for recruiting email because we saw that people were putting a lot of related content through Textio already. We have seen recruitment and other marketing content, sales content, course syllabi, pitch decks, love letters... but we are trained on and promise to be great at talent and hiring docs.

@kieransnyder You're on to something here. Would totally use this for any kind of content, reminds me of Hemingway Editor. Do you have any plans to support additional languages, let's say German?

@zedpelin We will support other languages, but not quite yet. I started my tech career in internationalization and multilingual support is important to me, but we're not quite ready. (We support regional tailoring for different varieties of English right now.) Thanks for the kind words!

@kieransnyder Hey! It's been three years since this comment so I hope you are much closer to supporting German now. Right? :)

@pawtiko Me too. Until I see the real data I'm going to assume those are stereotypes and therefore — sexist.

@ashocka18 @pawtiko Hi! Textio is a quantitative system. It starts by looking at many previous job listings and information about who has actually applied for them,. Then Textio finds the patterns that consistently drive various application and hiring outcomes. Language that is judged "masculine" or "feminine" is language that has statistically driven high proportions of male or female applicants for similar jobs in the past. When a job listing comes in to Textio, Textio compares it with other similar job listings whose previous outcome is known. Inclusive language ("green") language is language that statistically draws more applicants, draws more highly qualified applicants, and fills roles faster. Masculine and feminine language drive higher %s of male and female applicants respectively compared to the baseline for the job. Negative ("red") language is language that everyone across demographic groups disprefers.

@kieransnyder @pawtiko That's nice, but I still don't see any data. @rrhoover what is PH's stance on this? Problems I see with this startup: Lack of any data that would support your stereotypical claims. The copy misuses the word "gender bias", probably to earn sympathy of the less informed. "Gender bias" means "unequal treatment in employment". Using certain words in a job description will not solve this problem. Changing the mentality of those in HR will solve this problem. This startup's definition of "genders" is "male or female". This means they're actively discrediting all other gender identities. Again, not helping the diverstiy problem at all. Taking on this challenge, the founders should have predicted the PC backslash and have the data ready (and a PR person able to handle it).