Why inclusive language matters

The type of language used in job descriptions makes a difference in who applies for a job or not. Women are often less likely to apply for higher-paying roles. Those who are older may shy away from jobs that call for "a go-getter attitude" or for someone to be "dynamic".

Why is this tool important?

Exclusionary language in job descriptions can cause people to feel excluded from jobs they are qualified for. By identifying these pieces of language and suggesting alternatives, JADE supports more inclusive hiring practices.

More recently, JADE now covers more inclusive language across various industries and contexts. It now flags a much wider array of exclusionary language, making it useful far beyond job descriptions.

What do these categories mean?

The tool flags language across five categories of exclusion:

Ableist

Language that assumes a particular physical or cognitive ability, excluding people with disabilities.

Gendered

Language that assumes or reinforces binary gender roles, excluding women, non-binary and gender-diverse people.

Ageist

Language that discriminates based on age, often excluding older or younger candidates.

Othering

Language that positions certain groups as outside the norm, including terms that invoke cultural appropriation or treat minority experiences as exceptional.

Exclusionary

Language that creates unnecessary barriers or implies certain people are less welcome, without falling neatly into the categories above.

How does it work?

JADE uses a natural language dependency parser to search for verbs that are part of the US Department of Labor's ableist language lexicon.

The gendered terms come from research into gender in job descriptions in publishing. The ageist terms draw from parallel research into ageist language in the same context.

Additional terminology not included in the original lexicons has been added and updated to reflect more inclusive language. Coverage continues to expand.

What you need to know

We don't keep your text. We store aggregate statistics (number of instances found, the categories they belong to, and similar metadata) but no personally identifiable information and no job descriptions you submit.

Who built this?

Dr Miriam J Johnson. Academic of publishing and marketing, co-founder of a publishing technology startup, and researcher in social media and online language. She has written on exclusionary language in publishing job descriptions and has a broad interest in how language shapes inclusion across industries.

What's next?

We are working on expanding JADE's detection capabilities and deepening sector-specific benchmarking. Logged-in users can already track check history, cumulative stats, and score trends over time.

Contact

Questions, suggestions, or feedback: reach us at hello@jadecheck.co.uk.