> For the complete documentation index, see [llms.txt](https://opora.gitbook.io/opora-health-documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opora.gitbook.io/opora-health-documentation/opora-core-for-health-ai-funding/gender-bias-and-fairness-evidence.md).

# Gender, bias, and fairness evidence

Funders expect you to think about **who your system works well for, and who it might disadvantage**.

#### What you need to show

* Whether gender or other characteristics are relevant to your system.
* How representative your data is.
* Whether performance differs across groups.
* What you do if differences are found.

#### How OPORA Core supports this

OPORA Core enables:

* Structured bias checks as part of validation workflows.
* Tracking of performance across relevant subgroups.
* Documentation of decisions taken when bias is identified.
* Ongoing monitoring as data and models change.

This makes fairness something you measure, not assume.