The GOV.UK feedback form was receiving a lot of spam requests. We developed a machine learning model to detect spam responses — here is how we created it.
The Race Disparity Unit at the Cabinet Office Equalities Hub have analysed different approaches taken by national governments to understanding how they compare on issues such as ethnic diversity and cultural identity.
Richard Laux outlines the 3 main reasons for collecting data about people’s ethnicity and identifies 6 principles for collecting these to meet all users’ needs.
...look for specific accessibility content issues. We wrote it in Python, as it’s a GDS-supported programming language, and structured the code in a way that allowed us to write and...
...new technology. This includes adding more data related content to the Technology Code of Practice, the Service Manual and the Design System. Supporting the government data communities by bringing the...
...techniques to obscure sensitive or private information in datasets. These include statistical methods, deep learning techniques and natural language processing for the data types above. Typically they can be summarised...
...of the victim. New pages that we’d like to develop include loneliness, and access to gardens and other green spaces. New data pages in development ‘Ethnicity facts and figures’ includes...
...presented a pilot app using machine learning to assist triaging in accident and emergency. Queen’s Hospital sees over 290,000 emergency department admissions per year. The app aims to support NHS...
...inform our practice of combining multiple years’ data to enable us to analyse smaller ethnic groups Get involved Email us or leave a comment below if you are interested in...
...combining data for more than one year. I'd recommend that those responsible for data about teachers, children’s social workers, police and firefighters should take steps to include the Chinese group...
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