FST JOURNAL

After the formal presentations, the speakers joined a panel to answer questions from the audience on a range of topics, including: current changes; publishing data; corporate commitment; visibility.

Why has the current push on tackling racism in science and technology occurred – and what needs to happen next? The current ways in which communities are banding together is a source of hope. There is a sense of momentum, and people are listening. One change is that many organisations are openly using the word racism, which makes a big difference. People are starting to take it more seriously and thinking how to be better allies.

Data will make a difference – companies should report their ethnic pay gap in the same way as their gender pay gap, and Government could legislate for this – as well as publishing their own data on differences in educational outcomes. There is still fragmentation on tackling the issues, and an important next step is much more coordination.

Publishing data, while essential, is not sufficient – to avoid these procedures becoming mere tick-box exercises, conversations are needed between people. Some of these may start as hostile, but they will become easier with time. One problem is that for some organisations, the data they have is poor or fragmented.

One aspect of the Mellon Mays programme in the USA is that organisations commit to self-assessment and analysis and then publish a plan. The UK HE sector should have a conversation about what might work here. Working with other communities is vital to drive forward the changes needed. Bringing younger secondary school students into universities such as Cambridge can help them seem more accessible to those from ethnic minorities.

Increasing visibility of Black researchers is key. What did the panel find useful in their early careers? Items mentioned included seeing positive role models, leading to raised aspirations, and the huge benefit of mentorship. Some people have a fear of self-certifying ethnicity data. There are a number of reasons for this and institutions need to understand why people are not disclosing their data. There are real people under the data, and there is a relational aspect to disclosing data.