Just how diverse is the scientific workforce?

Earlier this month, the Royal Society released a report which looks at the diversity of the scientific workforce. As part of a four year work programme of the Society, the report focuses upon understanding the range of people within the scientific community with a view to use this information to learn more about the barriers and challenges people face when entering and progressing within science and what can be done to address them.

A key issue that the report faced from the offset is that the definition of the scientific workforce itself can change depending on who is talking about it. Those working in government, research or across relevant organisations all use varying definitions, leading to segregated views and understandings of the problems relating to diversity and entry and retention of people within science. As the report rightly points out, generating a standard definition would help to encourage robust comparisons between work into this area and improve understanding. For the Society’s programme, their definition of scientific workforce is taken ‘to comprise all those for whom their scientific knowledge, training, and skills are necessary for the work that they do.’

Bringing together three separate analyses of different datasets, the report describes the diversity of the UK’s scientific workforce in areas of science, technology, engineering, mathematics and medicine (STEMM) and looks at issues relating to gender, ethnicity, disability and socio-economic background. These three analyses focus upon particular areas – 1) comparison of the overall UK workforce with the scientific workforce; 2) career progression using data from mid-career individuals and 3) university sector and progression of individuals from higher education.

Despite complexities and difficulties in interpreting this sort of data, there are many key patterns that the report directs us to. 20% of the UK workforce uses science and the knowledge and training it has provided them with to do their jobs, and generally these people tend to work in the private sector, public sector or education. Those working in medical professions account for 40% of the science workforce, which meant that this had weighting effects on some of the reported results. As such, the report displays data including the medical sector and without, as often removing this sector highlighted less diversity within the science workforce than when it was included (e.g.  %  of women in science workforce including medical sector: 50.3%, without medical sector: 39.6%)

For issues relating to gender, whilst women weren’t found to be under represented in science as a whole, this overall trend varied with socio-economic status or career stage. For example, women were found to be very under-represented in senior career positions. However, this overall conclusion that women aren’t under-represented in science goes against other claims from a WISE report that women make up only 13% of the science workforce. These different conclusions from these different reports could be due to varying definitions of the ‘scientific workforce’, the differences with socio-economic status or other factors relating to the individual. This highlights the complexity of understanding these issues and this type of data.

Ethnicity within the scientific workforce was described as mostly similar to the rest of the UK workforce, with White British, Asian and Asian British representing the largest groups. Despite these general trends, the picture is very complex with ethnic group representation altering with career stage. For example, Chinese groups are over represented at the senior career stage whilst black and black British people were more underrepresented at senior levels.

Those with disabilities were found to be no more under represented within the science workforce compared to the whole, but they were found to be less likely to have senior positions.

Socio-economic status was also found to have an impact on an individual’s ability to enter the scientific workforce. Generally those from lower socio-economic status backgrounds took longer to enter the science workforce after leaving full time continuous education, but the relationship between childhood household income and likelihood of working in science is extremely complex.

As the report clearly shows, understanding the diversity of the scientific workforce is very complex to understand and varies so much depending on a huge array of factors and circumstances often unique to the individual. Drilling down to specific disciplines and subjects further complicates the matter. However, building up a picture of the STEM/STEMM workforce is integral if issues surrounding diversity, equality and entry and progression in science are to be addressed. To finish, the report laid out several recommendations for future analyses:

• ‘An agreed definition of the scientific workforce used across and by government departments and dataset owners would allow data to be compared and help improve understanding of entry into and progress through the STEMM workforce for underrepresented groups.
• Consistency between the definitions of and variables within diversity characteristics which would allow better data collection and analysis of multiple datasets on the STEMM workforce.
• Improved links between existing datasets to better understand the diversity of the scientific workforce and community, from school through to vocational, further and higher education and into the workplace, across the full range of STEMM sectors.
• Better data for the private sector to build a full picture of the scientific workforce in relation to diversity and entry into and progression within the scientific workforce.’

You can find about the British Ecological Society’s work into diversity and equality in ecology here.