Last week, the All-Party Parliamentary Group (APPG) on Diversity & Inclusion in Science, Technology, Engineering and Maths (STEM) announced their next project after a call for ideas invited submissions from the public. The chosen project will be: Equality, Diversity and Inclusion (EDI) strategies in STEM. 

Read the full announcement

The scope of work will review the ways in which EDI policy is tackled in STEM organisations and the evidence behind this across the sector. The project is based on a submission from Professor Nira Chamberlain, immediate past president of The Mathematical Association.

In this guest blog, Nira sets out the EDI problem and explains why using a more scientific method will lead to more comprehensive and better informed policies.


Diversity in STEM

In 2020, several expert witnesses including myself were asked to join an online evidence roundtable organised by the All-Party Parliamentary Group (APPG) on Diversity & Inclusion in STEM. The topic to be investigated was inequity in the STEM workforce, both in academia and industry.

One of the points raised by the participants was the way the Equality, Diversity and Inclusion (EDI) Statistical Key Performance Indicators (KPIs) produced by organisations rarely reflect the lived experience of the underrepresented groups. These KPIs are usually in the form of a subjective study, questionnaire, and/or an empirical equation. 

When I left this meeting, I thought, "surely there must be a scientific way of solving this problem?"

Data science has come a long way during the last decade and its applications play an important role in industry and government. As a result, data science and data scientists have growing influence and power. Decisions made using data affect individuals and communities around the world in more ways than ever before.

In terms of EDI, data scientists can surely detect and challenge practices, ideas and privileges that reinforce inequality, or can they?

Equality of opportunity

American businesswoman, Leila Janah, was a daughter of Indian immigrants who came to the USA with little money. Leila believed that through effective EDI strategies, the talent of underrepresented groups could be fully unearthed. Leila famously said:

Talent is equally distributed, opportunity is not.

It is often argued that a pool of individuals is stronger if it is more diverse. This is because there is more creativity and greater innovation of ideas from diverse thinking and backgrounds. Talent is present throughout the group.

But what about equality of opportunity? We can look at this from a statistical point of view, and we can ask:

If all things are equal, what numbers do we expect to see?

On considering this problem, I derived this thought experiment:

  • A coin has two sides: heads and tails.
  • Tossing any fair pound sterling coin has a 50% chance of landing heads and 50% chance of landing tails.
  • Tossing any fair, non-pound sterling will also have a 50% chance of landing the equivalent of heads and 50% chance of landing the equivalent of tails.
  • Say we have 50 pound sterling coins and 50 euro coins and toss each one. We place all that land heads, or the equivalent, on a top shelf. We place all that land tails, or the equivalent, on a bottom shelf.
  • Once we have tossed all 100 coins, we would expect to a similar number of pounds and euros on each shelf. If there are more pounds on the top shelf, this would suggest that either the coins or the tosses aren’t fair.

This thought experiment can be used to demonstrate what we find in some organisations; the opportunity for the coins to be placed on the top shelf is not equal.

The problem with EDI policies

Organisations may be increasing the diversity of their workforces, but they may be missing out on policies that ensure all employees have access to opportunities to progress their careers.

The scenario set out at the end of the above thought experiment – where there are more pounds on the top shelf than any other type of coin – is closer to the lived experience of many employees from backgrounds underrepresented in STEM than the statistics published by organisations, government agencies and other bodies.

Understanding this gap will help to inform future strategies that effectively reduce inequities in STEM organisations.

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