Experience of a plant scientist analysing complex human data

By Astrid Wingler, Professor of Plant Biology and Chair of Self-Assessment Team, School of Biological, Earth and Environmental Sciences (BEES)

Professor Astrid Wingler, BEES

Writing a departmental Athena SWAN application requires in-depth data analysis on diverse aspects, such as staff recruitment, career progression and student degree attainment. As scientists, we’re used to dealing with lots of numbers in large Excel spreadsheets, so all of this should be easy; but things did not turn out as straightforward as expected.

There was a lot I had to learn about School of BEES and UCC, especially as I’ve only been here two years and the procedures at UCC still confuse me. For example, it turned out that the students on the nine different undergraduate BSc programmes we offer in BEES are registered using 21 (!) different degree codes. I would never have been able to work this out myself, and I am grateful for the patient support provided by the Systems Administration Office.

 All data for the application have to be gender disaggregated, but how does one decide who’s “female” and who’s “male”? Am I really dealing with “gender” here, or are we just making assumptions about a person’s sex based on their name? As a plant scientist, I’m not used to dealing with gender issues, and I’m feeling slightly uneasy about having to pigeonhole humans according to assumed gender.

Plant Science staff and students at Tozer Seeds as part of a field course earlier this year (https://www.ucc.ie/en/bees/news/plant-science-london-field-course.html)

I also learn that staff questionnaires and the questions asked in focus group discussions need “ethics approval”. Well, I’m used to considering biological safety issues, but questions of morality rarely arise when I’m doing experiments with plants. All questionnaire responses need to be anonymised, which isn’t necessarily that easy. How can the responses be presented accurately and without hiding important statements, while also ensuring that individuals cannot be identified? And how does one present the responses that cannot be summarised as numbers to provide an accurate reflection of the “culture” in our School? I’m trained to focus on numbers and to make simple statements using scientific language backed up by statistical analysis. So how does one describe “culture” and does this really matter?


As my head starts to smoke, I ask myself what motivated me to get involved in Athena SWAN. I realise that it’s not numbers that drive me, but the desire to improve the experience of students and staff, whatever gender they may be. Behind those numbers hide very personal stories of success and achievement, but also of frustration and failure. The numbers are just the starting point to get us thinking: What kind of support does a student need who worries about career prospects? What impact does maternity have on the career of a researcher? How does a colleague cope with having to look after children or elderly parents, in addition to having a huge teaching workload?

I assume that thinking about all of this is an important first step, and that by trying to find solutions to the issues raised as a result of our Athena SWAN application we show that “culture” really does matter to us in the School of BEES!