Five reasons why I liked the ECSR conference ShareThis


Every year, the European Consortium of Sociological Research (ECSR) conference brings together sociologists from around the world to share research and discuss new ideas.

Representing CLOSER at this summer’s event in Switzerland, Bozena Wielgoszewska presented findings from her work using CLOSER’s harmonised income and earnings data to investigate the association between childhood language use and social mobility in later life. In our latest blog, Bozena summarises her conference experience and showcases some of the highlights from her trip.

A few weeks ago, I attended the ECSR conference on inequalities over the life course – an area of research where longitudinal studies play a key role. It was my first time at this conference, so I was not sure what to expect. I think the tweet below captures the essence of the conference very well – plenty of networking, intense discussions, and beautiful surroundings.

I went to this conference to present research in which we extract linguistic features from essays written by National Child Development Study participants at age 11. The part of the project I presented explores the relationships between these extracted linguistic features and study participants’ social mobility in later life. In addition to the essays, we also use the income and earnings data, which are currently being harmonised within and across several UK cohorts.

As academics, we are often taught to critique others work, pointing out its weaknesses. However, our research shows that, amongst other linguistic features, using positive and optimistic words, such as “enjoy”, “interesting”, and “my favourite” is related to better later life outcomes. That is why I decided to focus this blog on the reasons why I enjoyed the interesting research presented at ECSR conference, featuring five of my favourite presentations.

  1. Using effective and insightful visualisation

Aleksi Karhula presented research in which he and his colleagues use Finnish register data to investigate how education, occupation, and earnings are transmitted from parents to children. They compared the predictive power of these three aspects and concluded that similar social origin measures predict outcomes better in the case of education and earnings, and at least equally well in the case of occupation.

There were several reasons why I liked this presentation, but the main one was the visualisations they used. I get easily excited by visualisations of data and results, especially if these are presented in ways I have not seen before. In this research, Aleksi and colleagues use Venn diagrams to demonstrate their comparisons of predictive power, which I thought was a great idea! It inspired me to use similar visualisations in my research.

  1. Capturing the dynamic nature of life course

Tomás Cano presented research in which he, together with Michael Kuhhirt, investigate how different family income trajectories relate to children’s school performance, and whether these effects vary between the US and Germany. They use samples of children from the American National Longitudinal Study of Youth and the German Socio-Economic Panel Survey. This research looks beyond snapshots, which tend to capture children either living in or out of poverty at one point in time and, instead, shows a more realistic and dynamic picture.

Generally, I was surprised to see how many presentations at this, sociological-by-definition conference, used income and earnings data, which I traditionally associate with economic research. I am also very involved in the harmonisation of earnings and income project across the UK cohorts, which may be why this piece of research resonated with me. From my experience of working with longitudinal data, I know that the financial situation of study participants often changes from one time point at which it is measured to the next. Although this research is in its early stages, I look forward to the results and hope that the UK data can contribute further context for international comparison in the future.

  1. Exploring fascinating phenomena

Julie Falcon presented a poster, in which her and her colleague Pierre Bataille, investigate the class pay gap in France, using the French labour force survey. This research builds on similar research previously conducted in the UK, which found that professional people from working class backgrounds are paid less than their colleagues from more affluent backgrounds. Julie’s research shows that class pay gap also exists in France, and that there has been no sign of the decline of this gap over time.

Earlier this year I read the book, The Class Ceiling: Why It Pays to be Privileged in which Sam Friedman and Daniel Lauriston provide evidence of the class pay gap in the UK, and discuss the mechanisms responsible for its existence. I was fascinated by this book and found myself wondering whether this phenomenon is specific to the UK, or whether it would be replicated in different countries and contexts. The poster Julie presented provided some answers to my questions.

  1. Investigating contemporary topics

Yekaterina Chzhen presented her research, in which she looks at the roles of parental vocabulary and children’s reading behaviours, both online and offline, in influencing children’s vocabulary. For this research, she uses data from the UK’s Millennium Cohort Study and showed that children’s internet use has complex and non-linear associations with adolescent’s vocabulary scores, which were measured at age 14.

More and more children are using smartphones and social media, and there is little understanding of the consequences it has on their development. Yekaterina’s research shows the difficulties in measuring and estimating these relationships and highlights the need for further research in this area.

  1. Introducing methodological innovation

In the last of the parallel sessions of the ECSR conference, Matthias Studer presented research on a new method, which combines sequence analysis with data mining techniques. He illustrated this method through a study of the effects of family and work trajectories on health conditions of people age between 40-60 using the Swiss Household Panel Survey. This method allows researchers to extract several features, which can be related to the timing, duration, or sequencing of stages in life. It then tests and helps select the features, which are the most relevant for explaining an outcome.

Sequence analysis is one of my favourite methods for analysing longitudinal data, as it captures the dynamic nature of life very well. I am pleased to see how quickly this method is evolving, and I expect this innovation will be enhanced since the foundation of Sequence Analysis Association. However, having used this method in my PhD research, I am also very familiar with its limitations. I was excited to see that this new approach addresses many of these limitations, and I hope to use this method in the future.

Overall, the conference was very well organised, the quality of papers presented was very high, the questions were well-informed, and the comments were constructive. Due to the linear nature of time, I was only able to attend one of the 7 parallel sessions, but I hope there is a parallel universe in which I enjoy the remaining 6 sessions equally. I returned from this conference intellectually saturated, but inspired and motivated to continue my quest into understanding inequalities over the life course better.

Bozena Wielgoszewska is a Research Associate at the UCL Centre for Longitudinal Studies. She is currently working with CLOSER to harmonise income and earnings data across the British cohort studies. Follow her at @MeBozena