Интервью с профессором Каролин Шлауфер об итогах первого года работы НУГ, работе группы в дистанционном режиме и роли студентов в проекте.

Артём Ульданов и Каролин Шлауфер обсудили несколько вопросов, связанных с работой НУГ и отметили те результаты, которых удалось добиться.

Artem Uldanov: Hi Caroline! Let me ask you a few questions about the work of our RSG and also congartulate you with the succesful results of the project's expertise!

CS: Hi Artem! Sure and thanks, that is a reason to congratulate all of the group members.

AU: Let's start with the genral introduction. What was the idea behind the RSG (research and study group) project and what is the subject of your study?

Caroline Schlaufer: Research has shown that people use stories to understand the world around them. Therefore, stories – or narratives – also play an important part in the way people think and decide about public policy. A framework was developed to study the role of narratives in policy processes, it is called the Narratives Policy Framework (NPF). This framework has mostly been applied to the USA and countries in Western Europe. Our idea was to apply this framework to the Russian context. For our analysis, we selected public debates around three policy issues in Moscow. More precisely, we examined the debates around transport policy, the housing renovation program, and waste management policies. We selected texts from websites of actors who promote governmental policy and of those who oppose and criticize these policies. We then analyzed what narratives were used by these actors in these debates.

AU: What would you say about the students' engagement and their attitude towards the RSG? Was it hard to create the team? How did the pandemic affect your work?

CS: The students are doing an excellent job! It was their task to collect all texts and code them. This is very time-intensive work. Everybody finished their tasks on time and worked well in the team. The pandemic started when we had to start coding. Instead of face-to-face seminars I prepared a few videos to explain everything. Then we met online once a week to exchange on our coding.  Looking back, I am surprised how well everything worked. Everybody joined our online discussion and besides some instable internet connection, there were no problems. The online regime had also advantages: for example, all students could participate at an international online conference.

It was not difficult to create the team, many students were interested to be part of the RSG.

AU: Since the HSE academic fund's expertise was positive and the group's work has been supported for one more year how would you characterize the current results of the project and what are the further plans?

CS: On the one hand, we are finalizing our scientific articles that we prepared last year. I am very proud that we succeeding in writing four articles for international scientific journals. One of them was already accepted for publication, for the other ones, we still need to prepare revisions and re-submit them. On the other hand, we are planning on adding a qualitative study to our quantitative analyses of the first year. In this second year, we want to critically interrogate what is lost when narratives are examined quantitatively, and what could we gain by using qualitative methods.

AU: According to your experience, how complicated it is to be a NUG leader and what were the main issues/challenges during the first year of work?

CS: We were a really big team, consisting of 12 students. Of course, it has not always been easy to manage such a big team. To make this easier, we split up into smaller groups, and each of them had their tasks to fulfill. This worked very well. In my view, the biggest challenge – well, besides the pandemic – is the limited time. We wanted to present finalized articles by the end of the year. To achieve that, we had to start collecting data very early. I think we rushed too fast into the data collection. In a next research project, I would spend a bit more time in the beginning to clarify hypotheses, case selection, and the data collection approach.