NCRM Podcasts

Catherine McDonald 00:00
Hello, and welcome to Methods a podcast from the National Centre for Research Methods. In this series as part of the EU horizon 2020 funded YouthLife project, we're looking at how researchers can do better longitudinal research on youth transitions. I'm Catherine McDonald and today I'm talking to Laura Bernardi, Professor of Demography and Sociology of the Life course within the Life Centre at the University of Lausanne. Laura is also the former deputy director of the Swiss National Centre of Competence in Research or, LIVES. Which studied the effects of the post-industrial economy and society on the development of vulnerability using a longitudinal and comparative approach. I began by asking Laura about the aims of the Life Centre.

Laura Bernardi 00:45
So the Life Centre, its main purpose is to study vulnerability and resilience processes. And it's an interdisciplinary programme that brings together sociologists, demographers, psychologists, economists and experts in social policies, and a focus on a longitudinal perspective and a life course perspective to understand vulnerabilities and social inequalities in these processes.

Catherine McDonald 01:14
And how does your research fit into that?

Laura Bernardi 01:16
I'm a social demographer, and I have some background in social anthropology and philosophy. And my main interest has always been fertility and family behaviours, and also their interrelations with social developments. So in particular, the last years of my research as concentrated on wellbeing, in relation to the intersection between family structure, gender system and employment conditions. So in that sense, vulnerability is part of those intersections. And I'm currently responsible for longitudinal study on the transition to learn parented for parents and children and how they experience it. And there you have several examples both of how vulnerability and resilience operate, and what are the kinds of inequalities that may emerge. I also have recently concluded a study on the joint factor family and careers on wellbeing in adult population in Switzerland, they're also you can see enough of those processes at work. And I'm about to start a large collaborative synergy a project on the effects on separation and divorce and children wellbeing. So in that sense, it fits at the core of the interest of the centre.

Catherine McDonald 02:30
And they sound like such fascinating areas of research, what got you into that what sort of drove you towards those subjects?

Laura Bernardi 02:39
I started with demography as the study of population processes. And little by little, I got fascinated by the fact that those processes were very different from population to population, I started with the demography of African population in my master's studies and move towards European population. And especially, I was fascinated by family and fertility choices. So that's how I enter into that. And when you talk about family and fertility, you have to combine more objective trends, which you can measure and more subjective perspectives from individual involved into these choices. So I thought that was the most fascinating area for me.

Catherine McDonald 03:22
So looking back across the work that you've done, how do you see the relationship between theory and qualitative research?

Laura Bernardi 03:31
Oh, that's a very nice question. I think there are several and I've been thinking a lot about it throughout, there are at least three aspects that are important to me to relate qualitative research and theory first of all, theory generation. So, qualitative research by its nature is often explorative and interpretive. So, it is invaluable, both to generate theories in emerging phenomena that are not so well known, but also to account of for the perspective of different populations that are leading through this social processes. So, just to give an example, from the life course perspective, there is a basic element undiscussed element, that is time. And the conception of time in the life course in the social sciences in general is that it's a linear process of uniform units evolving from before to an after. And on this conception, we build all our modelling of causality. However, when you take individual perspective and interpret qualitatively what they say about the way they experience time, you see that anticipations, accelerations and varying rhythms characterise their experience. And also this is what they act on to construct their biographies. So using subjective temporalities and having them much more present in research should be taken into account if you're not only to measure, but also to understand life courses. In that sense there is a lot of theory generation that can be built on qualitative insights and have the advantages that they will be empirically grounded. Then of course, there is another aspect that is also very interesting when you need to take into account possible recursive causality process. So, you need to formulate a hypothesis on what are the most possible causal links between two phenomenon, you may want to have grounded hypothesis. So, if you have complex interactions that are difficult to disentangle statistically, this is very useful. There are very beautiful examples on how qualitative methods can allow you to distinguish what can be considered a dependent or a conditional element in a relationship, and what should be considered an independent or unconditional element. Paradoxically, the more we have data available, and this machine learning kind of approach to data analysis, the more we need a way to detect and interpret the detected patterns that we see. So, in that sense, qualitative research in the terms of in-depth studies that would try to understand causality link, from the actor’s perspective, are crucial. And last, I think what is also fascinating is that you can mix very different types of qualitative research to build theory. One of the experiences I made was, for instance, very productive and very fruitful, was the use of combining qualitative research insights with simulation models that we can talk about it.

Catherine McDonald 06:36
Absolutely. So to just focus on the mixed methods research at the moment, can you give us some examples of mixed methods research that you've undertaken?

Laura Bernardi 06:45
Sure, I can start with this, this last example I was mentioning. So, for instance, when we talk about mixed methods, there are several ways you can mix several methods. But often it is interpreted as a mixing qualitative and quantitative analysis, or in other words, interpretive data analysis and more standardised procedures for data analysis, often statistical modelling, but actually, that could be other mixing. And quite some time ago, I had a collaboration with an interdisciplinary team of researchers are now social network influence fertility, which was the topic of my dissertation, which was a mix of quantitative and qualitative methods as well. And what we did was to take my hypothesis on different channels of social interactions, and influence of peer networks on fertility choices. And then the informatics experts in the team, they built an agent-based model based on this hypothesis, and ran several simulations in order to check whether taking into account this mechanism would actually produce a better prediction of what the first birth probabilities in a given country, in that case was Austria, on a given period of time, where the result and actually it did. So if you wouldn't have had the part of theory generating based on the qualitative methods, you will not probably have simulated those mechanism and you will not have inserted into the model and you will not have had a better fit between the empirical data and the simulated model. So in that sense, the mixing was very interesting. Another example, which is a bit more classic and more seen, if you want, it's a recent paper on employment trajectories and on parentage and using both panel data analysis and in particular sequence analysis, and interpretative analysis of biographic interveiew data. So this study, in particular aim that exploring the heterogeneity in employment trajectories before and after the transition to lone parantage in Switzerland. And we use the panel data to identify and describe typical employment trajectories around the transition to lone parantage and to estimate the association of those trajectories with some characteristics of the women that were analysed. And this led to the identification of five employment patterns that characterised either an increase in labour supply or a decrease or a stable situation. And then we use the content analysis of the narrative interviews with lone mothers that were residing in Switzerland, and which focused on values and norms concerning work and care. And with those mix of information, we realised that the kind of employment opportunities and choices that they made differed by the way they entered lone paranting whether they were alone, or they were separated when they entered lone paranting the post separation relationship with the children's father when this was present and contactable, and the ability to mobilise individual social and institutional resources proper to the mother. So, this was very interesting because we could clearly show that the effective policies that encourage lone parantage Labour Law, mothers labour market participation should consider, first of all the availability of informal an formal support, but especially the number of normative priorities that mothers give themselves when they face work and care trade offs. So there are a number of moral dilemmas that they have in mind when they make choices. And this would have not been detectable only through the analysis of the trajectories and the characteristics that we have in a Panel Survey.

Catherine McDonald 10:44
And looking back to research questions, so sort of right at the start of a project, what sort of research questions or issues do you see as best suitable for qualitative or mixed methods longitudinal research?

Laura Bernardi 10:59
That's another interesting questions. I think most research questions in social sciences are suitable to be addressed with longitudinal mixed methods approaches, certainly all questions of which the answer requires to obtain plausible measures of changes over time. And if you take a life course perspective, it's inevitable thing about development over time to explain a social reality. So, in my view, most questions are suitable for some it's indispensable. For instance, the synergy project I mentioned before that I will start with colleagues in different disciplines, asked about children's well being after parental separation, and how it's related to custody arrangement. Now, we know very little across the globe, I think, then how custody arrangements developed over time since the family broke up. So we know what is the situation at a given point in time, but not how those custody arrangement changes, when new births arrive when new partners come into the scenes and in relation to the story of care decisions also, for those who pass through tribunals. And therefore, we know little so on changes in the relational quality between different family members, and this implies the closer family the more distant families. So, what we are planning to do is to run a large Panel Survey, but also a deeper psychological birth measuring over time, of relation of quality of family members. And in addition, we will have a content analysis or an interpretive analysis of the legal documents that are related to those separations and custody arrangements. And on the top of it, an architecture colleague will be responsible for an observational study of children housing and space use in multiple households, which have shared cost studies. So this is a very complex interdisciplinary and mixed methods project, which as a time dimensions built in it, which is necessary to understand change, and therefore well being and changes in wellbeing for children and parents.

Catherine McDonald 13:07
Yeah, it sounds like a fantastic illustration of a mixed methods approach. And sticking with approaches, do you have a specific approach to comparison and generalizability? And if so, what is it?

Laura Bernardi 13:19
This is a very difficult question to answer in a short time because both approaches to comparison and generalizability depends very much on the questions you're asking on the context you're studying. It is clear that when you focus on a specific case study, you may have two things in mind. One is to study in depth in a given process in order to theorise and generate hypotheses that can be generalised only after more systematic testing, but that is the generating theory part of the study. Or you may want to construct a number of case studies that compared to each other would be leading to a more generalizable finding. I can give an example from my very past research. I once had a project funded by the National Institute of Health in the United States when I was a postdoc in collaboration with two colleagues from Italy and the United States to study our fertility decision making in Italy. And we had the luck to be able to compare four regions in the country that were differentiated by the rhythm and the level of fertility, the rhythm of change of fertility over time and the level of fertility. So we could match regions where fertility was relatively high, compared to regions where fertility was relatively low, and others where the drop from high to low was fast in the last generation and regions where this drop was slower. And we did an in depth qualitative anthropological interview-based study in these four regions, which could then bring about the rationale brought into this context, by families by women and men to explain their fertility decision making. So I thought this was the only way to go to make a more generalizable understanding of the process.

Catherine McDonald 15:23
Absolutely. So moving on now to talk about the people that are involved in your research, your sort of participants, as it were, with longitudinal work, it can be difficult can't it to keep those people involved over a period of time. Do you again, have any advice on how to keep those people involved?

Laura Bernardi 15:40
Yeah, this, of course, it's a concern, both for quantitative and qualitative studies over time, attrition and loss of participants. I think in qualitative studies, because of the smaller scale and the necessity, often to build rapport in order to be able to conduct meaningful data collection, you have less of that risk. First of all, there's a more direct contact between the researchers and the participants, and therefore less risk of abandonment. But of course, depending on the duration of the study, then you may still incurring attrition, unless major failure in data collection process occur, you may have a limited risk. What are the ways written and oral communication between waves is a good tip to maintain motivation. And also to thank and express what you're doing with the data you collect, and thank respondents for that, they appreciate it normally. Also to have waitering colleagues who are able to establish trust that is very crucial. So I think training and constant communication efforts is the way I would suggest to go. That's what worked best for me, I can always do better, of course, on those aspects.

Catherine McDonald 16:55
And in terms of ethical dilemmas. I'm curious, have you faced any? And if so, do you have any tips that you you know, be happy to pass on that you learn from those situations.

Laura Bernardi 17:06
So I have not encountered a major ethical dilemma. I also have not researched possibly very, very extreme situations where you may encounter that. But you have a constant concern when you research on vulnerable situations, because people may expect from researcher’s immediate support. For instance, that was the case in Milan parents project that you cannot offer. Or you should not convey the message that you're there to offer the support, the material support for instance, it is important to clarify that you can pass information of services that could offer such support, but that you have limited capacity to get involved personally, this is something that often happens to younger researchers that feels very concerned by requests and feel very trapped sometimes in those different expectations from research and from the field. So in one case, I also had words about one respondent in a difficult relational situation, but nothing that would require legally an immediate denunciation. But it can be the case. So one has to be ready and clear much before starting the project. What are the possible ethical choices that has to be made in the field? That I think is the most difficult to prepare, And so training for the researchers in the field, it's crucial there as well, ethical training I mean, and possibly debriefing devices for the team, because many younger researchers comes back from the field very poofed by what they encounter by the stories they've been told, or the scenes they've been observing and taking part of. And this is a psychological burden that should be taken into account in the research process, as well as the ethical dilemmas they may feel. There is also sometimes professional dilemmas that comes back from the field, because researcher feel that they are far distance from solving the problems they're addressing. And so here, it's interesting to remember the long run purposes of what we do, it's easy to want to shift into action research or when you want to be an activist. So in that sense, sometimes those conversations are important for debriefing also about the long term impact that research can have.

Catherine McDonald 19:27
So yes, what I'm hearing from you there is that it's just really important that as the researcher, you understand your role in the whole situation and that you have a grasp on those sort of professional parameters.

Laura Bernardi 19:39
Absolutely.

Catherine McDonald 19:40
And what about the writing up? Would you have any advice on writing up your research?

Laura Bernardi 19:45
Of course, everyone has their own style write up research, right? So it depends on the personal style and the approach, but I think there are a few things that especially with mixed methods and qualitative studies I learned along the way One is that using cases at the beginning of the papers to illustrate the main issue at stake in your research and introduce them, the theoretical and contextual underpinning is quite effective. At least it's quite appreciated when the articles go under review and are read, then if you're using mixed methods, then definitely clarify quite early in the paper, what each approach brings to the questions because depending on the inclination of the reviewers and the readers, they may tend to dismiss very fast one or the other approach, because normally we are quite specialised, and we have preferences. So in order to gain them to the mix part and importance of it, it's important also not to be defensive with respect to quantitative research, which is often the case at least in the demography papers that use qualitative approaches, but rather highlight what would have been missed without the other approach, if you would not have taken it. I have an example from my research, my very first paper published, which was based on research experience in South Nyanza, Kenya, where I started with a very quantitative approach on the influence of social networks on protection from AIDS, devices and also knowledge about contraception in the population. And then the more I was receiving questionnaires back during the fieldwork, the more I realised, I had no understanding why some questions looked like being contradictory, within the same questionnaire, so I had to go in the field and make more qualitative interviews to understand these answers. And I realised that I was missing a quite important cultural dimension. That was key to explain those apparently contradictory answers. And this fed into the paper, which ended up being a mixed methods paper where I had to explain why it was so important to get the field understanding of the answers. So that, I would say, are the tips I would have.

Catherine McDonald 22:12
And Laura one final question to you, is there anything in particular that you would say to the early career version of yourself?

Laura Bernardi 22:22
I can tell only go ahead, in the sense that I fell into this job serendipitously, in a way, doing what I like to do all along the way without much forward thinking, I have to admit. So I loved the job since the doctorate, I would say that I could I do of it what I wanted, in the sense that I could choose what I was researching on, it allowed changes along the way. It also allowed learning all along the way, actually required learning all along the way. And now, yeah, going along. Also, I appreciate incredibly the fact that the more you meet young researchers coming in with their enthusiasm, the more you revitalise your motivation, so the only thing I could tell to my early career version would be 'good choice'.

Catherine McDonald 23:16
My thanks to Professor Bernardi. The YouthLife project is funded by the EU horizon 2020 Research and Innovation Programme and is the twinning initiative between the Universities of Southampton, Tallinn and Bamberg, and the Netherlands interdisciplinary demographic Institute. You can find out more about the project at EUqualimix.ncrm.ac.uk This was a research podcast production. Thank you for listening, and remember to subscribe wherever you receive your podcasts.