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President Yes.

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Hello and welcome everybody to the next RC 11 sociology of aging session and we will start with an acknowledgment of our Hosts here and

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Okay, thank you very much. On, Some technical technical adjustments and I will try I have to read it so I will be closer and then you will see my face unless I will be so on behalf of everyone gathered here I pay respect to the spirits of the country here in ARM where we are meeting I acknowledge a past in

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the present, coordination, room, Jerry, vo, room as the sovereign people here, the culture knowledge holders who maintain and promote the Narm Aboriginal law customs and custodians responsibilities for the country and the people that country continues to sustain a generation after generation.

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The future for all of us. I recognize the important contribution that First Nation thinkers have made to sociology, including challenges to our dominant ways of thinking.

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We want to we thank all of First Nation delegates in room today, if and for their contribution to the knowledge in the discipline.

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And I will be stepping in for our envisions. Chair. So we will, I believe we have all of the presentations set up so we will start with a session with and know any further ado.

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And the first. Of course, please do share the meetings, use proper hashtags and and you have seen them there and we will start with

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Should we start with Ortiz? It's let's go back please to maybe.

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If you stop sharing, I can share my screen.

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Yes. There we go.

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Thank you.

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Thank you. So we have Francis out who's with us. She also pre recorded her presentation but we are so blessed to have her here with us and she will talk about her paper on recurring Ego's memories.

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So, Francisco, the floor is yours.

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Thank you so much. And thank you for being here, even though I cannot see you, but hopefully, everything is going well over there.

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So for this presentation, I got to be, so first my name, Francisco Tis, and I'm working in the millennium Institute for Care Research in Santiago of Tile.

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And today a good 2% and reflections about data collection and for that I'm going to be using 2 studies.

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So first I'm going to be using my study, er, which I did in my PhD and I'm also going to be using my, which is my current research, which I'm doing right now.

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And a science is not something that we do alone. I will like also appreciate and acknowledge all the contributions from these people that are right here.

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So let's see what is the first research. Just to give you a brief idea of what was it is, I did my field one.

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During, October, 20, 19 and January 2020, I interviewed 30 all the people divided by gender versus economic level and I start the whole interview asking which one were the most important events of your life.

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So I also use the, approach. And I try to construct the whole social support network of people. And I did many different analysis and I also use many different software network of people and I did many different analysis and I also use many different So in terms of participants I use this kind of distribution generally was sequel but also I have a big branch

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of age and I try to have some division in terms of social class. So the most important thing that I did in there as I was telling you, I did this question which is about which are the most important events of your life.

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So the first thing that I did, it was collecting the life history of the people. And I just leave them talk and it was a whole, well, someplace many interviews.

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And after that, I construct this. This is probably the most important part. Or visualization of my research, which is a decision that allow us to see the timeline of the person.

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We can see all the dates and all the most important events that the person mentioned. Because those events are the ones with, blue colors and the ones in red colors are the, all the other events that they mentioned that they're relatively important.

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So what is in there is the dates. The event but also a quote from the person And then I use these.

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So we the each blue event. And we construct the social support network in that moment for that person. So for example, that's the first one, that's the other one and that's the other one.

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For each one I have both directions of the network. That's why I have 2 networks for a moment and evil is the person who was interviewing that moment.

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So in this case, Catalina who obviously is not her real name. So this was the first.

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Then the second one, is the one that I'm currently analyzing actually all the data and I concentrate more in only one place.

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I concentrate in one community center. And because I was trying to reconstruct the complete networks of all the people.

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And in there I have all the people but also I have professionals which are the people who work with them.

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So I also have interviews for them. So in the first place I asked for the perceived network, but then I also asked for the actual network.

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So in that way I could construct the whole network of everyone in there.

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So I have a whole process in which I have 3 waves. This was the plan, but at the end, they in their interviews were, er, made in advance.

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So actually, er, all this was done last year. Actually, they were done a little bit. Before the November and December and a little bit closer to the third interview.

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So just to give you an idea, this was the kind of results that I get. This, this, like, each thought is one person in the community center.

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And you can see all the links accordingly with different dimensions because I asked for many different dimensions and they have a lot of patience with me actually.

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So, what are the reflections that I would like to share with you all therefore?

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So to start first for the first study it was very difficult because, for the first study it was very difficult because, there was an very difficult because, there was an very difficult because, there was an very difficult because, there was an very difficult context.

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There was a social rights movement at that point actually 7 days after I arrived in Chile, there was already all this happening.

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And so obviously my field was completely disrupted. Everything changed the public transport. There was a cure for like I think it was 2 months at least or something like that.

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There were military in the streets. There was a huge, moment in there in Tilia and this was exactly just before the pandemic.

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So during this whole movement, I have high levels of stress for many, interviewers.

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So some interviews were cancelled at the last minute or were very difficult to follow. So I have to instead of doing one or 2 or 3, I have to do 4 or 5 sessions.

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But also I have to allow a lot of time to talk about this situation instead of talking about the research because it's something that it came out a lot during the interviews.

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So some of the learning is during those, moments were like 6. 6 at least that I could identify and share with you.

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So first, giving participants time and space. I usually call everyone, the ones that I already interviewed, the ones that I'm going to interview everyone on Mondays just to planning the whole field work, but also catching how they were doing, how was everything because sometimes people in these kind of scenario, they didn't talk

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with anybody and they didn't saw anybody because there was the difficulties for them. Yeah, well, and for everybody to be honest.

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And second, at the time of the interview, I tried to talk with them about what they were thinking that it was happening, what, well, a lot of people, they were not leaking their houses.

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Obviously, me coming to their houses. It was like, oh, there was someone who was outside. Maybe I would like to know something about how it's going outside.

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So I was trying to tell them how was everything. Then give them the option to end the interview at any time.

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This is something that we all used to do, but actually what I did is I teach them how to use the record, the voice recorder.

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So actually they could do it and they could pass the whole record whenever they want. And I keep to give them that kind of agency.

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And which actually a lot of them use it for my surprise and that was really nice and they posted and we have, I don't know, some tea and coffee with stuff in and they would continue.

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Then, I also, I talk to them about the personal experiences and how they are doing the protest.

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This is something that, er, to make them comfortable. But also I called them after the interviews again just to see how they were copied after the interviews again just to see how they were copied with everything.

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But also I called them after the interviews again just to see how they were copied with everything. Also because a lot of them, would you show you, Ask me for the results and that kind of stuff.

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So they were curious about what was I was doing. And also obviously Kibin and I own news later on social media.

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I was not, I think this was the moment in which I was looking a lot of Twitter because obviously I need to know what was happening at the same time.

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So the second thing the second reflection or video reflection is about the computer. I used a lot of the computer during the field world and something that I would like to highlight is that it was super interesting to use it because it creates a very different environment.

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But also a lot of people feel curious about using the computer and they were very embedded into the research because of that.

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So I already told you about these timelines. This is one of the key things that I use for activate memories.

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This was super useful because I create this from the beginning from the first interview and then I was changing it.

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Through all the interviews. At the beginning, obviously, it was not done in computer and it was not so nice.

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It was by hand in a paper. But then we were constructing this with the with the other people at the same time.

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So this was super, super useful. So, was super, super useful. Also, I asked the interviews in different orders.

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So, I asked the interviews in different orders, so for example, the interviews in different orders. So for example, the second interview I asked first for the perception then I asked for example the second interview I asked first for the perception then I asked for a second for specific events and then I asked for the perception, then I asked for a second for specific events and then I asked for the people

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who help in those events and then I ask for the people who help in those events. That kind of order can also perform the kind of resource that we could get.

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And before the interview I also told you a little bit about creating a safe and comfortable space but also after the interview and I came back with all these visualizations that I'm showing to you and from the 30 people interview for example in one of those research 21 agreed with the visualizations they were really happy with them and that actually a lot

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of them they asked for the print person or they asked for a for them in a Pendra, that kind of thing.

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But also some of them move the position of some people or they change some dimensions some answers and that kind of thing and that's also something that I would like to state that is relevant to count, but to take into account.

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So as the last reflection, it will be that actually when I ask them for the emotional support and this is something that happened a lot in the second research.

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A lot of people tend to think up outside the checkbooks and I think that's super interesting too and we need to think about how to add that kind of thing in our research.

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So for example, I have a lot of people who, globinate people who already die, institutions, groups of people, a lot of pets.

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I have a lot of those in the head who were taking for the taking care for them. And And that's interesting because it challenged us as researchers.

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As how we take this into account. So. Just to go to the completions.

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So some tools I show you some of these visualizations that actually are used during my research. I think I strongly agree that they can activate memories.

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They were super useful during the interviews, but not only using at them in the first interview and that's it, and also using it them in many different interviews and allow us as researchers to change our data collected in many different sessions.

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It's very challenging for us, but it's also. Very like, for us because we get more detailed descriptions about the content that we want.

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And so what I would like to say about the content that we want. And so what I would like to say at the end is how we ask questions, how we behave before during and after the interview and how we want.

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And so what I would like to say at the end is how we ask questions, how we behave before, during and after the interview and how we ask questions, how we behave before, during and after the interview and how we approach to these people, all impact actually in the results and any applications that our research could have afterwards.

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So thank you very much for listening and I will be more happy to receive any suggestions or questions.

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Thank you, Francisco. Do we have some questions or points of clarification at this moment in the floor or on the Zoom.

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Doesn't seem to be the case. So I'm handing this position back to Anas.

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I don't know which one. And we can continue with the next. Thank you. Once again, Francesca for this.

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Shall we, please can you set me? I'm okay. Okay. Since the session and then, And are taking over the or do we want to thank you?

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Oh, okay. That, they're not continues. Okay, you can have a rest, but we've been doing a lot of work already.

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So we've been doing a lot of work already. So we are very open related to cooperation. So anybody who wants to chair this session. Yeah, we are very open related to cooperation.

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So anybody who wants to share. We are very open related to cooperation. So anybody who wants to chair this session can.

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But right now we are giving Florida to Christine. The florist. We're going road.

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We're chair free. Okay, so I would get my little timer set up here. How's that?

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Can

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Okay. That was such an interesting paper. I love that first one. So this is going to be moving up far more macro I think than the last one so my name is Christine Mayer I'm from the University of Maryland, Baltimore County.

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It's in Baltimore, Maryland, the United States where a sociology and gerontology group and also its interdisciplinary, sociology, anthropology, public health, all of these and that's our centre for health equity and aging.

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So this is a little bit different. This is actually, make sure I can turn them.

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I'm sorry?

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It's not working.

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So we just need to be activated, yeah. Okay, thank you. Sorry. That's great.

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Thank you. So this is actually a book chapter and it's going to be in the handbook of quality of life research, place and safe perspectives.

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They wanted some sociology of aging examples in that book. So for me, this was kind of an idea or maybe more of a frustration that I've had.

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So doing a lot of linking of publicly available data from neighborhoods, individuals, and country level. There are a couple of challenges, I think, that I've experienced and thought about so it was a good opportunity to write sort of a it's more of a conceptual paper but it has a methodological suggestion.

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But my disclaimer is that this is sort of 90% me describing the problem and only 5 or 10% of me offering a solution for how yet.

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So I'm hoping that I can continue to talk to some geographers and see what we can put together.

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So this is more of identifying a problem than I guess. So we all are very aware of life expectancy expanding across the globe but I think it's important and helpful to think about it and look at it.

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So this is life expectancy across the globe in 2,023. You can already see of course Australia, Japan, Canada, parts of Europe.

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And as we start to move forward, we start to see this, you know, of course begin to take off really rapidly, but not evenly.

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It doesn't, take off evenly. It's a scattered sort of pattern across moving towards 2,075 we can start to see how quickly this will be accelerating which many of us know of course but it's helpful to see it visually and then moving into 2,100 where we're going to have many super

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age populations so there's a lot of need for thinking about this of course cross nationally and global aging.

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So there is increased availability and global aging. So there is increased availability of data cross nationally on aging.

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So there is increased availability of data cross nationally on aging populations and a lot more available about country context and a lot more need for these because we know what's happening and we need to be able to track this differently across countries.

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Majority of the data that's available is available at the country level. That's going to be kind of one of the points that I'm making for today.

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So data that might be available at the country level we have for example GDP right wealth of the country distributed across we know we've seen this before I find this to be actually quite a useless measure at the country level.

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It's like neighborhood socioeconomic deprivation. It explains everything but nothing all at the same time.

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So we have some other options as well. This is maybe looking at household structure, looking at one-person households.

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You can see this is also not even across countries and different challenges will be emerging in different regions as a result.

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This is so security programs across the world. We can see countries like the United States, of course, that are that have extremely high GDP are not do not have a strong Social Security program so we can see the policy variation that exists there.

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I don't know if you've seen this one before. This is from the World Values Survey.

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They've been doing this for decades, gathering different individual level survey data and creating these sort of axes of culture.

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We could definitely critique this. There's sort of individualism on the x-axis and then traditional versus secular values.

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But you can see that countries are clustering sometimes around regions, sometimes around religious histories. And so we know these things also shape the context within a country in a way that something like GDP for example cannot capture.

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So this leads me to be thinking about what really is country context. What do we mean by this? What does it really mean?

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And it's really, really complex, of course. So when we're doing cross ethanol research with a large number of countries in our data set, there's a lot that needs to be taken into account.

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There have been a couple examples, you know, whether it's culture type of expectations, economic development, allocation of resources, how a policy is formed and how funding is allocated.

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All of these might operate at the country level as well as at more local levels within the country, across provinces or states, things like that.

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And then I think we also have to think about historical trajectories and geography and topography of countries because this can also shape sort of cultural pockets within countries.

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So I'll use the example of the United States, not because I think it's a great example of anything, but it's the one that I'm the most familiar with the context.

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That's where I'm from. So you can think about the topography and sort of the geography and also the history of the United States.

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We've got the mountainous regions in the west, the breadbasket area in the middle, and then in the southeast kind of coastal flood plains.

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This is where there's a high proportion of agriculture. So this the southeast region was where we had the institution of slavery in the United States for an exceptionally long time, right?

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And you can see that this has left a demographic imprint on the United States. So this is the proportion of black or African Americans in the United States by county.

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We call this the Southern Black Belt of the United States. And you can see this demographic imprint of the institution of slavery on the country still.

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And we know that this shapes culture, this shapes all types of things in terms of discrimination and experiences and identity all of this is really important to that region of the country.

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That's also the region that I'm from of the United States. So we can also look at poverty and see how this varies.

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We've got that kind of southern area high in poverty. You also have a pocket up here in the mountains, which is actually white poverty of the Appalachian Mountains.

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We have different other spots in the southwest. We have our own first people that were displaced and you know were the victims of large genocide that are pocketed in some areas on the reservations and high areas of poverty, which is also an important part of our context.

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We've got variation in disability that sometimes follows the poverty line, sometimes doesn't. And then we can think about, percent without health insurance.

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This is after the Affordable Care Act, which we call Obamacare. This is better than it was 10 years ago in terms of lack of health insurance, but we still have especially areas where there is high levels of immigration from Mexico or from Cuba.

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We have, you know, higher levels of uninsured and as well as in other pockets of the United States and Alaska.

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So this is just to highlight that when we're using country-level data we're missing all of this really interesting painful but also potentially really interesting nuance that's within country and we all know that right we all know that that's a lot more complicated than country level measures and then of course even just looking at Australia and

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Japan, this is where I've been over the last month and I thought you might want to see Australia, you know the geography but this shapes also the cultural pockets as well.

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And then if we go more global, this is looking at motorized times to the nearest health care facility.

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You can see that some areas like the United States and Europe, for example, highly urbanized, lots of availability here.

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But then we see a lot of variation within countries. Australia, I think is a great example on this one with the rural areas there.

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You can really see how difficult access to health care is and some of the more rural pockets of Australia.

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So we know all this contextual variation exists, so with all this fast, with in-country heterogeneity, how is it currently measured in cross-national studies?

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And I think really the short answer is it's just not for the most part. If we're doing a one country study, we can often incorporate this level of detail at least into our interpretation of the results.

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But if you work with multiple countries, I usually work with you know the gateway to global aging this could be 30 countries together even if you're running a sample by different countries.

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You've got really no ability. You have no methodological or analytic ability to really account for this within country heterogeneity.

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That's why people might tend to do one or 3 countries or 2 countries at a time so they can really dive into serve them as a case study and start and acknowledge some of these within country context.

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But there are some examples of ways that we can try to do this. So this is still me formulating the problem, not the solution.

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So this is just something I ran that's looking at who says they have very good self-rated health, breaking it down.

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We could compare by rural and urban area, for example. That might be one way to try to get at some of this within country heterogeneity.

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But we see really different patterns. You know, sometimes rural higher, sometimes urban higher. And we know that not all rural areas are the same.

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Not all urban areas are the same. So this is really a major oversimplification of a diversity that exists.

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Oftentimes people use administrative boundaries and this is the same case for neighborhoods research so I'll talk about that in a little bit too.

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These are, you know, this is one example. The International Organization for Standardization has these at administrative boundaries.

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You can see they get much more dense and more urban areas. But I could also imagine those are who from Australia might find these to be quite arbitrary in many ways.

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This is not likely capturing your real kind of cultural or economic regions. So this is also not ideal.

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A paper came out in 2,023 that was trying to identify some cultural regions in the United States.

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They just use social media terminology. So it's really sort of linguistic. And you'll start to see they actually give a good summary of how these changed over time as people kept trying to map this.

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Florida starts to emerge as a really different region which I would agree that's why I grew up in Florida.

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It's a very strange place. So I could attest to that. But you can see some of these kind of regions start to emerge in this analysis, but it's still quite limited.

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It's not taking into account economic or even geographic differences. So here's another example. What I want to do is look towards neighbourhoods research.

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Neighbourhoods research has been thinking about this problem a lot. And I think that what we can do is think about some of the solutions they're coming up with and apply it to cross national research, especially with aging populations.

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This was a study that I worked on back in graduate school. There are other studies that do this. The black lines, this is actually a neighborhood in Texas that's near an environmental hazard and we were looking at health and race and ethnicity in this group.

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So the the black lines are the census tract divisions and the green lines are the ones that we divided by doing interviews by walking to see where railroads were, where rivers divided neighborhoods, and we found that the ones that we did use taking into account these kind of social of course and geographic boundaries were far more predictive of health than these

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arbitrary census. What we expected to see, but there is more work being done this than the last 10 years.

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So what I'm arguing is that really the problem is that we do not have non-administrative identifiers for within country at a larger kind of regional level.

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So this is what I think the missing link is for global aging research methodologically from my perspective right now.

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We actually need an additional linking variable. We can link data up at individual levels if it's a repeated survey of course we can link them up at the country level we can bring in aggregated data we can link that and attach that on to survey data of individuals, but we're still limited to the country level and the individual level.

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And this is, I think, really methodologically and conceptually, becoming increasingly problematic. So we can, as I said, we can look at rural urban areas.

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We can compare across states and provinces or just known regions if we can aggregate in that way. But we are still limited.

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There's these standardized administrative identifiers that we know are there. So these delineations are often arbitrary.

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I don't know about in Australia, but in the United States they're often politically motivated, right?

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We've got a lot of them were drawn by lines of segregation in order to prohibit voting in certain areas.

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And they also just can't capture regional identity or subjective meetings of place, which is a big issue.

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So we're really limited to this finite set of pre-existing identifiers that are largely arbitrary and really unrelated to processes of quality of life.

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So we're trying to think about how to investigate aging populations and compare on a macro level that's a big problem.

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So there are some issues. So as I mentioned at the neighborhood level, there's a lot of sort of new health geography.

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They call it this uncertain geographic context problem, the unit question, contextual fallacy. They are working on this intensely at the neighborhood level and have a lot of interesting kind of creative ways of addressing this.

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But right now, the approaches that are being done at the neighborhood level, a lot of different people are working on a lot of different solutions and there's not one accepted sort of idea about how we should go about doing this.

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So there might be some ideas coming from this literature in the next decade. So what I propose, and I think it's just an idea, I don't know how to do it, is that we need to create standardized with in-country regional identifiers to add a context level between the individual level and the country level.

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It's kind of simple actually. But to do it I think would be a little complicated but this is really the first chance we've had to do it.

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We have a lot of big data that's available. Historically, historical data, political, I think it should be multidisciplinary, socio-cultural, economic and geographic.

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So all of this data is publicly available often from administrative sources. So it really can be linked and analyzed and set up in a more systematic way for us to have a little bit more of a pathway about how to think about regions within countries.

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So I think we can kind of think about this in different terms of geographic formations, infrastructure, socio-historical divides, cultural identities, and we need would need to coordinate across disciplines.

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So it would be kind of a matter of just pulling in similar to the example of the United States kind of one they use social media.

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We'd have to pull in data from a lot of different disciplines to do this. But essentially you can kind of look at a basic cluster analysis and you could overlay it on maybe GIS data.

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It's not something that I could necessarily sit down and whip up. But I think an interdisciplinary team, the data are out there.

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It's just a matter of figuring out how to put this information together in a way that could solve this problem.

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So I think but the key for this I think is that it needs to be able to be replicated and repeated.

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I would ideally think this needs to be something that would be taken on by the large leading institutions like the US Census, the United Nations.

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They could coordinate with this and then essentially it can be you can repeat it over time, maybe we revise it every 10 years or every 5 years, right?

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Because we know these regions might shift and identities might shift a little bit. And then what they could do is basically provide it as a regional ID number.

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Rather than these ISOs that are these sort of administrative boundaries that are meaningless. Maybe each country has like 5 or 6 within country regions. We don't have to have 100 of them.

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It could be these kind of large clusters that exist. Something that could allow us to take a country level measure, an individual level measure and find some sort of linkage to acknowledge some of the differences that exist within the country when we usually only have those 2 layers available.

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So I would like to add that context level between the individual and country level. That's that's kind of it.

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There remains vast and explain heterogeneity especially in terms of health and quality of life. We have all these public data sources and geographic tools to do this.

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This is actually a really important time that we could do this right now. We're really not being able to see real world risk factors because we're either going over macro or over micro or under micro.

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So with this arriving explosion of aging populations all of the needs. I think this is a real opportunity for us to think about how to improve upon the way that we link data and analyze data.

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So if anyone wants to do this, let me know. Thank you.

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Okay. I was so domestic when I walk today to the room and then I just I don't know if I don't know when I walk today to the room and then I just I don't know if I don't lost hope when I see the complexities that ahead of us.

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But are there any suggestions questions remarks do this fascinating Christina's paper

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Let me know if you know any health geographers.

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Go ahead.

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I think it was a very good paper. Thank you very much. It's interesting because we were working, I'm from the social policy research center and we were working with 2 other centres, the Center for Health Equity and City Futures Research Center.

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So want a health center. One's place, the demography, urban demography or geography center and I was sent to which looks of poverty.

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And the concept seemed very easy. What we were trying to do was map. Regions of poverty by location across the country with health centers recognizing that people's living conditions We are really directly dependent on access to certain things, access to services, whether it's community services, hospitals, GPS and in a country like Australia, given our geography

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that was very, very difficult to get. And we couldn't do it. Yeah, actually. So exactly what you're saying is the problem we had which is that it would obviously be seemingly known to everyone that in a country with with various populations and a lot of a lot of people in remote regions access to infrastructure is important and if

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you want to stop people coming into the city which causes an urban density issue that you need to have. Access to certain services, but we couldn't do it actually because we couldn't map it.

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So we have the same problem. We had various sources of data and nothing that could be mapped onto each other.

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So I just wanted to make that point. Yeah, I think what I was thinking about this I thought well maybe somebody's doing this I thought well maybe somebody's doing this I just kept thinking this I thought well maybe somebody's doing this I just kept thinking this this could this might exist.

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I just kept thinking this this could this might exist already maybe I just need to read more so I keep thinking this this might exist already maybe I just need to read more so II keep trying to read and find it and the more I kind of talk about it.

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It seems sort of simple like you said but obviously the methodologically to do it is complicated but we have I believe I mean it makes me feel kind of hopeful like we have the data to do this absolutely we do we need an identify we just basically need a linking identifier we need a large institution full of smart people from all

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of our disciplines to basically just spend a little time to do this and then provide a systematic, you know, this is going to be region 1 2 3 4 5 6 for the United States and we're going to repeat it, reassess it every 5 years.

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It can it can start simple with large regions just to provide some sort of basic guidance I think would be really helpful.

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One but also a way of defining certain things of that they give normalization. Exactly. And right now we use for the United States census.

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We all know it's part of my French crap. I mean, it doesn't tell you anything about what's what spatially and we all know it's bad and we all use it.

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So if we can all agree that we're using the census maybe we could all agree on using something that actually makes sense.

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At least a little more sense. If not, thank you very much, but we may have some time in the end.

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And now it's our one and only Anna Urbaniak who should be next on the list.

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Yes.

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If I'm no? I'm sorry? Oh yeah, I'm sorry so much. I'm looking at the phone and that's not good enough.

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Apology is this pre-recorded or would we have to stop a check?

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Greetings I'm here

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Perfect. Thank you. You quick. To stop the sharing.

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I thought I saw you, Corina. So apologies once again. I saw it and I immediately forget about you.

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Yep.

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But the screen is yours. If you can make it also in a presentation mode. So. We now see your PowerPoint only.

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Perfect. Thank you so much.

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Great. Thank you so much for having me. This is a great opportunity and I'm happy that I can share my ideas with you.

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This is an idea that I've been working a lot. Lately and there are several papers that are linked to this idea.

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Basically we are thinking about measuring intersectional disadvantage and, we, I'm discussing about this in the context of.

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Aging populations, but not necessarily. So the idea of measuring, intersectional disadvantage started from intersectionality.

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Research and basically the main intersectional research has been done in a more qualitative way in the sense that you would like to take into account multiple disadvantages in a very specific way and take into account multiple disadvantages in a very specific way and looking in detail to some particular intersections in a very specific way and looking in detail to some particular intersections of categories

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that place people at a higher level of disadvantages in a very specific way and looking in detail to some particular intersections of categories that place people at a higher level of disadvantage.

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Basically we refer to categories of people that hold more disadvantage position in the same time and their interaction places them at higher risk and social exclusion.

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Then when their position is taken into account on each category separately. And we like to think about them all together in order maybe to see what extent intersectional disadvantage, influences other aspects of their lives.

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For example, health. Because I told you that we have some other papers. that we are working right now.

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Basically this is what we have tested and we found a lot of great impact across countries that is that is significantly statistic and that is significantly statistic and consistent.

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And here basically we are taking a Look, in the sense that, there may be a discussion on what categories you would like to see as comprising the multiple disadvantage.

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And such categories may be represented by being at all old age, then in comparison with being younger, being a woman.

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Instead of being, men without living with a partner instead of living with a partner at all age with low education comparing with higher education and with low digital skills in comparison with higher digital skills.

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And so on this so maybe the list can be Oh, further, you consider with ethnicity for example being, part of the minority group.

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In comparison with being part of the majority group in that particular region and going on with Christina's presentation maybe taking into account the level of development or maybe in that particular area and so on.

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And, intersectionality aims at considering how characteristics can be mixed in order to capture the reality of social exclusion and difficulties people may process.

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This is the idea of, intersectionality. And, our methodological approach proposed starting from the following idea.

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Until now, even though there were, several published, papers on, quantitative research using intersectional intersectionality.

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They were using interaction terms, basically multiplying or taking into account cumulative factors. But basically your interaction terms.

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We are thinking about creating a factorial analysis basically a factor within a structural equation model. That may represent another way of accounting for intersectionality in quantitative ways.

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And, the discussion for there is, related to the comparison between formative factor and reflective factor.

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Because creating a formative factor provides a way of creating a type of index. Basically you create a sort of index of multiple disadvantage or intersectionally disadvantage.

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Whereas considering a reflecting factor may conduct towards considering measurement errors in the variables that composed intersectional disadvantage such as age, a gender education and so on going to the discussion of types of age.

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Because if you consider that age has measurement errors, basically you say that you don't measure it directly or maybe other types of age behind that and for example you can say that you can measure the age felt, the formal age or social age or other forms of age.

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For gender more than 2 genders, the idea that you didn't capture the other genders and how people will consider in other ways because usually in quantitative research in surveys you have you have women and men and that's it.

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And we are looking for data sets that also have information about other types of genders. And then, informal education maybe or in comparison with formal education because you you may consider that people with both formal and informal education throughout their life, long life learning, the long life learning concept may be also important for their outcomes in

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life. Oh and so on. The 4 more key factor I was talking about is this one.

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And, basically here, the model is constructed considering all these characteristics correlated between each other.

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Basically you have all these errors. Arrows that show correlations between all the indicators then you have the intersectional disadvantage compound the factor basically and an error term here is considered for the for the factor meaning that you there may be other.

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Other disadvantaged statuses or indicators for intersectional disadvantage that are not measured but they may be important and relevant for intersectional disadvantage and this is how you account for them by adding this error term that basically some in most cases is mandatory for be for for the testing the model.

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Then the other approach is the reflective factor and you can see here that we have those error terms that are also talking about.

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Basically you have for each, indicator and an error term, error measurement, with the examples I told you.

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Basically error terms in old age or in measuring gender in measuring the living alone or indicator education digital skills.

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I use this Well, the proposal here does not contain. Minority ethnic and minorities.

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A minority ethnic and minorities, even though the intersectional minorities, even though the intersectional approach, even though the intersectional approach, does, minority ethnic and minorities, even though the intersectional approach, does, into take into account ethnic and minorities.

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Because, for example, we have worked a lot with the share study, a survey of health and aging, aging and retirement in Europe.

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That is for aging populations. But that particular survey, even though it's longitudinal, it does not take into account atnicity at all.

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So you don't have data about that. Oh, and, recently they are starting taking into account digital skills that maybe also relevant to be irrelevant above and beyond education nowadays.

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Importance of this. Because all these approaches can be further used to predict out outputs and as I told you at the beginning we started testing the effect of intersectional disadvantage on health at old age and This is the other presentation that I have, during this conference.

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It will be tomorrow. Basically there you can see the fact that this connection exists across the all countries that we tested and it's the connection is important.

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And it's statistical, so the coefficients are standardized coefficients are between 0 point 2 to 0 point 6 in some countries.

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Which are pretty high. To, to have this particular characteristics that are social demographics basically.

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And to have their compound or the total effect of them to have such an importance on health independently well, to have such an importance on health independently while whatever people are doing this is huge I think and importance on health independently well whatever people are doing this is huge I think and we are also on health

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independently well whatever people are doing this is huge I think and we are also trying to look at some importance on health independently well whatever people are doing this is huge I think and we are also trying to look at other connections and to see what extent this kind of disadvantage influences or is connected to other outputs or

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maybe also inputs for example we may also consider social origins education occupation or income that the parents of the respondents had or maybe other others related to social origins.

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And then the theoretical approach in this case is very much connected to the methodological approach for revealing intersectional disadvantage at old age.

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As well as the complexity of real life by means of quantitative research. And this innovative approach of considering hardship in later life may represent a step forward, you know, counting for intersectionality in quantitative research.

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Okay.

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Thank you. Thank you once again. And apologies for the mixed up in the start do we have some suggestions comments.

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Yes, there is one. Hi, this is Christine. I just had one question. I work with Share 2 and I couldn't remember if they might have, do they have maybe country of origin or country of birth?

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That might be able to be used, because I really love what you are kind of proposing to do with us.

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I think it's wonderful and I was thinking about how can we capture that and share some of the diversity even though they don't ask every ethnicity question or if you have any thoughts on that.

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I think they may have, the origin there country of origin, but I'm not sure.

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Yeah. Well, thank you for the for the idea. I, that would be helpful to see they have a migration history yeah thank you

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Good anybody have a follow up on this? Are you working with Chair anybody? Doesn't seem to be this case in this room.

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Hmm.

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But we know that the sheriff's used, would you like? Yes, I must have had 2 coffees.

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Thank you, Carina. I just want to ask you a question and I hope you don't, it doesn't come across as if it's off putting a question and I hope you don't it doesn't come across as if it's off putting but can you go back to slide 7 on the reflective factor maybe

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I've missed something or the formative factor, both of them actually. No, the reflective factor.

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Just so I understand. With all these indicators. How do you distinguish between My impression always that an indicator has to be leading towards something.

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So like age by itself doesn't imply disadvantage. Being a female doesn't apply disadvantage.

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Neither of those things. Any of those things do not imply disadvantage. And so how do you, how do you imbue?

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In either those indicators and then in the combined factor. Assumption that doesn't automatically mean that you're embodying the factors with with the disadvantages that doesn't reflect reality.

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Do you know what I'm saying? Like if you had to, you could make an argument for instance, if you have if you if you look at an income scale having more income is almost better than having no income or having a house is better than having no house but you couldn't for instance necessarily say that being employed is better than

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not being employed especially if not being employed was your choice. And so. Yeah, I maybe I've missed that at the beginning of the presentation.

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So can you just clarify? How how those categories do not necessarily imply disadvantage.

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Thank you so much for your question. Yeah, basically, this starts from the feminist idea that, that some categories of, some groups of people are more likely.

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So in terms of people are more likely. So in terms of probabilities are more likely to are there.

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To experience some difficulties that the place them in our category or that would represent a disadvantage. So it's not, would represent so disadvantage.

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So it's not the idea that being a disadvantage. So it's not the idea that being a.

303
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So it's not the idea that being a woman and do that's it.

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Basically if you are a woman you automatically are disadvantage. It's in in terms of statistics and probabilities, that are taking into account the configuration of societies nowadays.

305
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And the idea that if you take into account the configuration of societies nowadays and the idea that if you take into account some other measures for example domestic violence or the fact that the outcomes from the labor market for winning in general maybe or in some particular areas maybe more difficult because traditional values are made to say

306
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that we need to take care more for our children or if you if you take into account for our children or if you if you take into account for our children or if you if you take into account for our children or if you if you take into account so their work at home that is not so paid and so on so basically this is

307
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what the intersectional approach is saying that there are specific groups that are, that have cumulative disadvantages.

308
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Because of other factors that are influencing their lives. And, basically, only this is what we also, I thought in this case.

309
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That to see what extent considering only this particular groups or we can further have a see an impact on other factors for example I told you about health but another one would be, twice extent.

310
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So. At this particular, configuration of characteristics. This particular, combination of portraits.

311
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Practice is influencing, occupational outcomes or occupational prestige.

312
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And so on so it's not about to something that is in or in these categories, but basically the comparison between them and the others.

313
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Maybe if I put your gender instead of females or, their marital status, you know, instead of leading alone or maybe only education instead of considering a lower higher education and but behind that you have to choose some categories higher or lower categories and then you can see that all these configurations.

314
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Have certain impact or that is high on other outcomes. I will buy you. Provided the network.

315
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If you're going out, we may need to move this to email exchanges or if you have some more time we can go back to that.

316
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I don't know if you're happy with the answer so so, okay. It's of course the battle, but now it's the time for Anna finally already announced.

317
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Thank you Corin Avance again. And

318
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Yes, we should. Now we will be together. So. The screen is yours and Mike is yours and this Time to wait.

319
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Thank you.

320
00:54:01.000 --> 00:54:09.000
Thank you. Hello everyone. I'm very conscious of time so please forgive me. I will go very quickly over my slides and I will probably speak way too fast.

321
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And on the top of that, I will use the last 30Â s for the checkout or promotion of the book recorded it with Anawanka and the cross-section that we would like to invite you.

322
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To be a part of. So today I would like to contribute to this session with some very short overview of the Experiences we made in our project that was organized in Austria.

323
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And it will be all about participatory approaches with other adults. I don't hope that in this room we are more or less familiar with Vat as part of our approach but please believe me it happens sometimes that when I mentioned participatory approaches people think that I'm talking about interviews.

324
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So no, of course, this is taking the case once the father and us soon as I figure out how to change the light I will bring you to them.

325
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A context. The topic for today. So as you probably noticed more and more researchers and more and more funding bodies call for democratization of science, which translates easily to this.

326
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Appeal to involve are different groups of participants more in the role of co-creators and active participants of the research process then merely the objects of it.

327
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So here I'll be talking more about doing research. With other adults rather than just about them. And of course the arguments behind it are multiplied by numerous altars.

328
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And you can. Use the time outside the session or I would be delighted to just talk with you more about it but just keeping the time very short just to mention that this actually comes from To end, so the first one would be to.

329
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Broken the need of having the data that are more accurate and closer to the lift lights of the groups we were interested in and secondly exactly this trend of bringing the science closer to people and being done by the people.

330
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And if we agree on that, there is obvious conclusion that, OK, then we need some methods and approaches that allowed to meaningfully involve different groups and here I will be focusing on all the adults that traditionally might have been not only overlooked but underrepresented and not heard in the mainstream research.

331
00:56:24.000 --> 00:56:40.000
So the idea is great and it creates a lot of opportunities. However, as usually it is in the cases with rising new trends although this is not such a new trend like the butts what you approach is which all the adults started gaining up their attention already in the eighties.

332
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But what I argue here the main issue is that okay we do understand this need we want to do this but we lack Clear process of documentation.

333
00:56:48.000 --> 00:56:57.000
How to actually do that if you check the research papers and reports that report using participatory approaches with older adults.

334
00:56:57.000 --> 00:57:14.000
You will notice that they are not always very well described. And the basic reading for that would be the text of James and Buffalo from 2,022 where you can actually see that review of papers that applied by this battery approach so I encourage you to take a look on that.

335
00:57:14.000 --> 00:57:25.000
But bringing you closer to that what we did I would like to use the example of 7 projects so this is socially excluded all the adults voices and experiences.

336
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And this is actually amazing. I need to mention that the context of Austrian funding agency actually allowed us to do this.

337
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This was a spin-off of another project and we didn't this pot of money they actually made it very clear that this is only for participatory projects for Citizen Science Project.

338
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That would build up on already existing products. So we use this opportunity and I am aware that in many countries participatory approaches such as citizen science are not really very well funded are not really well supported so yes Austria that it's does it and they've been great with that and this allowed us for a lot of flexibility and we did learn a

339
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lot through this process. And this is that's what I want to share with you now. So what we learned just to provide you the really short context I wanted to show all the steps that were involving active participation of older adults.

340
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So during the first consultative form, we invited older adults and local stakeholders interested in the topic of So social exclusion of all the adults.

341
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And there we designed more or less the overall idea for the project, then it was followed by peer researcher training for older adults interested in contributing in that way to the project then we collected and analyzed data together.

342
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And finally in the consultative form too we brought it back to the stakeholders and other groups of all the adults who didn't collect the data.

343
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And now we're at the stage where we try to disseminate results. And you are the lucky audience to witness that.

344
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And so today, focusing only on And that what we Experience was really critical for our process and we think that also that would It was mentioned at the beginning of the session that I thought this is like really some basic introduction to that what I want to say, that indeed, oh, that we do how we approach.

345
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People we work with really impact the research as We heard that and here in the context of participatory approaches we would argue that it impacts it even more.

346
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Therefore we need to be Very cautious about what is happening during the whole process. And how does my impact not only the way We generate the knowledge but also the way What type of network is being produced?

347
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So here in order to support ourselves in this system, we use the concept of was dividing the different types of Reflexivity team of to the through the personal interpersonal methodological and contextual aspects.

348
01:00:04.000 --> 01:00:08.000
So If in case it's not self-explanatory, I'll just quickly say that.

349
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Personal Context was what reflect their relations between co-creators. So in our case as a academic researchers and our non-academic participants and also the relations between non-academic a researchers themselves.

350
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And the expectations that were involved in that. Sorry, I went already one step. Father so personal that will be our expectations throughout the process and to our participants interpersonal that would be the connections between academics and academics and non academics themselves.

351
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Methodological in our case we were dealing with social exclusion. So this is very sensitive topic and we label this as a citizen science approach.

352
01:00:53.000 --> 01:01:08.000
This also led us to relying on gatekeepers. In helping us to target the people who are at risk of social exclusion and obviously this might have led to some vases in the equipment process, so we are aware of that.

353
01:01:08.000 --> 01:01:17.000
And contextual aspects for us as I already mentioned this meant that we're lucky enough to get the money for a citizen science project, but it also meant that we tried to conduct it during the COVID.

354
01:01:17.000 --> 01:01:26.000
19 pandemic. And, the topic that we chose that's to have chosen work was not really easy.

355
01:01:26.000 --> 01:01:38.000
So here you can see what we actually did in all to support our reflectivity throughout the whole. Process it was full of regular meetings, meetings, ad hoc meetings, consultation and constant discussion.

356
01:01:38.000 --> 01:01:45.000
But the main thing I'm sorry, just quickly check the time. Yes. The main thing I would like to kind of leave you with.

357
01:01:45.000 --> 01:01:54.000
That or actually I will move even further to that so the final version this might seem a bit complicated. But I hope I will be able to.

358
01:01:54.000 --> 01:02:03.000
Explain it clearly. So What we see as the corner's turn of participatory approaches with older adults.

359
01:02:03.000 --> 01:02:11.000
Would be meaningful involvement. Of heterogeneous group of older adults. So maybe I can show that like so the meaningful involvement of heterogeneous groups.

360
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Of other adults who can contribute. They've fought and they vision in truly co-created process.

361
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So this basically means that we need to Ask our like be in this process of constantly asking ourselves whether that what we're doing is supporting meaningful involvement.

362
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Whether that's what we're doing is actually encouraging the contribution that other adults want to make. Whether the power relation with the project actually support or hinder the meaningful involvement and finally which is very often the main question for us in dealing with a sociology of aging and doing research.

363
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On aging whether the we can really capture the heterogeneity of all the adults within our products and of course with participatory approaches We already kind of have this

364
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Not assumption, but we can actually expect that people who would be willing to. Investor time and investor efforts.

365
01:03:12.000 --> 01:03:31.000
Will be overrepresenting a group of better educated, more like representing the more educated and better like sorry I just my English now But there are research on that for example Ariana Poly wrote a great paper on it so you can actually check all the.

366
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Criteria that are being overrepresented and not fully contributing to capturing the heterogeneity of other adults.

367
01:03:37.000 --> 01:03:48.000
And in order to critically reflect on that What we found was working for us in 7 and I hope you just could also be useful for you.

368
01:03:48.000 --> 01:04:04.000
Is applying those 4 aspects. Of ongoing reflectivity. So reflecting on this personal interpersonal contextual and metadata methodological level levels in context of each of those dimensions.

369
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So it does require a lot of question. And on the top of that. What I really wanted to.

370
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My clear is the fact that it's not enough to reflect it only at the beginning of our process when we plan it or at the end when we were already finished.

371
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Because the research projects as you are very well over are very dynamic practices. And so is the inclusivity or exclusivity of participatory approaches?

372
01:04:29.000 --> 01:04:36.000
So we need to do it. Throughout the whole process. That's why you can find here the timeline.

373
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And what I find also very important to mention and highlight that true this reflectivity throughout the whole research process.

374
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We also need to think how it interacts with this macro, meso and micro level.

375
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So. Here I would suggest to understand the micro level as the mostly related to interactions within the project meso level as the institutional context so that For example, what happened for us in 7 is that some of the gatekeepers involved in our project left their position and we needed to wait for another one to step in and therefore

376
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we were able to include the second group of participants later in the project. What had also the consequences that we were already smarter with the second group.

377
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We were already able to adjust our approaches. And I will be open about it lower our expectations because we entered the field with way too high expectation what became very obvious after the if your first meetings which actually also shows how dynamic this process is.

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That you can constantly learn and I think we really did great job in terms of learning. I hope also maybe in terms of actual research but I think for all of us involving this project, it was an amazing journey.

379
01:05:48.000 --> 01:05:59.000
And I think we really have this. Well, maybe naive, but still this does believe that this is possible if we will practice our reflectivity and this is my summary, like the conflating remote.

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If we. Invested efforts in asking ourselves constantly whether that what we are doing is actually inclusive or exclusive or when it changes the position because it might be the case that what we find inlusive at the beginning of our research process later on turns out to be not so inclusive as we thought as we planned.

381
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So if we actively Reflect the like imply the reflexivity toward the whole research process we might actually be able to challenge the existing context.

382
01:06:32.000 --> 01:06:37.000
Like I believe that many of you who tried to get funding for participatory approaches stumble upon the problem of for example a particular problem.

383
01:06:37.000 --> 01:06:54.000
The like universities quite often are not ready to do this. We don't have the resources to make it really work starting from ethical approval going through the reinforcement for the participants.

384
01:06:54.000 --> 01:07:03.000
And finally to making sure that they can equally contribute to the dissemination of funding. So as I promised the last 30Â s go to the GKE outer promotion.

385
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I would like to draw your attention. To discuss action that is on participatory approaches with all the adults.

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If you are interested in joining us in this international endeavor of advancing the field of participatory approaches with other adults just go online and type in cost action and this number below so see a 2 2 1 6 7 and there you will find all the information you can apply to join.

387
01:07:25.000 --> 01:07:36.000
The group and we would be delighted to have you there. And the final remark would be that Please, okay for those of you who would like to take a picture.

388
01:07:36.000 --> 01:07:49.000
Please be aware, soon enough, so I believe it should happen in September. There will be an international route that handbook on participatory approaches with older adults coming up and we with Anabanka were very proud of this volume.

389
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We encourage you to take a look. There are some contributing outters in the room. So I really hope you will get something from it.

390
01:07:57.000 --> 01:08:04.000
Thanks a million. I hope I didn't use that much of the time.

391
01:08:04.000 --> 01:08:13.000
Don't. Thank you. I think you've done great with the time we are slightly behind a schedule but still within the frame we are slightly behind a shadow but still within the frame.

392
01:08:13.000 --> 01:08:17.000
What I hear from we are slightly behind a schedule but still within the frame. What I hear from all the different presentation, but still within the frame. What I hear from all the different presentation is investment.

393
01:08:17.000 --> 01:08:20.000
Time, what I hear from all the different presentation is investment, time, energy, you know, getting together.

394
01:08:20.000 --> 01:08:29.000
But what are your experiences in the room? Would you like to add? Would you like to add something to Anna's talk or ask her some question.

395
01:08:29.000 --> 01:08:38.000
I don't know if you have something online maybe also no Look, go ahead.

396
01:08:38.000 --> 01:08:42.000
This is so wonderful. I just I'm such in favor of this. It's so important.

397
01:08:42.000 --> 01:08:45.000
I and I was thinking when it's so important. And I was thinking when you were describing this as I don't know.

398
01:08:45.000 --> 01:08:53.000
And I was thinking when you were describing this as I don't know, since I don't know, I don't know, since I don't know, since I don't know this literature, is there a movement to incorporate this approach with survey research and on a larger scale that you're aware of to incorporate this approach with survey research on a larger scale that you're aware of if you could tell us a

399
01:08:53.000 --> 01:08:59.000
little bit on a larger scale that you're aware of and you could tell us a little bit because I think it's so important for them to begin

400
01:08:59.000 --> 01:09:10.000
Thanks for that. Yes, of course. There might be any impression that this is limited only to qualitative approaches, but naturally there is a growing movement and interest in creating the co-creating.

401
01:09:10.000 --> 01:09:22.000
The service one of the amazing examples that I've might be really interesting for you is the work work done by Charles Spout Grave in New Zealand where they tried to not try they actually did develop quantitative measures with Maori people, so indigenous people from New Zealand.

402
01:09:22.000 --> 01:09:37.000
So this is happening and there is growing interest in that and I really hope that if you would like to join the cost action there we can bring all the great minds together and we can jointly move it forward.

403
01:09:37.000 --> 01:09:45.000
So. I hope this, yep, just answers your question. Okay. Do we have some more points?

404
01:09:45.000 --> 01:09:52.000
Now then, thank you once again, Tina. Thank you. And we move to another.

405
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Anna and we'll see if this dust something for us. No, no, that's So, let's go.

406
01:10:04.000 --> 01:10:11.000
That's cool. Let go. That's the, that's, I think it's actually also, I could be used as a.

407
01:10:11.000 --> 01:10:19.000
What would do the key word for the participatory approaches, right? Let go. And so I'm letting go here as well.

408
01:10:19.000 --> 01:10:29.000
But I don't think do we have our next presenter? Actually, in the Zoom is Anna.

409
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Prison. Doesn't seem to be the Okay. And we don't have her presentation pre-recorded.

410
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If that doesn't change in 1Â min or so, we can use the time for continuous debate on some of the topic that we.

411
01:10:53.000 --> 01:11:07.000
Yes. Okay. Okay. Yeah, but none, none from the The presenter.

412
01:11:07.000 --> 01:11:12.000
Okay, so we'll just take the comments from.

413
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From the chat.

414
01:11:17.000 --> 01:11:26.000
Just don't know where to store it. Okay, I'll start on the top or maybe if the person who wrote the comment is in the room.

415
01:11:26.000 --> 01:11:35.000
We can also take them, or in the zoom room. Marina, if you would like to.

416
01:11:35.000 --> 01:11:39.000
No, she doesn't seem to be here, right? So I'll just read it through.

417
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We have used some migration related variables that are included in share. So there is some information on it even though it could be better.

418
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See the paper for more information from Rodrigo Serat and Sandra Torres and others civic engagement amount foreign born and native born older adults living in Europe.

419
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It's was published in European Journal of Age on Aging. This year And then we have something queues and one issue is that the respondent needs to have sufficient knowledge in the language of the country of interview to be able to participate so the foreign born who are included in share is the sense a select tech

420
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group. And, and I think it's an important issue also to include in quality quantitative sorry research groups that have low lumber of cases and samples.

421
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That's for Karina. Would you like to elaborate that, Corina?

422
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Oh yes, sure. We also thought about the approach I presented to you that may be useful because you can include the variables that have some low number of cases in some categories.

423
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So basically there may be variables like migration status or ethnicity being being part of an ethical minority group that may have a low number of cases in that particular minority group that may have a low number of cases in that particular sample and you are able to include that without a low number of cases in that particular sample and you are able to include that without

424
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intersecting without making an interaction term with some other variables and to have a lower and lower number of cases.

425
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Thank you.

426
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Just anybody want to follow up on that? Looking in the room and then the zoom.

427
01:13:48.000 --> 01:14:05.000
Doesn't seem to be the case. Are there any other suggestions for our topics for debate? Checking out this guys over there.

428
01:14:05.000 --> 01:14:06.000
I'm here, but I cannot hear.

429
01:14:06.000 --> 01:14:14.000
Francesca? Yeah, yeah. Yeah, you, you will, you will get your question.

430
01:14:14.000 --> 01:14:15.000
No, I can hear you.

431
01:14:15.000 --> 01:14:26.000
A lot you're still there because I know it's literally the middle of it. Yeah, so thank you for your presentation as well and it was hugely impressive what you said about your field work.

432
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I mean the sheer persistence and engagement and the sheer persistence and engagement, I mean the sheer persistence and engagement and the returning to them.

433
01:14:33.000 --> 01:14:52.000
In order to, I suppose, really drive the quality of your data and your investigation. So I'm just curious to hear a bit more about how you relate the way in which you are doing the fieldwork to your understanding of.

434
01:14:52.000 --> 01:15:05.000
Quality of qualitative research. However you define that. I'm asking this because I'm working on a paper that's sort of conceptualizes quality as a relational process.

435
01:15:05.000 --> 01:15:17.000
And from what you were saying I could hear a lot of resonance with this idea of research being a profoundly relational process.

436
01:15:17.000 --> 01:15:40.000
And yeah, actually this sort of relates to the last paper as well. Which was kind of very strong under the theory and the concepts, but I'd be sort of curious to hear a few examples of how you achieved these things because you know they're not easy to achieve like genuine participants meaningful engagement.

437
01:15:40.000 --> 01:15:50.000
Contribution and bringing in a heterogeneous group of people and for you as well how You understand what you did.

438
01:15:50.000 --> 01:15:55.000
Relates to the quality. Thanks. Thank you.

439
01:15:55.000 --> 01:16:02.000
Thank you so much for that question. That's a really good question. So first I will say, well, I am a mixed method researcher.

440
01:16:02.000 --> 01:16:18.000
Okay, so I need to say that allowed because I really don't believe so much in this distinction between qualitative and quantitative methodologies, but I know that that's not so.

441
01:16:18.000 --> 01:16:31.000
Popular opinion maybe. So at the second theme that it makes a lot of sense for me is what you were saying about relational production of data.

442
01:16:31.000 --> 01:16:43.000
And I definitely believe in that. And I get that. Actually I really embedded with, relational sociology.

443
01:16:43.000 --> 01:17:11.000
Someone that I follow up a lot and all her research is Kathleen Grisman. And the whole narrative approach and about how to use, interviews to actually this kind of data and that the interviews are not only something that we go into the field or collect our interview and then we have one box check.

444
01:17:11.000 --> 01:17:24.000
So. What I would say is that. I think actually I definitely believe that this kind of data is co-created even if we don't want to do it.

445
01:17:24.000 --> 01:17:36.000
So there is a lot of research around how we perform the data and even in the most Quantity moving districts as a kind of surveys we have done for a long time.

446
01:17:36.000 --> 01:17:44.000
We all know that the way in which we ask questions the way in which we express these questions.

447
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The person who is doing the questions is also having a role during the field work. So for example something that helps to me without even wanted to be.

448
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Something that helps me. Something that I didn't control is that I look like a grand child, for them, for a lot of them, for a lot of other people, they treat me like their grandchildren.

449
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They were very glad to be there and So talking about this stuff because a lot of them were really isolated and they were really without company.

450
01:18:12.000 --> 01:18:42.000
So obviously this was a great moment to have a visit and the whole idea of er, being completely honest about the research I share with them about the research about how was in that moment I was living in Manchester so sharing with them about how was living in UK because for a lot of them it was like they have never traveled outside the

451
01:18:42.000 --> 01:18:51.000
country. So that also creates some kind of connection and I will say that we don't need to be so afraid of actually sharing those stuff because.

452
01:18:51.000 --> 01:19:02.000
We don't, I get the impression and I really, agree in this with Catherine Brisbane, the author about narratives, analysis.

453
01:19:02.000 --> 01:19:16.000
Is that the people that we interview, they are not, if we treat them with not the same kind of information that we have or if we are not completely honest or if we, er, for example, tend to use this kind of techniques in which we don't give them some kind of techniques in which we don't give them some kind of agency.

454
01:19:16.000 --> 01:19:33.000
Used this kind of techniques in which we don't give them some kind of agency. And we actually treat them as they don't know comparison with us, the researchers.

455
01:19:33.000 --> 01:19:42.000
And I think it should be in the other way around or at least equal. They know a lot of stuff.

456
01:19:42.000 --> 01:19:58.000
They have a lot of experience. Some way to be respectful about those things and I think the way we approach to available that's also creates some kind of environment that actually perform that kind of data and that's why for me it was super relevant.

457
01:19:58.000 --> 01:20:13.000
This relational aspect that you mentioned for me is crucial because definitely it's not something that And we are going to have it in there, even if we don't want to.

458
01:20:13.000 --> 01:20:14.000
Yeah.

459
01:20:14.000 --> 01:20:17.000
We have some influence from the environment into the data. And the, the data is not in a bubble and it's not something like.

460
01:20:17.000 --> 01:20:24.000
It's not environment or context related. So if we can Be completely open. About this kind of stuff.

461
01:20:24.000 --> 01:20:35.000
And make these kind of statements is also some kind of a even almost like an activist.

462
01:20:35.000 --> 01:20:41.000
Kind of role that we could have as researchers. That we sometimes forget about this kind of stuff. And we live in our academia.

463
01:20:41.000 --> 01:20:55.000
Yeah.

464
01:20:55.000 --> 01:20:56.000
Yeah, that's

465
01:20:56.000 --> 01:20:58.000
Bubble and then we go to field work and we need okay we need 30 interviews let's go 1 2 3 4 and it's not like that it's like we are in meetings we need to remember that but thank you so much for that and we'll be looking forward actually to read about.

466
01:20:58.000 --> 01:21:05.000
But thank you so much for that and we'll be looking forward actually to read about your article if I have the chance I would love to read up on your article if I have the chance I would love to read up on your article if I have the chance I would love to yeah I don't know you because I have the chance I would love to yeah I don't know you because I cannot see you

467
01:21:05.000 --> 01:21:11.000
because I have the camera only for the morade dator, but I will let to me.

468
01:21:11.000 --> 01:21:18.000
We are glad to have you and it's just there are so many things that are now in in a play.

469
01:21:18.000 --> 01:21:32.000
I was just about to ask the colleague in the back if you have something to this point or you want to move.

470
01:21:32.000 --> 01:21:33.000
Okay.

471
01:21:33.000 --> 01:21:37.000
Yes. Yes, and if you come to come in front and if we will just go back to Anna and for her tips and tricks.

472
01:21:37.000 --> 01:21:55.000
We'll come. Thank you very much. Thanks to all the presenters. In methodological innovation so that I'm going to take that to share with the team I work with the Social Agent Futures Lab in Perth.

473
01:21:55.000 --> 01:22:00.000
Yeah, I'll be really excited to hear how they are here today. My question was tips and tricks again.

474
01:22:00.000 --> 01:22:14.000
So hearing you talk about participatory research we're always trying to bring older people into our research and being here in Australia with the heterogeneity in that word of the older population.

475
01:22:14.000 --> 01:22:27.000
Particularly around language is a huge challenge that we're really working with and of course there are institutional barriers that you pointed out as well, not just ethics but the challenge we have is around things like payments.

476
01:22:27.000 --> 01:22:47.000
So institutional barriers to actually getting the first month of funding and then second finding mechanisms to pay people because giving them supermarket vouchers is something, but sorry my question is Which, well, so what kinds of you talked about?

477
01:22:47.000 --> 01:23:02.000
Resetting your expectations. I guess my question is around what kinds of data and what methods do you find work best when you are working with older co researchers.

478
01:23:02.000 --> 01:23:09.000
Okay, perfect. Thank you for that. I'm not sure how I don't have to say back to the audience or I would just move.

479
01:23:09.000 --> 01:23:18.000
Here. Okay, so exactly thank you for the last question because This will give me the opportunity to reflect and again bring our experiences from the field.

480
01:23:18.000 --> 01:23:31.000
So initially we started with this very open approach that we will just ask the group of older adults that decided to contribute to the data collection what skills they think they are recognising themselves who present them with different approaches and we let them choose what they want to do.

481
01:23:31.000 --> 01:23:40.000
So this group ended up doing Individual interviews. Focus group and outward photography. So those were the tree metals they used.

482
01:23:40.000 --> 01:23:50.000
But we are that this is overwhelming for them and for us. Therefore when we started working with our second group which was actually a group of older women with experience of homelessness.

483
01:23:50.000 --> 01:24:04.000
We decided to go with the photo voice as we thought this might be easier to Give them the complete overview of one method that seemed most suited for this group of participants who were also facing different mental health issues as well.

484
01:24:04.000 --> 01:24:20.000
So that's what we bid. And, the main Trick or teeth would be really I know that we all talk about it and in our group we also talked about it a lot like Be flexible.

485
01:24:20.000 --> 01:24:37.000
And responsive. And I think that's the most general. Treat a general key that I could give that it really is a very different way of working, that you need to have this level of openness and flexibility to make it work well and I'm very much aware of the language issues.

486
01:24:37.000 --> 01:24:44.000
I think this will be one of the main challenge we will face in the cost action as well when we try to have international groups and we want to foster this meaningful contribution, it's absolutely crucial to be able to communicate.

487
01:24:44.000 --> 01:25:01.000
In the same language. So yes, obviously this is a talent coming back to the institutional limitations. I think you might be aware with the work of Amanda Grenier.

488
01:25:01.000 --> 01:25:22.000
They actually did prepare like very nice Policy briefs and overviews around how to support in like how to create the pathways towards the institutional support of true ring, not on the rainbow but actual payment for the curry searches so I think this might be very useful for you.

489
01:25:22.000 --> 01:25:38.000
I think I come from Colorado in my cultural and musical context it's not possible like we don't like even the discussion about the supermarket vouchers it's not quite there yet what we quite often do we just give gifts like a scarf or something and this is all related to the tax issues as well.

490
01:25:38.000 --> 01:25:45.000
So I think There are not shot. Hats and I think there is plenty of work ahead of us.

491
01:25:45.000 --> 01:26:03.000
That's why again, please check the cost action. Maybe we can figure it out all together and I think that would be great to gather different experiences from different contexts because I really believe that if we create this group that can work Better like with similarly to finding the right way of bringing the indicators.

492
01:26:03.000 --> 01:26:09.000
Jointly we can actually change the field. So it might be easier which time to publish with core researchers to recognize them as active controversy.

493
01:26:09.000 --> 01:26:19.000
It might be easier to reimburse them and it might be easier to support this meaningful involvement. And just if I still have you have, do I?

494
01:26:19.000 --> 01:26:27.000
So if I still have time, I will go back to this comment. You might, and I think in part as Butterior approach it's really important to think about quality in those 2 dimensions.

495
01:26:27.000 --> 01:26:42.000
So first of all the quality of data we produce but also the quality of cooperation. And I think in Our case there was plenty of learning processes which of course translates to We did, some unexpected challenges.

496
01:26:42.000 --> 01:26:56.000
So we had withdrawals, we thought that the things we planned so we had withdrawals we thought that the things we planned so for just one simple example would be we provided the things we planned so for just one simple example would be we provided our participants with one simple example would be we provided our participants with the one simple example would be we provided our participants with the transcripts which timestamp

497
01:26:56.000 --> 01:27:01.000
because one simple example would be we provided our participants with the transcripts which timestamp because we wanted to train them in with the transcripts which timestamp because we wanted to train them in providing the training with coding the data.

498
01:27:01.000 --> 01:27:10.000
We wanted to provide them the training with coding the data and one of the buttons and we thought, we wanted to provide them the training with coding the data and one of the buttons and we thought okay we make it like the font super large so It will be easy we selected the part of the transcript that wasn't very

499
01:27:10.000 --> 01:27:21.000
complicated that was easy to follow and we thought okay we ticked the box of making this accessible but of course one of our participants got so frustrated with the timestamps like he was looking at it and said no it makes no sense to me.

500
01:27:21.000 --> 01:27:39.000
I can't read it and just put it away. So this reopened her eyes to the fact that what we are used to is not necessarily that what is It's very inviting for people who lack the academic training and of course thinking about research training that we try to do in, I think, 3 sessions.

501
01:27:39.000 --> 01:27:51.000
Of course it's. It's not possible. And we were very lucky in this project that the project allow for flexibility and I think we had very committed team so there was a lot of extra time.

502
01:27:51.000 --> 01:27:59.000
Invested in that but I think it paid off in terms of when we organised the final reflective meeting with our participants.

503
01:27:59.000 --> 01:28:18.000
They were very happy. So I think that was the main indicator of whether we succeeded or not is the fact that actually I think we were able to create some Hi levels of reflexivity in them around their personal situation and also some of the social connections they had got strengthened.

504
01:28:18.000 --> 01:28:24.000
So. I'm not sure if that really answers the question, but I'm really open to have some tea or coffee and share some more insights.

505
01:28:24.000 --> 01:28:40.000
Thank you. Thank you. But we may have another follow-up to these. For example, in Czech Republic, we don't have that many problems with paying the, of course it's a bureaucratic process but we could probably pay the voluntary score creators but we are not allowed to keep their

506
01:28:40.000 --> 01:28:46.000
contacts. So I was like, OK. And I actually went to the meeting with the ethical office.

507
01:28:46.000 --> 01:28:50.000
I said, if I want to send a postcard to thank you, I need to have address.

508
01:28:50.000 --> 01:28:58.000
No. So it was a great negotiation. And one of the things also back to the funders as well, they need to be ready for unexpected results.

509
01:28:58.000 --> 01:29:19.000
We have also 2 different types of scientific agencies in my country and one is kind of expecting that you will know what you will find out at the very beginning when you were writing the proposal and then it's very difficult to come to them with the co-creation and then this other one who actually wants that you write at the very beginning what

510
01:29:19.000 --> 01:29:33.000
types of risks you are expecting and if you don't are not a very of very stable not found you so they are very open to anything can go wrong and we know about it so obviously you know which one I like to work with.

511
01:29:33.000 --> 01:29:52.000
But any other types of tricks in my shower we still have 20Â min I don't know if that's correct but we have 20Â min I don't know if that's correct but we may also use them for not so structured session in debates with mics that would of course leave out our zoom friends which is

512
01:29:52.000 --> 01:30:02.000
unfortunate but probably if this is something that the room kind of has decided by their looks. We will, we will end the session here.

513
01:30:02.000 --> 01:30:14.000
Thank you once again for being so open to risk as this one goes and and we I think we did a great job and thank you once again to everybody here in the audience and the presenters here and at the Zoom for another very good session.

514
01:30:14.000 --> 01:30:17.000
Thank you very much.

515
01:30:17.000 --> 01:30:20.000
Thank you. Bye.