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okay, okay, good morning. And hello. Everyone. My name is Turkish Hammondo. I already lost the 10 min. But, anyway, so let me try to make my presentation on on on time. My topic is how to make a kind of a comparative research about some kind of national policy studies and the policy implications. So in doing it. So I'd like to

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to propose some kind of nesthological keys to make more kind of accurate and objective cooperative research at the global level.

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Yeah, that's background is kind of the in the last couple of years. We a have a kind of Raj, is the common experience that a pandemic of Covid they've got quite a few rolled out issue. Everyone's got affected by that. That's why. So I'm thinking, to make use of such kind of a from a global comma experience to brush up our kind of internal compiler. comparative research.

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That's why the background is how we are able to recognize Covid as a comma experience. And the second point is, we got the national report as a source of Social national discourse on the family. The key point is how I'm able to kind of make use of such kind of a national survey or national research about the experience of covid for comparative research materials.

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The third point is how to propose a media for comparative in this study of the how many policies in global sociologist? Because I'm a former primary sociologist as a family sociologist and also interesting global comparative research.

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Okay, aim of presentation. is the following, first, I propose an article attempt about comparative studies on national primary research. actually. So I did it once last September in the Regional conference of this kind of research committee handling online and the Japan. That's why this is kind of more kind of an improved version of the previews and presentation.

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And second point is how to gratify cost and the benefits of the comparative methods in sociology. This is the sociological, methodological kind of inquiry. Ideas about my research method

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mit Ctl, and a third point is how to attempt. introduce kind of robot a functional approach. This is a key approach in both theoretically and methodologically. In my research proposal to this course, national comparative family research one.

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Okay? And this is a research case. I picked up 2 research cases for this analysis. But both took reporting about most actually, it was reported about experience of family rates in during the COVID-19. And the first example is Call 3 and all 3 on the survey. It's called the Primary. It's in Australia, Sunday by Australian institution, primary studies.

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And second point is second, the matter here is Japanese service life consciousness under the impact of COVID-19. Also, research people on the impact of the pound in COVID-19. I don't detail those kind of reports at this time that in my presentation the major topic is how I'm able to actually be comparative research by using those different about tigers issued independently in different countries

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and discussion. It's the first discussion point is how? I'm able to make a way of controlling. It's all kind of equivalent to measures in this grocery families that is, such kind of the development of equivalent measurement equivalent to measures should be the most important kind of a a research topic in comparative sociology and comparative studies. So in doing so. I consider the

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3 points how to focus on service conducted by national institution. This is a call aspect for a equivalent measurement. Second, the point is that there is a kind of comp compatibility of service on the same social issue, because both reports talked about the same social issue. I mean COVID-19. There's some other point. It is a strong, a synchronymnity, or those researches and

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those research paper released on the same period and the same time field. Those 3 points should be considered as a kind of equivalent measurement in my research.

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Okay? And the second points more advanced topics. but that's why. So in doing a in in the following slides. So I'll start from talking about benefits and a good point of those kind of comparative studies. And the later I submit more kind of diff card from I haven't dissolved yet

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in my research first is a benefit to clarify those units in this analysis. First, it enables it to conduct a meta-analysis of national survey on family policies.

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A second point is, clarify an article units by examining the sites of questionnaires, of surveys rather than report of debates from from each report, because so what I a study? what those who are doing policy studies. They often adopt any particular kind of measurements or a variations for comparison.

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But in this research, I try to do more kind of culture. And for I mean, I should say, what kind of ethnic methodological analysis. because national Survey reflects about each National and Culture society and other kind of social Id, or and it's a case in particular, among family studies and the funding surveys.

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Yeah, but of course we have to do it. We have to proceed it in the carefree, because there is some point to be undeserved.

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Yeah. First, the point is case very bouncy, and the second point is a qualification of the measurement of each case. I have limited to you mentioned this in this presentation.

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And further point is how to identify national context of family in this comparison, because each national, a context so much unique and each national state of the long history of the Development Department to state that they find the history and culture background. That's why. So thinking, I want thinking about those kind of differences. How we able to achieve such kind of a comparative research amongst those kind of national survey data and even national survey questions.

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Yep. And to us, those kind of programs issues I direct to set up for the kind of some kind of suggestions in the following first regarding a case where you can see call me to 19 would be the perfect case. Let's see, like, and we do game carried out to suicide as a good, resourceful comparison in our twenties.

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And the second point is, suffering in each survey. Suffering is always quite mad in any social research, of course. So we have to consider about the different types of sampling.

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And the third point is research, design and its differences. What is a purpose of research, or how they want to aim, what kind of policy implications they want to improve. This is a kind of good resource for comparison. To think about national identity and national social history and characteristic in that research. And the first point is defined different purposes of policy making through research outcomes

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mit Ctl. And this is more than that. I can advance the questions how each society or each country is able to appropriate use of such kind of specific marriage in policy making or what stage administration.

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In doing so, I'll try to introduce Robert Martin's functional approach

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in the following way, past let me try establishment of the common research problem. That's easy. COVID-19, it's a common problem. And let's try identify each. If we financial group, maybe state or a national research group would be regarded as a kind of different kind of reference or group referential group has a different.

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a referential program by sharing that kind of a particular specific set of meaning lists and values

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which is so much indifferent from other referential groups or parties. And then I'm a let's try underwrite a particular call to set of each referential referential program, or good, because, every country, every institution set up as this particular set set of questionnaires, questionnaires, and the framework of analysis.

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And this is a kind of a comprise of each different carrier. The meanings, like ethnic methodologist or a cultural anthropologist that does in their research.

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And this is a kind of overview of of such kind of The uniqueness of my research. So in the multiple times, so international comparative research policy banking and the policy studies normally set up one very objective and universal sense of evaluation, like established by United Nations and other famous researches.

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and they compare each cases in light of those kind of major or kind of universal evaluations.

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But in my concerted research a, as you see in the right video, I try to carry out more kind of ethnol mesh approach in that kind of growth or comparative policy studies to pick up each kind of different groups of each differential groups and try to set up some kind of So

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what sanctuary equivalent to components, and after picking up functionary equivalent components between in case A and the K speed, I will find another case C or a case d for for that comparison by using such kind of a functioning equivalent components, I found through my trust researches.

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All right. And now let's do a wrap up my presentation. And what kind of benefits from my mesology is a kind of a contrast to the frameworks to identify the national family into reports.

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and maybe through out of the research I could to figure out, what does a family and a national by a fair treaty. This is a quite a case in Japan, but but not fund in Australian studies. For example, how kind of such kind of charity and the preparation is connected in such kind of primary discourses in each State and the second points, primary and agenda. In domestic work, for example.

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gender issues and sexuality issues for a comparison. And the son of the call some point is more kind of a unique, and what a broader comparative between the kind of Western society and the Normal Style society. What kind of a modern society, like a kind of institutionalized, individual, individual, institutionalized individual

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these are the a familiar with. There are many Asians. Cross talked about such kind of difference between in Asian primary policies and Western societies like that.

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And some further questions should be a a explorer at a a after this presentation like this. how I'm able to set up alternative an article method of national policy research in comparative sociology.

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And the second point is how to describe the normative and national record enabled in objective research. this is a kind of good at the power of comparative research to extract some kind of a current objective call to set in the research itself. And the third point is, you know there is a availability of international confirmative analysis through functional approach. And it's

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strings rather than kind of top down. If our Asian we should be more careful about each society's east national context and the defined, the cultural social background. And the first point is, maybe we should think about more careful approach inevitable to the drop in. It's methodological challenge

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about this topic. Okay, this is a, and thank you so much. And actually. So I updated my slide. Pdf, because I found many typos and errors in the previous slide uploaded here. That's why. So just a please contacted to me in puzzle. I'm happy to share the latest version of my slides. Yeah, thank you very much.

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Ok, I'm Jay. Thank you, Dr. Hammer. And for the good start. I believe, both in terms of me.

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So just

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yeah, I I I I need to. I need to come to the mic and say once again. So it was smells and Neil smells of work on the on the presentation. Those who who watched us online and with with the second presentation was, a second and third presentation will be online. That's why

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we do not have questions right now. I mean, like questions of clarification or some substantial things to ask and comments. Maybe we will do optimize. We will do when we will hear all the

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presenters to give their papers. And thank you? Dr. Hamana. Yeah.

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Zoltan Lakatos: he's got it

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Zoltan Lakatos: here.

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What's that?

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Can you hear me? Okay.

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okay, we can just hang on a TV. I'll bring you up.

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Zoltan Lakatos: Okay, so, can I share my screen?

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Just a second.

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Zoltan Lakatos: Yeah, okay.

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Zoltan Lakatos: so I can start sharing my screen. Right?

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Wait. Wait. Yes, you can. Yes, I can. Okay.

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Zoltan Lakatos: I can. So

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so let me let me make a formal

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of your presentation. We have Sultan Lakotos from Budapest University of Technology and economics with the

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paper that is on that that you see over there. And now he will share his screen

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result on the floor is yours. And as we agreed, 20 min. Okay, thank you very much. So you can hear me. Okay, is that right

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Zoltan Lakatos: on? Okay, in the conference room, I start sharing. So here we go.

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Zoltan Lakatos: So you can see my slides.

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Yes, we can.

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Zoltan Lakatos: You can. Okay. So, starting up, my name is Otta Lakash. I'm from the Budapest University of Technology and Economics. And the title of the talk is that end of construct variance

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Zoltan Lakatos: and how to work around it with geometric data analysis. Now.

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Zoltan Lakatos:  course, cultural researchers have long been preoccupied with measurement equivalence, especially in qualitative research, where a central question is whether the various indicators collected across different cultures, indeed, that the same phenomenon, if they don't. Well.

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Zoltan Lakatos: then, is the proverbial app to oranges problem. And my focus here is late and constructs, i. E. Those emerging from multivariate analysis, a very brief review of what it takes for 2 latent constructs to be fully equivalent. They must be

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Zoltan Lakatos: 3 criteria. One is configural equivalence, so we should say the internal composition must be nearly identical in terms of variables and the loadings.

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Zoltan Lakatos: Then there is metric which say one, a unit at the scales being compared, expresses the same difference like a cellular, the Celsius and the Kelvin scales, and finally, scalar, which is, say that specific points and the scales must have the same meaning. Not

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Zoltan Lakatos: late in post proxy. In a course, cultural study

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Zoltan Lakatos: very rarely satisfy all this criteria at the individual level. So this criteria are, it's fair to say, that are so stringent that they constitute a

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Zoltan Lakatos: barrier to comparison. Very often. Now I'm going to present a workaround.

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Zoltan Lakatos: I do. Individual analysis look for latent dimensions, do clustering and also compare subsets. and the illustration is from

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Zoltan Lakatos:  mixed methods, research specifically, its discourse analysis of coverage of 2 migration waves. In Europe. One is Jewish migrations, Jewish migration from the Russian Empire in the late nineteenth century.

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Zoltan Lakatos: and the other is The mid 20 tenths migration wave to Europe, involving Muslims, and by coverage I mean, The Hungarian press of the respective periods. So To give some idea of Jewish presence in Hungary. That's the distribution of Jews in the late nineteenth century.

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Zoltan Lakatos: Apart from receiving a steady influx of

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Zoltan Lakatos: Jewish migrants from Russia at the time about a million Hungarians. Around 5% were Jewish.

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Zoltan Lakatos: And next slide. That's the Jewish migration route from the Russian Empire to Western Europe in the late nineteenth century.

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Zoltan Lakatos: Now. that's the that's the

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Zoltan Lakatos: trajectory of migrants. In the most recent wave

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Zoltan Lakatos: the size of Hungary's Muslim population was never comparable to that of Jews. But the mid 20 s. Migration wave has significantly reframed public discourse on Muslims.

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Zoltan Lakatos: Now, the quantitative part of this study

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Zoltan Lakatos: includes so-called geometric data analysis.

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Zoltan Lakatos: Why? Gda, because well, because in Gda the focus is the space of observations press articles in our case. could you, could you please move the room. Audio, because it's kind of interfering here. thank you.

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Zoltan Lakatos: Well, so because in Gda the focus is the space of observations, press articles in our case and unlike in methods rooted in the general linear model. Like, you know, principal components and factor analysis. Gda does not search for meta variables that best capture the information contained in the input variables in Gda, the latent structure emerges from the data

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Zoltan Lakatos: rather than being imposed on them. And a typical method to describe these relationships is the Chi-square statistics.

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Zoltan Lakatos: So look at this distribution of discourse. Themes

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Zoltan Lakatos: identified in this study along these X's identified in multiple correspondence analysis on a horizontal scale. There's an opposition between racial I terms on the right

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Zoltan Lakatos: and relational terms on the left. Racial lights includes crowd out

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Zoltan Lakatos: parasites versus real refugees, corrupt culture, or they breed like rabbits, etc. On the right

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Zoltan Lakatos: as opposed.

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Zoltan Lakatos: They're just stigmatized by illegal ignorance, fear.

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Zoltan Lakatos: or the notion that religious tradition is not the same thing as fundamentalism.

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Zoltan Lakatos: or they are vulnerable, etc., on the left. There's also a vertical scale here, with an opposition between domination toward the top and being unintegrated to at the bottom. So wealth.

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Zoltan Lakatos: exploitation.

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Zoltan Lakatos: being alien reading others lives dishonesty, etc., on the top versus being alien

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Zoltan Lakatos: non-western and failure to integrate on the bottom.

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Zoltan Lakatos: There's also a third dimension, opposing compassion. on the bottom to conflict on the top. So violence in homeland deprivation.

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Zoltan Lakatos: fleeing persecution. hardships in general, etc., on the bottom.

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Zoltan Lakatos: as opposed to violent self-defense criminality.

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Zoltan Lakatos: a clash of civilizations. They have collaborators on the top.

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Now

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Zoltan Lakatos: all is set for isolating this course frames, in other words, doing a cluster analysis. But you know not quite. because already at this stage, failing to control for context will lead to wrong convolutions for an illustration. See the distribution of the articles

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Zoltan Lakatos: next slide.

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Zoltan Lakatos: look at this distribution! These are the individual press articles, colored and labeled according to the group. They cover Jews in blue and Muslims in green, so they are unevenly distributed. Coverage of Jews is concentrated in the positive range of axes, 2.

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Zoltan Lakatos: While coverage of Muslims in the Naga-five range. Here Jews are also skewed to our towards the right, the the racialized end of this horizontal scale.

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Zoltan Lakatos: No apparent concentration along X is 3.

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Next slide now dimension 2. The vertical one might be a measure of not only domination.

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Zoltan Lakatos: strong integration versus Greek integration, but also of being about Jews versus Muslims. Coverage of Jews is associated with wealth, exploitation, ruining others, lives while coverage of Muslims with alien being non-western, dogmatic, etc. If, in addition to these labels, the scale is also a measure

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Zoltan Lakatos: of Jewishness versus Muslimness, then we have a problem as a solution, we regressed. All article coordinates on the binary group variable

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Zoltan Lakatos: Jews versus Muslims. If any of the free scales is indeed also a measure of Jewishness versus Muslimness, then this will come out in significant r squared values.

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Zoltan Lakatos: and there you go. Access. Access to

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Zoltan Lakatos: is indeed also a measure of Jewishness versus Muslims, so is X is one, and to a much lesser degree, axis free with your or squares.

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No, no!

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Zoltan Lakatos: What to do with all this?

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Zoltan Lakatos: Well, to eliminate those effects, we use the residuals from our scales. That is the part of the coordinates that's not explained by the opposition between being about Jews and Muslims.

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Zoltan Lakatos: And now we see a modified distribution of the articles. Articles on Jews are present also along the lower half of access to, and vice versa. Articles and Muslims, also along the upper health

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and structural effects also

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Zoltan Lakatos: eliminated, for X is free.

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Zoltan Lakatos: So we have seen the distribution of the articles. Now here is the distribution of the discourse themes.

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Zoltan Lakatos: Thanks to advances in geometric data analysis, it is not possible to conduct a study of objects from very different contexts by accounting from for

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Zoltan Lakatos: group-specific configurations while still locating those configurations in a joint space. Specifically.

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Zoltan Lakatos: we use the variant of multiple correspondence analysis called multiple factor analysis, which does precisely that so we have the group specific configuration of discourse themes here

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in a joint space.

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Zoltan Lakatos: So the distribution of these core themes is very different from Jews and Muslims. This is to say. cluster analyzing the discussed frames on the joint sample, on the joint simple would be misleading. So what we did we did cluster analysis on the group, specific discourse, configurations.

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Zoltan Lakatos: And here is what to be in. this needs to further clarification. So this is how the discussed clusters look like

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Zoltan Lakatos: in the joint space. There's a modest degree of similarity. Discourses on both Jews and Muslims have a barbarism.

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Zoltan Lakatos: a barbarism, a dislocation, and a clash cluster

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Zoltan Lakatos: indicated using the same color. But even these pairs are very different.

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Zoltan Lakatos: The barbarism frame is more complex in the case of Jews

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Zoltan Lakatos: than it is in the case of Muslims it's heavily racialized for both, but in the case of Jews it has more to do with disgust, like the suggestion that they are animal-like, etc. Then there is this location. There are some common themes. Between Jews and Muslims, like Framebody, fear

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Zoltan Lakatos: societies. parasitism.

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Zoltan Lakatos: and crowding of locals, but there are also differences, like associating Jews with

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Zoltan Lakatos: usually here. which is absent from the Muslim specific dislocation, frame.

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Zoltan Lakatos: or terror in the case of Muslims, but not for Jews. Also notice that the dislocation frame here

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Zoltan Lakatos: it's more racialized regarding Muslims. The third frame with the same label is clash.

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Zoltan Lakatos: Here, too, there's a few common themes highlighted in purple. Like the idea that the out group hates us.

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Zoltan Lakatos: corrupts or culture the need for violent self-defense, and that the group should immunize itself against their own group, also a clash of civilizations, idea, and the notion that the All-group has collaborators within the in group who are being hypocritical about

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Zoltan Lakatos: the aliens and manipulate public opinion. But here, too, the clue clash. Themes have their group, specific flavors, highlighted blue, like cultural dogmatism and physical violence in coverage of Muslims, but not in coverage of Jews

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Zoltan Lakatos: or crime, is part of this frame with regard to Jews, but not with regard to Muslims, or as part of the dislocation frame, and also notice that this location with the Jews involves themes with

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Zoltan Lakatos: higher than average scores on the integration scale. Theres integration scores are lower than average for the Muslim specific dislocation frame. This is because discourses of this location regarding Jews suggest that Jews are firmly embedded in power structures. Then there are discussed frames that appear only regarding one of the groups like the exploitation frame in the coverage of Jews

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Zoltan Lakatos: at the from the coverage of Muslims. This is the idea that wealthy Jews, by their dishonest and deceptive practices, oppress the well-meaning majority. Further, there is only one frame on Jews here is not hostile, this one a general tolerance, discourse, non-hostal coverage of most limbs. Here

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Zoltan Lakatos: he's more. And he asked one of the 2 frames emphasizes a context tool that pushed to the art group like this thing and the other frame is compassion.

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Zoltan Lakatos: Emphasizing all vulnerability and calling on the in group to help the stigmatized minority. Now, why am I talking at length about this specific feature of coverage? Because I want to stress that under the Glm construct, equivalence, paradigm, these group. Specific frames are an impediment to comparison.

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Zoltan Lakatos: but not in geometric data analysis.  Because even with these group specific frames we can nonetheless answer the question.

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Zoltan Lakatos: or each of the 2 coverages is more racialized, and also others. The key is what we mean by measuring that now a side note on distance is in order.

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Zoltan Lakatos: approaches the distance standing from the general linear model. typically focus on averages, Medians and other summary indicators. Look at this illustration. First, consider these 2 ellipses here labeled H. And a, and H. They are concentric with a common centrade set. A is larger than set H. Owing to its longer. X's.

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Zoltan Lakatos: Is it reasonable to propose that the distance between set A and set H is the distance between a between the centuries or 0? Of course it's not reasonable. But in the general linear model, distance between sets is understood as distance between some summary indicator is typically cent for it. Now

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Zoltan Lakatos: look at the bottom left. Set C and T. Using them as illustration. Let's consider a measure of distance which takes set complexity into account.

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Zoltan Lakatos: And here we go

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Zoltan Lakatos: at the houses of distance, named after Felix Haldorf, one of the founders of modern topology.

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to get the house door distance

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Zoltan Lakatos: first, take the longest distance from set D to the nearest point in set d. That's the purple line. Then take the longest distance from Set D to the risk point in, set C the black line.

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Zoltan Lakatos: and the grader of these 2 distances will be the host of distance

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Zoltan Lakatos: or the purple line. To repeat the Hoister of distance is a better measure because it takes distribution or variance into account. Now, the

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Zoltan Lakatos: what we're going to measure

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Zoltan Lakatos: using the host of distance is the distance between clouds. Specifically. The clouds of the observations are the articles and the clouds of properties are the discourse themes. And we're studying all possible distances between articles and discourse frames between discos frames vice versa, etc.

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Zoltan Lakatos: To simplify, we did a multi-dimensional scaling with the host of distances between all the claws of interest.

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Zoltan Lakatos: The items on this map are dots.

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Zoltan Lakatos: but they represent clouds of discourses and clouds of articles.

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Zoltan Lakatos: and the discourse frames are connected by blue dashes. Blue blue dash lines for Jews and green dotted lines for Muslims. The item, the items labeled with italics are the newspapers and magazines

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Zoltan Lakatos: in the sample. Now, one key question is.

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Zoltan Lakatos: how coverage of Jews and coverage of Muslims differ in terms of racialization? To answer this question we created 2 separate discourse frames based on overall attitudes. One is racialized and the other is non-racialized. For Jews.

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Zoltan Lakatos: The racialised includes exploitation, clash, dislocation, and barbarism. Its cloud is labeled bold blue represented by this dot, and for Muslims racialise is dislocation.

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Zoltan Lakatos: clash and barbarism, and the cloud labeled, or the dot labeled Both Korean for Jews. The non racialized frame is the same as tolerance here and for the Muslims, non racialized is the combination of the contextuality

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Zoltan Lakatos: and the compassion frames. So coverage of Jews is much closer to over racialized discourse than it is to non racialize this course compared to the positions, whereas coverage of Muslims is at about equal distance between the racialized

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Zoltan Lakatos: and the non-racialized frames in terms of specific frames. Coverage of Muslims discloses the compassion, rest, coverage of Jews is closest to barbarism, closely followed by exploitations.

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Zoltan Lakatos: and of all the specific discourse frames closes to the origin.

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Zoltan Lakatos: of the rejection versus acceptance method, dimension, and identified in Mds are the 2 barbarism frames. Barbarism, in other words, is the default portrayal of both the Jews and Muslims. But the specifics indicate that late nineteenth century press coverage of Jews is, generally speaking, more hostile than is racist and coverage of most limbs.

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Zoltan Lakatos: So I'm not going to review all these in in instructive findings. But a couple of more are worth highlighting.

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Zoltan Lakatos: and for both Jews and Muslims the racialized subclass of coverage has to do first and foremost, with a sense of dislocation

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Zoltan Lakatos: to wrap up. I started by reviewing the stringent criteria of construct equivalence, which over the last couple of decades have become near

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Zoltan Lakatos: currencies in cross-cultural research, and underlying this issue is the research philosophy of the general linear model. The approach proposed here to deal with the issues. Of course, culture, comparability of latent constructs uses, geometric data, analysis, and the argument in its favor is not that applying glm centers construct equivalence, criteria of the leads to an impasse? It's something.

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Zoltan Lakatos: It's that their geometric methods are especially suited to make sense of the relationality of social phenomena, so comparison is not the privilege of glm related models. It is time to make comparison more geometric, which means more relational. Thank you very much.

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Zoltan Lakatos: My time's up.

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Zoltan Lakatos: I can't hear you, could you?  almost yourself?

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Okay. So I'm trying to make it to the third time right in the mind. Thank you very much indeed for such a substantial presentation. And we will. We need to go further with the third presenter and they also online. And then we will have time for questions and discussions.

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And the presenter that I want to. Okay. So now it's a search program. Can we get to the

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to the list?

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Tugce Beycan: Hi, everyone. Hi. my name is Twitter.

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Okay.

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Tugce Beycan: okay, yes, exactly to check.

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Tugce Beycan: So I can share the screen.

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Tugce Beycan: so I can to.

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Yeah, because you have another 20 min. And you started on like 1115. So 1135, 11,

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35 fish. You have time. Okay.

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Tugce Beycan: okay, guys.

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Tugce Beycan: So hi, everyone. so my name is

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Tugce Beycan: So today, I'm going to present you the work that we are carrying up with my colleague, Sergeant Marcello.

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Tugce Beycan: We are from the resource center at Saint Morris hallbacks in Paris, which is affiliated with ecolnormal superior, and the

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Tugce Beycan: and the French National Science Foundation.

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Tugce Beycan: So our city is called the Social bones, and the diversity index in the United States the relevance of the Durkheim into the approach of social attachment.

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Tugce Beycan: And so our study is also financed by a Service National Science foundation.

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Tugce Beycan: Okay, so the overview is that, I will start off the presentation by expressing the goal of this study.

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Tugce Beycan: So at the second stage, I will talk about the turtle framework. At first State. I will give information on data indicator, statistical methods. and after that I

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Tugce Beycan: parliamentary results and the most relevant observations from the results.

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Tugce Beycan: And in the end I will conclude the presentation by emphasizing the utility of this research on the X.

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Tugce Beycan: Okay. So the proposed of this study. So this study. applies a t of social attachment based on the panic work of famous French sociologist, Mildura. So the idea is to find out the the bones, the social bones that attach individuals to each other.

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Tugce Beycan: so different groups. For to society in general.

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Tugce Beycan: so, according to that we. We set the the 4 goals, as you can see. So the first of all, the creating social bone indicators because we have the Terry and we we? We do ampirical study by creating the indicators in order to operationalize the theoretical framework, to make it possible with to to have more. let's say

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Tugce Beycan: I'm pretty good results because it it is. It was a theoretical stage. Firstly, so we create still social bond indicators and find out the social attachment regimes across the United States and on Federal level.

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Tugce Beycan: Second goal is the discovering the most influential variations between the Federal States regarding social bonds, statistics.

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Tugce Beycan: Third, one is the revealing the correlations between some selected socioeconomic variables and the social bones, indices, and by Federal State cluster.

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Tugce Beycan: And the

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Tugce Beycan: for is the explaining the relationships between social bonds and the diversity index which reflects the ethical and rational diversity by Federal State cluster.

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Tugce Beycan: So we have 4 goals, and the for each call. So we have a research questions.

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Tugce Beycan: So we respond, To these 4 questions like, the first question is, what are the similar States, and how the State clusters, you will see later on. The classrooms is similar from each other in terms of social bond statistics.

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Tugce Beycan: So this question is in line with the first and the second goal.

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Tugce Beycan: The second question is, does the lineal bond become significant when this season she phone is week, which is related to second call. The chart question is, the States, with relative good socioeconomic performance are regulated by which social attachment regime, which is in line with the circle. And the 4 question is that what is the racial and ethnic diversity

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Tugce Beycan: profile of each social attachment cluster which is in line with the portfolio?

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Tugce Beycan: And then we have also the 5 question, which is the the fifth question, is to do the clusters with greater racial and ethnic diversity, or from better regarding. So I am a aspects which is line with the fourth call.

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Tugce Beycan: okay. So the theoretical framework the terror of social attachment contains 4 types of social bond

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Tugce Beycan: which refer to difference to fears of morality and normative system.

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Tugce Beycan: So first one is the linear bond

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Tugce Beycan: which is associated with domestic morality through family relationship.

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Tugce Beycan: like the participation bond which is related with

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Tugce Beycan: associative morality through participation, humanitarian organizations and donations to charities.

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Tugce Beycan: Or it is the organic participation bond which reflects occupational morality through labor market situation, and the fourth one is the citizenship, both which represents civic morality through trust and people trust in justice.

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Tugce Beycan: So the the typology we did here of social bonds and the social attachment framework which is already mentioned, actually by a program in 2

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Tugce Beycan: in and later on with the Me. Sergeant, the Christian suits are. We have short social attachment regimes across Europe. And the more recently we did international study, including

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Tugce Beycan: 34 countries. And here we are applying to the Us case.

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Tugce Beycan: So so we have the 4 social bones. And then, based on that, we are, we define 4 types of social attachment regime. The first is that families type of social attachment, second is the voluntary type of social attachment. Third, one is the organis type of social attachment, and the final one is the Universalist type of social attachment. So the first one

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Tugce Beycan: by family relationships, Bilinal bonds and domestic morality, the second one is regulated by elective participation bonds and associative morality. Third, one is regulated by organic participation, bone, pational morality, and the last one is regulated by citizenship phones and civic morality.

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Tugce Beycan: So when it comes to particular research. So we use the American data. But we have different data sources for social bond indicators, but also for social, economic indicators the the rational and ethnic diversity indicator.

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Tugce Beycan: So as you can see for the social bonds indicators. We the average 4 to 2,010 to 2,015 period. And we use the American Community survey current population survey and the United States election project 250

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Tugce Beycan: for the

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Tugce Beycan: and the for them.

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Tugce Beycan: the racial and ethnic diverse indicator. We use the as an indicator. We use the the blow index which measures the probability of 2 individuals choosing at random from the population being of different race or ethnicity, so which are comes from also the Us. Census bureau to office, and for the

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Tugce Beycan: they are different population groups. According to us, census bureau, which are white, black, Hispanic, American, Indian, and Alaskan, native Asia, native, Hawaiian, and other Pacific Icelander population groups.

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Tugce Beycan: So when it comes to indicators, these are the what you see from the screen. These are the main indicators of social bonds.

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Tugce Beycan: So the final one is the ethnic and racial diversity to the blow index, which is very famous in the case of the United States, which is already defined by the

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Tugce Beycan: Mit. Ctl. And which is also used already by the Us. Office but the Sansu's office. But this the 4 social bonds indicators, the lineal bond, 150

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Tugce Beycan: patient bonds, organic participation both on the citizenship. So we created together

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Tugce Beycan: as a team. So for the first one for delineal Bo, we want to know what are the how people are attached to their family. So for that reason we choose the 4 indicators.

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Tugce Beycan: the percentage of 2530 years that our mother or their father

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Tugce Beycan: percentage of the 25 to 30 years old, on employees, people living with our mother or their father, and the person to talk people aged at least 7 to 5 years old living with our children.

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Tugce Beycan: and the last one is the a percentage of people aged at this with 7 to 5, and living in a household composed of at this 3 individuals

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Tugce Beycan: for the elected participation. Bo, we use the percentage of people active in in the humanitarian organization and the percentage of people who donated to a charity

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Tugce Beycan: last month

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Tugce Beycan: for the organic participation. Bo, we use the percentage of jobs covered by a agreement which is adjusted by informal employment rates.

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Tugce Beycan: and for measuring the season we, we use the average results of season participation in 2,006, 2,012 and 2,016 general election in the Us.

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Tugce Beycan: So we also use some social economic indicators. You, you will see later on.

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Tugce Beycan: So we charge the head controversial forward to Juni index percentage of high school graduate or higher Median earnings in the past 12 months, maybe an income in the past 12 months, and the on up.

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Tugce Beycan: and all of this indicators come from the Us. Census bureau, and these are the 2,000 need of 2,015 American coming to survey 5 year estimates. So when it comes to statistical steps. So we create all social bones indicators, we follow the human development index technique. And the second, we process with the cluster analysis

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Tugce Beycan: and the class will indicate the most influential variations between the Federal States regarding social bonds, statistics, and the third, we computed correlations between select social economic variables and the Social bonds indices by Federal State cluster. And the last one is the we did computations of correlations between the index of diversity and the social bonds. And this is again by Federal

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Tugce Beycan: 8 class for a level.

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Tugce Beycan: Okay? So we have some preliminary results. So you can see from this the Mac. So you can see the distribution and the intensity of the each of the social bonds Index in the in the United States. So you can see that actually, the indices takes the value between 0 and one. So the 0 is the lowest value, and the one is the highest. So which means that

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Tugce Beycan: mit Ctl. And for a state having a very higher score regarding the linear bond. So the State going to take the maximum, the score of one, and the from this map you can see that in terms of color, so the highest value is represented by the darkest green, one

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Tugce Beycan: color. So, for instance, you can see for the linear. the the state of

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Tugce Beycan: California, for instance, is the most green one, so, which means that which is which has the highest value regarding the one

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Tugce Beycan: regarding the linial bond index

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Tugce Beycan: sucks. So here we have the we have the clusters.

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Tugce Beycan: So the clusters we have the 8 cluster, as you can see, because the United States is quite large. So we we we do not have 3 or 4 classes, which might be good, optimal, but 8 is also already is already good, but, as you can see, at the

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Tugce Beycan: the the the left right side of the sequence. We have the inconsistencies course, because we did all of this computation by using the statistical software for, and we use the Fpc package. And from this computation, so you can see that we have them.

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Tugce Beycan: We have the consistency quite good, cons to say, except 2 clusters, plus or 6 and cluster 8, which have the score is under 0 point 7. So which is not very good to to to interpret. when it's in constancy. It's not very good. So we are not gonna do that. So you can say, we from the first cluster, the first cluster. So we have the Connecticut, Maryland, Delaware.

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Tugce Beycan: Pennsylvania, Alaska, Ininhua Road, Iceland, Massachusetts, Michigan, for the second cluster we have Florida, Louisiana, Alabama Mrs. Sipsey, Georgia, South Carolina, North Carolina, and Virginia

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Tugce Beycan: for the tort cluster. We have New Mexico, Nevada, West Virginia, Arkansas, Oklahoma, Texas, Arizona, Tunis

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Tugce Beycan: on the fourth classroom we have New York, Hawaii, California, New Jersey for the we have Minnesota, Wisconsin, Yoba, Maine, Colorado, New York, I'm sure, and for the Seventh cluster we have Nebraska, South Dakota. The whole Council, North Dakota, and the

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Tugce Beycan: so

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Tugce Beycan: here also you can see the again. We did here. the map of the

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Tugce Beycan: ere.

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Tugce Beycan: So these are the higher values and

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Tugce Beycan: And so the darker color represents the cluster one, and the lighter color represents the class for 8. So you can see, for instance, for the first class we have the Connecticut marijuana, Delaware, etc. These are the is called actually so. These are the presence, the the darker color. So you can see the is another way of representing clusters which might be easier for

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Tugce Beycan: some kickbook

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Tugce Beycan: mit Ctl, and for interpret. So we we computed average the course of social bonds, indices for each for each cluster so, and you can see in the end the permanent social attachment regime. This is 150

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Tugce Beycan: the table. So which is the most important results at first stage. So you can see that one.

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Tugce Beycan: for instance, the first cluster which is the Connecticut, Maryland, the East coast, which is a

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Tugce Beycan: mainly by the organis and Universalist regimes. Okay? And the second one

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Tugce Beycan: I have the Florida, Louisiana. Alabama, Mrs. Zipsy, Georgia, South Carolina, North Carolina, Virginia.

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Tugce Beycan: You can see this cluster is regulated by the Universalist and a familiar list region.

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So we

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Tugce Beycan: combinations. But the the most interesting by me. First of all, the third cluster, and the third cluster is the Mexican Nevada, West Virginia, Arkansas, Oklahoma, Texas, Arizona, Genesis, which is mainly mainly regulated by the femalees region, which means in this cluster in the States. So all the regulation which, in terms of 250

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Tugce Beycan: society, and the groups

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Tugce Beycan: through family relationship. So and in opposite, for instance, you can see the fifth cluster, which is Minosota, Wisconsin, Iova, Maine, Colorado, and I'm sure it isn't more north of the

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Tugce Beycan: the the Us. Compare it to the classroom, the third class. So here you can see that the fifth classroom is mainly regulated by the Universalist regime in the Universities regime it's very important. Trust and people trust in justice. So the the people are more confident, trusts more to the state. But when we have the classrooms with the familiar, this regime, people do not very much trust to the State

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Tugce Beycan: no justice, or not very much trust in people. But instead of that, all the regulation in the society through family relationships, which means, they trust much more their family members compared to the State. So we were going to say later on, which type of ethnicity these clusters do have.

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Tugce Beycan: Okay. So

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Tugce Beycan: we have in this in this table. So you can see, we have the average scores of some social economic indicators that I mentioned before. So we have the forward toate median of earnings, genie

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Tugce Beycan: to level a high school, or higher or less on heart, less than high high school. So you can see the green colors and the yellow colors. These numbers are the the most important, the important ones. So yellow signifies relatively bad performance, and the green defines relatively good performance. Regarding the indicator

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Tugce Beycan: answer, which was mainly regulated for the familiar list regime, so you can see

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Tugce Beycan: the their

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Tugce Beycan: quite that in terms of the forward rate is high and the income level is also bad compared to other classes, and also the education level. And when you see that the classes which are much more

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Tugce Beycan: regulated by the Universalist on the organis's regime, where the poverty is less junior indexes, less a median of Ernie's higher and education level is

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Tugce Beycan: a higher.

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Tugce Beycan: So we also uploaded the diversity index in the Us. So you can see the higher number is in yellow.

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Tugce Beycan: so defines greater ethnic racial diversity, and the lower number corresponds with less ethnic racial diversity. So the index text, the value between 0 and the one

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Tugce Beycan: and the 0 appears to no diversity.

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Tugce Beycan: and the and the one is the the highest.

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Tugce Beycan: highest diversity. So.

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Tugce Beycan: for instance, when you see the yellow like the California and etc., in this days the the the diverse terms of the his funny population, black population or the Hawaiian population. Alien publishers. It is higher compared to do, and

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Tugce Beycan: the country is, significantly defined by less

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violent diversity.

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Tugce Beycan: So we did some also correlations. So you can see like, first of all, between diver and the lennial bond in the use States. So there's statistically significant positive correlations in terms of higher diversity, higher linear bonds. So diversity index, and the linear bonds are positively correlated.

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Tugce Beycan: For, in other words, we can say that in the States where there is more diversity. The families regime

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Tugce Beycan: one amongst the 4 other social attachment regime, because you will see later on. We have also results that the communities, like Asian communities or black population or communities with the Hispanic population, they do much more trust on their.

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Tugce Beycan: So the family relationship and not very much to the state. So that's why we have this positive correlation. So we have also correlation between diverse index and the elective participation bonds. So elective participation bond is mainly defined by the participation to humanitarian organizations or the donations. So there is such a sickness, significant negative correlation between these 2 indicators.

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Tugce Beycan: But the correlation is not very much high compared to the first one. So in the States, where diverse is higher participation in humanitarian organization or donations to charities is few and is due to a strong family relationship or to labor market protection system which defines the root of process of how to come with 150

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Tugce Beycan: vulnerability forward, or some difficult periods, and the, for instance, in the cluster one which is also mostly regulated by familiarist and the organis regime, which was the New York Hawaii, California, and the New Jersey. So you can see in this script that there is significant negative.

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Tugce Beycan: It's an elective participation bond and the organic participation bond.

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Tugce Beycan: So we have also a correlation between diversity index and the citizenship phones. So here we have the statistically significant negative correlations between 2. So in the States, where diverse is high trust and justice and the trust in people is fuel, and which means that minority groups or people with groups with immigration background trust less to the legal system or to people in general compared to the rest of the population.

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Tugce Beycan: So we have here average scores of ethnicity and

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Tugce Beycan: indicators for each class or so. We do not interpret 6 on the 8 cluster, but one is, you see the other?

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Tugce Beycan: Let's see that for us, as a diverse index, very low in the class here. 5 and the 7, so where you can see the rate of Hispanic. Why Hispanic, black, or Indian Asian population is few as well, and the score differences between black population and white and his funny population is the highest level. So in this size, particularly, the regulation is not through the family relationships, and it's taken by the organis and the citizenship phones.

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Tugce Beycan: So and then we can conclude so in as a conclusion. So we can say that or results at the stage of this this study show that it will be important to implement a public policy

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Tugce Beycan: mit Ctl and increasing trust in justice and trust in people, but also more labor protection system in the States, on the or classrooms, where the familiarities, the regime appears as the most permanent regime, and this tastes and the classrooms are less diverse compared to others. 2.

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Tugce Beycan: So, in other words.

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Tugce Beycan: for better social inclusion. So the perception of minority to groups in terms of race ethnicity, people with immigration background towards cross injustice, trust and people participation into humanitarian organization and community activities. It can be examined in detail.

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Tugce Beycan: So we here aimed at solving some, how we can, is or is all be useful for reducing some social, economic dispatches between States and putting in evidence some characteristics of social attachment, regimes of the States with high ethnic diversity, with high black population

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Tugce Beycan: mit Ctl. And and we high binary to a grip. So and the next step we're going to apply the variance on the All States to explain in in detail significant differences between the social attachment clusters 150

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Tugce Beycan: so and so in that. So thank you so much. And this, but also the special thanks to the research committee. and the organizers of this.

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So we we we will like to hear, as your suggestions remarks, and the comments for this study. So thank you so much. Absolutely. Thank you, Dr. Beckham. Thank you very much indeed. So we're successfully very successful in terms of time. We have plenty of room for questions, discussions and comments. And

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really! there's fascinating papers that were done this morning, and I believe the presenters they have the right to ask questions each other. They have.

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If do you have questions, talks, or or Sultan.

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to each other.

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Zoltan Lakatos: I have a question to.

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Zoltan Lakatos: Can you hear me? Okay.

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sure, definitely. Yeah. Yeah. Okay. Let me try to.

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Zoltan Lakatos:  in the most accessible way possible. So I am intrigued by this statistical, significant

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Zoltan Lakatos: correlation, bit fan

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Zoltan Lakatos: the diversity index, and the

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Zoltan Lakatos: strongerlinial bonds?

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Zoltan Lakatos: Is it reasonable? Question? Is it reasonable question to ask.

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Zoltan Lakatos: how this correlation looks like for the the specific

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Zoltan Lakatos: ethnic racial groups separately, you know they they the same correlation for, say, whites Hispanics, blacks, Asian Americans, and so on. Did you get to study this suspect as well?

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Zoltan Lakatos: You are actually. And you say that the diverse index on the which fold because I couldn't hear.

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Tugce Beycan: Is it reasonable

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Zoltan Lakatos: to raise

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Zoltan Lakatos: the issue of how the same correlation, how they, this relationship, looks like for separate Ethn and the racial groups like, yeah, for why? It's certainly for Hispanics. Because, you know, it might be interesting.

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Tugce Beycan: Yeah. So it's it's very good point. So So at the first stage we look at the like overall level

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Tugce Beycan: relation. So what we we can do is that for the next steps? So we have already the clusters. So we already started to look at into the each clusters, because because the correlations So when we look at the in each cluster. So then we can look at the

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Tugce Beycan: like to by population groups like you. What is it? The? So that's why we're gonna apply the variance test to see the differences between groups. So what we can do is that we have the group of Hispanic population, black and white, etc. So we have the 5 groups. So we're going to say, if the correlation between the lineal phones

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Tugce Beycan: mit Ctl and and the this the index is the we can the linear bond score. Sorry the lynnial bond score is just a significant on MOX this 5 groups. So it's important. That's why we're going to do the variance test, one

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Tugce Beycan: to see the intro and intra

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for a.

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Tugce Beycan: And so it's very important. So and then I think we, this can be applied also for each phone

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Tugce Beycan: for not the world interest regime, because for one, we didn't have the significant results. But this can be applied for lennial bone citizenship phones and the for the organic participation of first

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Tugce Beycan: to yes.

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Zoltan Lakatos: thanks. So it's in the next step, this exactly for the variance. Do you think it? Is it possible that also white

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Zoltan Lakatos: living in States with a high of diversity index

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Zoltan Lakatos: that also whites have stronger linear bonds.

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Tugce Beycan: No, actually, the results have shown that we we we, we found out to the classes with high population of

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Tugce Beycan: With the high population of

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Tugce Beycan: these are the lord of the country, because, as you can see, diversity is much more relevant when we go to the subtle country so, and the North is especially when we are going to like close to the Canada and etcetera, what population is very high. Our worst index is very few. And then we don't have. We have very much the family relationships.

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Tugce Beycan: So it's because

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Tugce Beycan: actually, this, the results at some point are proves that the the white people, they

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Tugce Beycan: more to the state. compare it to the other other racial and the ethnic groups.

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Okay.

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thank you. Thanks.

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before the audience here in Australia and online are working on their questions. I have a question to presenters.

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So the first to to catch it on.

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Why, Robert Merton, why structural functionalism?

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Why, why did you choose? That's

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thing. And then, just to prepare to the users online, both of you guys.

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 what do you think.

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Jabiti, or any language model can do your job?

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Can instruments of artificial intelligence do what you've done

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in terms of doing this statistic also a statistical research or data. Whatever you did. Is it possible for instruments of artificial intelligence to substitute your teams and your ideas.

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Yeah.

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David, thanks to your question, yes, actually, so, I really expected that the question because regarding the structure approach like a functionality. And everyone so normally imagine. Like, personally, I'm very kind of structured. Pyla made the model.

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Yeah, and and which, a course for a kind of more kind of objective, quite universally stick various structures which I have been criticized for comparative analysis in my research. That's why, I try to figure out this issue by introducing more kind of integrative approach like a ethnic methodological approach to compare each different

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kind of structure, no stroke stacks or a kind of framework of needing the sense for internally comparison. in the analysis of a structural analysis, because, Marathon's robot. Madden's functional analysis is quite unique, because Ritchie has a sharp contrast.

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regarding to Parson, you more kind of very objective approach like his kind of analysis or kind of several types of function by each kind of communities groups. So it should be very kind of insightful. Even. I try to conduct such kind of the international confirmative, and or is, given each national society as a single cross.

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the kind of cultural social community. This kind of a mythological approach is actually taken from one Japanese famous sociologist publication. In the recent publication. In that book he tries to figure out how his integrated device.

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the Marathon's function approach to model in the more kind of ethn mythological approach in an emphasis with kind of referential program, our referential sets of each individual groups

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to integrate more to kind of to can this or so called a micron conflicts. as it happens in sociological debates in the theory and methodology.

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I hope? my kind of answer, yeah, yeah, yeah. Thanks. Thank you. Did. Yeah, definitely. Yeah. Jordan taxi, you know, instruments of it. Artificial intelligence and future research is ideology in your research?

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Zoltan Lakatos: I

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Zoltan Lakatos: okay, thank you. So interesting question, intriguing question.

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So the question looked like something like whether AI going to be a substitute for

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Zoltan Lakatos: a much or most of the statistical work

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Zoltan Lakatos: that the 2 of us are involved with or in.

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Zoltan Lakatos: I mean, not really. I'm not very familiar with the a potential of

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Zoltan Lakatos: statistic, the the potential of AI tools in

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Zoltan Lakatos: sociological studies. But you know, even preparing the data or data cleaning the data. Cleaning phase requires

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Zoltan Lakatos: an awful lot of work in terms of

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Zoltan Lakatos: in interpretation. Literally, literally, I, we have to translate

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Zoltan Lakatos: late nineteenth century Archeric. Hungarian to, you know, contemporary Hungarian. So these 2

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Zoltan Lakatos:  these, these these 2 body bodies of text. or separated by one.

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Zoltan Lakatos: 12020 plus years. So this is kind of, you know. A late nineteenth nineteenth century Hungarian press is kind of yes, I can understand, but on

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Zoltan Lakatos: a lot of crucial points the meaning is not by no means obvious, not evident.

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Zoltan Lakatos: and I fail to see how, at the current state.

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Zoltan Lakatos: AI

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Zoltan Lakatos: might help with this with translation, make excess

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Zoltan Lakatos: of of of the

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Zoltan Lakatos: the fine print in in the you know this this granular aspect of discourse analysis. So for my perspective.

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Zoltan Lakatos: it's it's it's a no, but I I'm kind of opened.

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Well, I appreciate that. That's very interesting. Yeah, thanks thanks toxic, please.

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Tugce Beycan: 10 years. yes, oh, yeah. So well, I mean, I'm so just. But my background is statistics. So I'm statistician, really. So I think, as a sensation we already use. I think, a lot of We are already like, you know, with the R in the State, I said. Try, and especially are we have a lot of packages which help us to do some very complicated computational statistics. But I think when it comes to computational social

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Tugce Beycan: sciences like quantitative theology, and then, or socio-economic studies. I think the most important is the first of all the ideal. So what we want to do as a research. And then so I think we did, you know, put the question, and then we think about it. And there's special territory framework. But

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Tugce Beycan: but I think it's possible to do some new packages or the programs that if they have very good algorithms, maybe. But you have to. Also, I think, construct this algorithms based on some like terror is like sociological Terry. I think it's it's quite so difficult. I think we need a

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Tugce Beycan: cannot be possible. I think tomorrow or later on, I think maybe 20 years is possible. But because we need a very strong algorithms for that. And I think,

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Tugce Beycan: as a human being. We are thinking we do interpretations. I think we can all obtain, maybe some objective in interpretations that much more, let's say the package in the interpretations. But when it comes to more subjective indicators, and which involves the you know the personal

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Tugce Beycan: not perception. But let's say we, the way that we look at the art of the state, and How we interpret it! So! I think very personal. I don't think that to say to

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Tugce Beycan: artificial intelligence can do that. Such a very and, let's say, rich interpretation. But I think it's possible to do sort of some packages. I think the the the computational scientists. They do already. Good job.

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Tugce Beycan: But I don't think it's enough at this stage.

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Okay, thanks. Thanks. So looks like both snores. Because you know, this is about our future, I mean the future of sociologists. And when we are talking about the crisis in sociology, what what to teach, how to teach, in what direction. So, on the one hand, we have structural functionalism. And Robert Merton, on the other hand, we we have really, really sophisticated analysis that it was presented today. And but interpretation. So it still belongs to those who call themselves human beings, you know.

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Okay? Other questions. and yeah, for me, a some. Please.

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Okay.

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okay.

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okay, technology. You know. So it's

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yeah.

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I have a question to Professor Kamanov. You mentioned about the Meta analysis. You propose the analysis for comparative national surveillance. And you also mentioned about the

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I wonder what? What is your methodology about this Meta analysis? Do you mean a kind of a content analysis.

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So what kind of methodology do you grant to on this meta analysis of?

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Yeah, thanks to your question, that's what I missed to detail in my presentation. So meta-analysis means in my presentation in the analysis of the sets of question layers and the purpose of the survey itself, rather than analyzing the outcome or a data research drown from the Sava itself.

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Normally, people do some kind of even statistic, well corridated research about to the result of all this a survey, but rather, I've been interesting how to make a comparative research between the kind of research project itself by comparatively examining sets of questions or a kind of ways of anoris. This is what I mean in that town. Thank you.

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Okay, thanks.

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Any other questions. Yeah, yeah. I have a question for which one so could you

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go to your slides again?

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Zoltan Lakatos: Yes, Let me try from the start. And all, yeah, yeah, yeah, you get there.

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So now you can see my slides. Okay, Yup, I see them.

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01:20:39.880 --> 01:20:55.450
And could you please speak of the closer to the mic, because, yeah, yeah, much better. So which one you are interested in.

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let's say

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Oh, there! I think. But that one, I think. Yes, so some of them. Some of them are of the letters are in different colors. What do those colors indicate?

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Zoltan Lakatos: it's very simple. The colors indicate a higher contribution to the inertia of the

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Zoltan Lakatos: access in question.

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Zoltan Lakatos: 0 speaking.

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Zoltan Lakatos: and which colors indicate high contributions. Especially high contributions. Here, for for example, to the horizontal axis, red

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rat. and black, or lower

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Zoltan Lakatos: the black black a higher contribution to the other axes.

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and then the the ones that are in

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Zoltan Lakatos: indicated in rectangles? Are they simply the ones that are at the extremes. I just extracted them for ease of interpretation. You know, I mean, for lack of time, I need to focus on the most

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Zoltan Lakatos: conspicuous are discourse themes in order to make sense of the

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Zoltan Lakatos: dimensions. Okay, so this is a bit the chair picking. But you know there's no more to this than than just, you know ease of interpretation. And was it purely on statistical grounds, or was there some judgment involved?

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Zoltan Lakatos: Of course that is the good runs, because you know these on the horizontal axis, you know, up a this is a very

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Zoltan Lakatos: Where is the the the coefficient, or or the coordinate on the horizontal scale for crowding out locals. This is this is a racialized. This is, you know, part. This is a significant theme in real life, racialized discourse. It has a very high contribution, and it's also

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Zoltan Lakatos: it also comes out, appears in its respective coordinate. So it's not just, you know, my out of thinner.

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Zoltan Lakatos: It's that sort of a statistical background.

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Oh, but it's sort of a mix of judgment and statistics.

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Zoltan Lakatos: Yeah, it's it's a mix, I mean I I I can go as far as saying that these are my favorite ones. But you know also we have other significant contributions as well like

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Zoltan Lakatos:  For example, here, here I have. Immigration must be curtailed. I did not Highlight it in my talk, but it nonetheless has a significant contribution impact

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Zoltan Lakatos: on this horizontal axis, which is the racialized versus relational.

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Zoltan Lakatos: this course.

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01:24:12.290 --> 01:24:13.780
Okay, thanks.

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Zoltan Lakatos: Yep.

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01:24:14.850 --> 01:24:18.639
thank you, David. Yeah, thank you, David. And so

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any other interventions, comments, please. If you come to the Parliament

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this

440
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good morning. I would like to address this question to took save by. By.

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So you use the theory of Durkheim on social band or social attachment.

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I remember Durkheim use it

443
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in relation to religion and morality. Is it also possible to make a comparative sociology with regard to that. Those variables like religion and

444
01:25:05.120 --> 01:25:07.389
and morality in the Us.

445
01:25:09.610 --> 01:25:11.210
Good one. Yeah.

446
01:25:13.840 --> 01:25:24.379
Tugce Beycan: thank you so much for the question. Yeah. actually in his the first of all. Say he did some the beginning of, I think, in the theoretically do coming started by

447
01:25:24.460 --> 01:25:30.889
Tugce Beycan: with the suicide, and then the religion. But after that he didn't very much

448
01:25:31.060 --> 01:25:52.680
Tugce Beycan: the roll of the indicators or the he didn't go very much into further to the the way that the people were attached to society. So that's why, actually, which sergeant and the colleagues, we, we develop these indicators. So when it comes to the religion. So while I think we have to look at the National Survey.

449
01:25:52.700 --> 01:26:04.810
Tugce Beycan: if we have this we don't have this dimension religion dimension, because we want to. Religion might be how we can implement this with the

450
01:26:05.550 --> 01:26:31.320
Tugce Beycan: it. It might be used, I think, as a decomposition analysis, when it comes to. You know, we have some social economic variables. This religion cannot be used for the main, for social bonds indicators, but this can be used for checking the correlation or the relationship with this, the main social bones and the the the and the religion and the we can maybe look at the some States with

451
01:26:31.550 --> 01:26:48.959
Tugce Beycan: when they have strong religion. If they are more volunteers, regime, or with less religion, if they are much more citizenship, they are more Universalist regime. Definitely, it's a it's a good point. But we need to have an indicator

452
01:26:48.980 --> 01:26:57.409
Tugce Beycan: which gonna we, we need to ask you people which religion they do have, and I think we can find it in the in the census, definitely.

453
01:26:57.690 --> 01:26:58.350
Tugce Beycan: So

454
01:26:58.980 --> 01:27:01.859
Tugce Beycan: thank you very much for the for. Yes.

455
01:27:02.020 --> 01:27:04.810
okay, thanks. Thank you.

456
01:27:06.950 --> 01:27:08.920
Other questions, comments.

457
01:27:11.610 --> 01:27:13.170
Tugce Beycan: I have a.

458
01:27:13.290 --> 01:27:36.220
Tugce Beycan: I have question, Yeah, please, please, please, please, yeah, to. I'm luck. As to Zoltan, so I think it was very interesting, for in this to all, just from methodological point of view. So you did the multiple correspondent analysis of categories. And I think, especially you use you implemented, you developed a specific method for better estimation with the.

459
01:27:36.220 --> 01:27:48.829
Tugce Beycan: with less variance if I understood correctly. So I just wanted to know. So by doing this analysis. So you want to obtain the profiles of the Jewish and the Muslim. migration

460
01:27:48.830 --> 01:27:58.760
Tugce Beycan: migrants in a Hong Kong press, or what is the difference compared to discriminate analysis. For instance, the type of output that we can obtain

461
01:27:58.760 --> 01:28:20.860
Tugce Beycan: by doing this because we have discrimin analysis that we can see the difference. So you use the multiple correspondence analysis. So we obtain the profiles. Let's say so different variables. And you look at the proximity of this variables, and to see the profile of the Muslims and the and the Jewish

462
01:28:20.990 --> 01:28:27.039
Tugce Beycan: migrants. So how you can say the major differences between these 2 methods

463
01:28:27.310 --> 01:28:36.330
Tugce Beycan: so like when it comes to this study. So why you didn't use, for instance, the discriminant analysis. But you opt for the multiple correspondence.

464
01:28:37.190 --> 01:28:41.170
Zoltan Lakatos: So just a clarification is in order.

465
01:28:41.270 --> 01:28:43.559
Zoltan Lakatos: What we are studying

466
01:28:43.700 --> 01:29:08.660
Zoltan Lakatos: is not the properties of the migrants. So on the one in Jewish, late nineteenth century Jewish migrants, from the Russian Empire. And, on the other hand, the mid 2,010 migration views involving mostly Muslims. It's coverage. So it's press coverage. Okay? So they? What what we're studying is is, is press coverage all the.

467
01:29:08.980 --> 01:29:18.389
Zoltan Lakatos: And so the the the different. The first question, rather, why, we're not using the document. Analysis.

468
01:29:18.950 --> 01:29:26.610
Zoltan Lakatos: well. yeah, this is a very, very, very good question.

469
01:29:26.640 --> 01:29:37.300
Zoltan Lakatos: Let me just add to specify this subclass of multiple correspondence analysis, even further

470
01:29:37.620 --> 01:29:47.980
Zoltan Lakatos: exact variant is called multiple factor analysis, and it's executable to using

471
01:29:48.440 --> 01:29:49.710
Zoltan Lakatos: a

472
01:29:50.630 --> 01:30:01.670
Zoltan Lakatos: an r package called facto myacomorphectomine R. Factor, mine R. And is developed by a French team.

473
01:30:01.890 --> 01:30:08.480
Zoltan Lakatos:  so from your country, can I? Can. I call France also your country? Because you are

474
01:30:08.510 --> 01:30:24.580
Zoltan Lakatos: your friends? yeah, yeah. Yeah. Okay, so it's it's it's developed by a team at the University of, I guess, Bordeaux factor, my R. So again, a a package in R

475
01:30:24.660 --> 01:30:26.959
Zoltan Lakatos: and the the

476
01:30:28.020 --> 01:30:29.570
Zoltan Lakatos: deep

477
01:30:30.170 --> 01:30:39.810
Zoltan Lakatos: one of the Bridge research interests is to locate these group stiff-specific discourses in a joint space.

478
01:30:39.980 --> 01:30:44.469
Zoltan Lakatos: The joint space is key here in terms of thinking.

479
01:30:44.930 --> 01:30:50.120
Zoltan Lakatos: and I see the interest in doing a

480
01:30:50.410 --> 01:30:55.390
Zoltan Lakatos: discriminatory disconnect and analysis of sorts. But

481
01:30:55.440 --> 01:30:59.770
Zoltan Lakatos:  Unless you tell me otherwise.

482
01:31:00.250 --> 01:31:07.140
Zoltan Lakatos: I don't see its benefit in terms of locating this group. Specific discourse frames

483
01:31:07.230 --> 01:31:12.329
Zoltan Lakatos: the joint space. Because that's key to measure

484
01:31:12.430 --> 01:31:36.410
Zoltan Lakatos: the distance, the non-linear distance between this, their risk group specific discuss frames on the one hand concerning juice, and on the other, concerning most limbs. These discuss frames in a joint space. And to do that, we need this specific version of geometric data analysis. So multiple correspondence analysis.

485
01:31:39.040 --> 01:31:59.880
Thank you. I I I don't have anything against there. There's some and disconnect analysis. Okay, so that's good. And then just a further point. I I I I've been toying with discrimin and the analysis within the scope of this study, in order to

486
01:32:00.000 --> 01:32:13.800
Zoltan Lakatos: have a better better understanding of the specific discourse clusters using additional variables for for the purpose of description. Okay.

487
01:32:14.000 --> 01:32:26.580
yeah, thank you. Thanks, Jordan. And yeah, science. It's not really gazed. And something that divides people. But it's about cooperation, but not competition science. And it's about

488
01:32:26.760 --> 01:32:28.970
for something. Right? Thank you.

489
01:32:29.050 --> 01:32:34.759
Not being against other methods. Right? Yeah, David.

490
01:32:34.790 --> 01:32:38.970
please, you want it? Yeah, if you go take the mic.

491
01:32:40.780 --> 01:32:43.540
This is for to tray.

492
01:32:44.680 --> 01:32:53.810
I was thinking in your talk of Robert Putnam's well-known ranking of states by what he called social capital.

493
01:32:53.950 --> 01:33:02.289
Did you compare your clusters? in terms of their social capital, according to Putnam's rankings?

494
01:33:06.440 --> 01:33:29.020
Tugce Beycan: yeah, thank you so much, David, for questions. So we we start with. We thought about how we can use the social capital. So we look at the at the time. I remember the the world value survey, for instance, to to, to, to to know if we can implement it. But it was finally we decided more to look at, the, to choose the indicators of the donations.

495
01:33:29.020 --> 01:33:43.909
Tugce Beycan: and to to charities, and to and for the, the, the bond of the the, the, the, the elected participation. One, I think you'd ask this question. Maybe social capital can be can be useful for this phones.

496
01:33:44.060 --> 01:34:10.850
Tugce Beycan: But I think it it might be also useful to see the how the community actually help each other. But it. And then it comes difficult, because the I think the challenge that we had when we did this this analysis. We don't have very much indicators. Also, because one want to. When we want to use the when we want to do comparative analysis by using the same indicators, the same framework.

497
01:34:10.850 --> 01:34:21.450
Tugce Beycan: and for different countries, even in the world, and it becomes especially, very, very difficult. But it might be it might be good to look at again. The World value survey, maybe 150

498
01:34:21.490 --> 01:34:27.810
Tugce Beycan: for better. captain, social capital. I was living between. Yeah.

499
01:34:27.960 --> 01:34:53.010
I wasn't thinking of really incorporating it in your analysis, but simply saying, Well, now, you have your classification. simply look at Putnam's ratings and compute the average for your different clusters, just because it seems like the ideas you're investigating are closely related. And you could even say you're

500
01:34:53.050 --> 01:35:18.330
sort of create a multi-dimensional version of social capital that's differentiated along several lines rather than just one single ranking. As he did so, I think quite a few people would have similar questions, right? Yeah, yeah, yeah, me, I, I was, yeah, yeah, okay, thanks for this question. And thanks for clarification. Actually, as well, yeah.

501
01:35:19.220 --> 01:35:27.669
okay. So we still have time for people in the audience here to comment, to say.

502
01:35:28.230 --> 01:35:40.259
 to ask Otherwise I would. I would ask presenters to have 1 min to finalize. their thoughts.

503
01:35:40.740 --> 01:35:50.970
And like we did. Takasha, son Do you have like one minutes for for final words, please

504
01:35:53.240 --> 01:36:11.360
alright, thanks to other, to present us for very inside representation of which we are really going to be ready to to think about my own methodology, methodological challenge. in my future. And actually, my presentation is to work in progress.

505
01:36:11.360 --> 01:36:39.550
And I also have to justify why I choose, for example, Australia, austerity and survey in comparing to Japanese subway something like that. But, thanks to you, a very kind of warm kind, and the Sha artistic comments from the audiences. I, we we want a lot, and it really encourages me to keep working with that challenge in the future. Thank you very much. Appreciate. Thanks, thanks you. It's also in place.

506
01:36:39.750 --> 01:36:54.280
Zoltan Lakatos: So thank you very much for the opportunity to present our work at this prestigious conference. let me just add 1 5 of thought concerning my research. I was very surprised.

507
01:36:54.490 --> 01:36:58.850
Zoltan Lakatos:  by finding that

508
01:36:59.010 --> 01:37:03.909
Zoltan Lakatos: the late Nineteenth Century Press discourse on Jews.

509
01:37:04.240 --> 01:37:21.729
Zoltan Lakatos: What is, is, in fact, much more racist than what we currently have in Europe. Speaking of Muslim migrants, that was not an expectation, I had, in fact, I was expecting the current coverage of most of them. Also in my country. They Hungary

510
01:37:22.160 --> 01:37:28.609
Zoltan Lakatos: to be more racist, but it's the opposite.

511
01:37:28.690 --> 01:37:43.690
Zoltan Lakatos:  it's it's difficult to imagine that such a finding would come out using the traditional methods rooted in the general linear model. And finally, the question, What's the weather like

512
01:37:43.750 --> 01:37:47.840
Zoltan Lakatos: is in Melbourne. Is it called?

513
01:37:48.969 --> 01:38:00.119
Okay, yeah, it's winter. So, but it's pretty nice. Yeah, I I to

514
01:38:00.290 --> 01:38:29.209
Tugce Beycan: So so so thank you so much for for the for the Conference, and especially to Research Committee 20. And the David, and do all the organizes of this of this session, and especially for making possible to to participate with with Zoom. So Australia was a little bit far away from from Paris. It was quite difficult to us, for come to there, but maybe for the next time, and also thank you so much for the very

515
01:38:29.209 --> 01:38:38.340
Tugce Beycan: valuable questions that we receive. So we're going to look at these questions for our research. with the team. So thank you so much.

516
01:38:38.440 --> 01:38:52.729
All right, I appreciate. Thank you. The real thanks to the presenters. But I definitely want to join and thank David Wiklim, organizer.

517
01:38:52.730 --> 01:39:20.919
the Rc. 20 Compared to I was saying that it was good in the session belongs to him, and everything was wrong belongs to me as I. I share the session I was, and I'd say, control this, I want to send the presenter to Keshe song

518
01:39:21.000 --> 01:39:38.789
and to the volunteers. Special thanks go to the volunteers. They gave us an opportunity to organize online and a face to face. And the audience, the audience, the questions, and the warm atmosphere for the presenters.

519
01:39:39.330 --> 01:39:58.000
Thank you very much indeed. We are still human beings. And as the presenters told us, AI, it's it's it's we, we. We are still alive, and we still continue to be. Hopefully. Thanks. Goodbye.