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second, yeah. So it's about time. So I would like to start this session. This is the Rc. 28 session on.

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Let's see if I can read it right. Stratification and inequality in education, the role of context.

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And there are 2 organizers who are online whom you cannot see now. But And then I'm Hiroshi Sheid. I'm the chair in the session.

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the first thing I would like to do is to ask everyone to read this acknowledgment of the country. I'll just wait for like 15 s. I'm not going to read it out, but I I'm sure everyone will read it very carefully.

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Well, thank you. And then can you put the program in

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just a second.

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Great.

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Thank you. We have an excellent technical support person.

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She hasn't been working since 8, 30, or 80'clock in the morning until the very end. We really appreciate her support. She's a volunteer.

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the program, as you can see, there are 4 presentations. And we go in this order. And actually, there are 2 organizers who are online. And

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would you like to explain the how you want to proceed? Just to make sure that my my understanding is that the first presentation followed by Q. And A for each presentation. Andre ballet or Hannah, would you like to explain the the procedure in the session?

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Hanna Ayalon: No, it it's okay.

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okay, okay, then, we'll start with the first presentation by Google, socioeconomic and genomic roots of verbal ability. Please.

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I like to it. First of my appreciation for the organizers that that makes this session.

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and and to have this opportunity to present my work.

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And so the title is socioeconomic and genomic rules of verbal ability

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from current evidence.

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and I've 2 authored co-authors. Munro Lin at National Taiwan University on Kathy Harrison

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at you and see Chapel hill.

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So I just

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 to to the next page

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up.

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yeah, yeah, I think

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page down page that okay

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and cognitive ability is one of the best and predictors of life outcomes

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such as school performance, education, attainment, occupation, income, wealth, and health.

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and

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until very recently, cognizability and related achievements. They are very much related, highly correlated, almost universally used in elementary and secondary schools, as well as in

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as well as as well as for admissions in college and graduate school and professional schools. But in recent years this trend has

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in reverse to

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no, because the pandemic. But but again, this is very predictive, and

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and the long standing view that considers cognitability

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often as a genetic trade, the sociology don't want to touch it, because a genetic trade and the genetics behavior genetics, you know, really just assume it's a genetic tree.

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and they often claim that 80% of you know, intelligence is inheritable.

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So there's some that controversy there. I'm not going through this. the bottom of this page

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and this evidence

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heritability from twin studies that shows that 20% to 80%. But oftentimes they say it's 80%.

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And recently, where the molecular genetics advances molecular genetics.

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and there's a genome-wide assumptions and study large-scale studies, a molecular genetic base of the cognitability.

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And

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so from so the and the the behavior genetics is even claiming more and one example, Robert Kleman, and in the famous interview the BBC, hard work.

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2,019. It's a, it's a fairly lengthy interview and also hard work. It's very influential interview.

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He was. Basically, it's it's online. And if you look at it, it's basically saying that. And social environment means nothing.

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So individuals and they can be randomly assigned into different school. Different families eventually would end up about the same and very, very strongly burned strongly.

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He's still the same saying the same thing, you know similar things now today.

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So what do sociologists say? Not much. Actually, as I mentioned the sociology, I look at the literature. Sociologists tend to even the Wisconsin

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stratification. Socialists tend to stay away from IQ. And they're not sure that's a genetic trade. Or now.

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yeah.

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So with the just quit very quick. And with the recent advances in molecular genetics with. It's just saliva. You can see that you can just gadge the lever from your mouth.

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You can get from, you know, each of human style.

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The nucleus has to be all the secrets of the DNA that we can. You know we can, we need. And we could easily.

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So this is like 6 persons and 6 person. DNA bursts more sections. You could that. But each person have DNA sequence has a 3 billion.

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There's a huge amount of like 40 42 volumes of a dictionary. This kind of a letters

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so now

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can easily be measured, and and using to to

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to be carried out with the in statistical knowledge to link with lots of human trace, first with the disease, then with the

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and with

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like education, attainment, and and IQ.

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So so the first would be. So this is so-called the genome-wide Association study basically got all the genetic variables throughout the human genome. They try to correlate with the each human trade.

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And so this is a for human height, not surprising, right? Not surprising. But this is for educational cabin. At first I I did not even expect this could be successful. Education attainment is so complex, but but but it turns out to be very, very successful and very highly predictive lots of things. So this is the G out with the 1 million and individuals.

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And this is a for and with 250,000 individuals, they they do the 0 with the cognitive ability.

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And so the objective here

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an objective to investigate laurel, the contribution of human genome and social environment to a cognitive Bailey. What is you know? How much is this? How much. how much environment, how much it's a and human genome

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only among the Europeans and Hispanic Europeans.

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And we're using the data from my health and health. We use the verbal ability which is highly correlated with the intelligent test.

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and

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it's twice measured

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the social environment. We use as much as we could, and we could get from at health a large number for Imamanto and predictors.

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Okay.

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so what is.

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You see.

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it's just time. I just

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so the the genome measures essentially, and they use. They use all the signals.

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the significant and all non-significant variable that can predict.

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and education predicts cognizability. It just construct a composite score that's that's like a single. You can treat it as a single variable to include in the regression analysis

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and the modeling strategies. The first one would be just modeled, like sociologists have been doing using ses or the Ss, and you know, or parental education, parental occupation, parental

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income, etc., etc. And then the second model used the genomic murder. and the third one we use both.

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And then that we, we also carried out the additional analyst for team environment interactions.

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So this I don't have time to explain this. So the basic idea is actually, we have only measured for individual genomic Mega. But it's not. but

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but this complicated picture, if you look at the if you think about the parental environmental influence, not really 100% environmental, but parents influenced also their

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the

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and the recording hasn't started yet. So your virtual participants will be missing out on all your amazing information there. Currently.

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Sorry, everyone. I'm just going to restart this zoom. So I'll be back in if you did

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sorry team just working out some funnel

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tech issues.

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Okay, as you were sorry about that, you can throw that all back online.

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Thank you.

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I can go to that graph. I think this graph is I do not have enough time, but still important.

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So, and we have a individual self genomic measure. We do not have parental in the matter. But what what is important here is the parental environmental influence, not entirely environmental, because the parents, influenced by their genome.

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but because the parental genome and individual genome is correlated 50% right from mom, 50% from death. We could capture some of the

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and parental influence which is parental, genomic. So again, this is very complex. We thought this through very carefully.

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and some of the results here. I just want to describe them verbally.

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And again, the first model traditional. So sociological model. And that's as expected, lots of apparent income. occupational education, highly predictive of and verbal ability.

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The R-square is at 20%. You can see it's 0 point 1 9 9. But you know it matters. And

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the R-square. We put also highly predictive of cognitability. And the r squared is 0 point 12% 12.6%.

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And but much of it actually is a popular stratification. You know, I mean, this is technical, not really genomic. So we need to. You know, I I will.

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if I in the final model that we adjusted one another.

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And so

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then here we combine the genomic influence from the environmental influence in the same model. Predict, verbal ability. And the R-square is 0 point 2 1 9. And the genomic fact is reduced by 20% because the the parent environmental influence correlates with the self- individual

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genomic influence. Right, as I said, explained earlier. So this reduction there the ses also reduced because some of the Icf effects is

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it's correlated. It's a very environmental. It's genomic call it, with the individuals, children's genomic and

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origin.

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And then we

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so here in the you can see that we use the we use the at health for mobility to measure twice younger ages, and then 6 years later, second time. So we we include the first time in the in the model to predict the second times of verbal, including everything else, that genomic influence Ics influence.

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And of course there are scores very high 40%. But because you have the same error to predict the same measure, but we can still see something what's going on about them.

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But even with a strong control, with the first

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verb ability to predict the second measures for mobility.

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And there's some of the environmental influence still there, like self-education, length of education and school, they are very highly highly influential.

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and

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I think we also did Geneva interaction, so that you have genes. But it depends on the environment. If you in a good environment, you tend to do better than expected relative to a view from a

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worse environment.

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Yeah, eventually, I think, let me see. how much time do I have.

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So I think a summary there is covered. And

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but this traditional ses model predicts verbal ability with an R squares of 20%, and

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but both a genomic measure and ses measure together, predict the variability with r squared of a 12.6%

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and

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an incremental incremental squares of a genomic measure is about only 1.4%.

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So let me repeat this, this is very important. So the genome matter, we added.

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ask where after the ses after the parent of some of the parental influences in genomic, some of the parental environmental information, you know, after that's even controlled, the added genomic influence is only 1.4%. It's quite small.

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And you know.

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and

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the fact self-general measure reduced by 20%. Again, I mentioned this before, because there's a mutual adjustment.

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you know, when you add the self children's genome matter and parenting environmental in the same model.

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and we added lots of health behaviors. The health behavior don't do not predict invitation to writing in the model and schooling, especially schooling. This is what the sociologists really appreciate.

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The schooling. Their self education lines of education in school and neighborhood are really really important. But with all the control, they're still very, very important.

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And so the research is focused on genomic.

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a genet influence. So far the explanatory power is limited so far. Again, this is the current evidence.

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and they are all square for total environment, right? You know, respectively, total environment.

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self-general and parental genome. At 7 it bought 8%, 1.5% and 1.5% respectively.

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You can see, this is a and the, you know, it's so the environmental, in fact, even adjusted for some of the parental environmental influences genomic. Still, 8% is still dominant in the, in the number relative to the

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the current evidence of genomic effect. and

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for the social-sense research that follows the blueprint of including Ss. In the model interpret the ses effects as environmental. And that's not clearly it's incorrect. If you intellectually honest, that's not correct.

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And about 20% of scs effects

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you, we usually estimate, are not environmental, but the parental, parentally genomic. And the solution that we we have, you know, one solution would be to include the genomic measures in social-sense data collection and making adjustment when you report the Incidence! I think that

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that's the end. Thank you.

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Can you?

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Sorry?

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Ok, well, I'm sorry for those who are online.

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We didn't recognize that you guys were seeing the the screen, and then the next time If you can speak up, then it will know that the people are online were not able to see the screen. No.

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I got it. Okay. okay, okay. I see the problem. Okay.

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So I guess it's open to the floor. And the format is, as I said, first presentation, followed by the questions and answer session. yes, Tony.

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is that my on? Yeah, yeah, thank you. One for the

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about the findings. Your final conclusion is mostly interesting for me. You said that

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schooling and neighborhood have large effect, but you term suicide studies routinely control for gen genomic measures.

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and so on. How is it possible

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to do that?

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We haven't been able to do that for the last century, and collecting genetic data? Now that

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very few data of that kind of information. How? What? What can be a more practical and visible way to improve social science model results?

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Yeah, let me repeat, if you ask me the the ses effects in the sociological model. At least this 20% of the sei's effects is nomic, parental, genomic.

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But in the in the Us. Lots of a large.

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a longitudinal study by already collecting DNA data. The Wisconsin at Hrs. At hell of.

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I think every pi is trying to.

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you know, get money to get this? DNA, yeah, I don't know in the world. Yeah.

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yeah, I is there a statistical I learned long times ago when we have investment era, our estimate parameter, because the estimates will be biased down to 0.

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Their statistical method to say that, assuming

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the error is random, then we can adjust for it. You say

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in there, I probably question that

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it's just for it without knowing the management era.

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Can you suggest a statistical method to adjust for the potential science from omitting genomic measures.

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Are you using simplified? Yes, you just include the genome measure side by side with the ses, measures that would be automatically exhaustive.

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What about that? I'm saying that without that kind of information, can we say? Oh, it sounds.

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And I I don't know. I mean the behavior Genet is used to use of twins

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and siblings, and and I don't think that that twins and sibling studies that can do the you know, can do the trick. Yeah, you need individual level data that at the individual level you need micro genomic

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mayor in ss.

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okay?

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And any other.

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Yes.

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can you identify yourself before you start? The the first question was asked by Tony, and I'm an assistant professor of Sociology from the Chinese University of Hong Kong. his colleagues. So thank you, Professor, go for this very inspiring talk. So my question is actually about the dependent marvel. So now in this study, we we see that genomic information has a great influence on verbal ability.

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But I'm just curious, because this is one measure of one's capability, right? So for other capabilities. Does genomic Feathers also have that great contribution. Or maybe the contribution of genomic effects will be smaller for other type of capability measures. That's my question. Thank you. I think, for education or 10, an even bigger effect.

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Yeah.

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okay, so for other an address, it may have even bigger effect, for at least for educational attainment.

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the the lots of genomic measures. Now, the education tenant, Gibbouts, and IQ, the especially the Containment, the Gibbs. The Polygenic score is highly predictive of everything. It's surprised to me

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it's very, very predicted. High off. Well, everything.

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Okay. Thank you. Yeah.

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Any other questions any questions. who are on online?

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This is a delicate operation. You have to watch both more and online.

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Everyone's happy. Yeah, please.

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My name is Miaoyi from Prince University. So my question is. maybe 2 questions. One is the, I think, your third result. You mentioned that there is kind of

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genome, and Ss Cs N. Has each other. So that means like a kind of positive G, i. E.

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And they mutually reduce, if you include both the Ics and genome matter in the same model, predicting cognitability. They both reduce because it's correlation.

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So there could be interactions different. Yeah, we asked me the interaction. I did not have time to.

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I understand how your genome credits like a neighbor fruit kind of a neighborhood choice.

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And again, that neighborhood's choice in school choice. It's part of usually sociologists traditionally regard them as the environmental. but

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but their parental decision, so they could be partially and and genomic.

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genomic, partially genomic for the schooling neighborhood choices.

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and

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it being this type of malice with only one generation of genomic measure, the children, not parents.

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Again. This, I think we, I think we thought through there could be like a I think, a 50% of their

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bad decision.

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And the the parental genome

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it's controlled because of the adding there, including

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individual children's genomic matter.

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Okay, I do. I think we are running out of time. So thanks for the excellent presentation.

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we'll move on to the second presentation by Marion Fisher Newman, that I pronounce your incorrectly

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Ok. So I'll just ask you to take over the screen.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): can you? Yes, I will share my screen.

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Great.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Yes, I hope you can see it. And

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): now I start my presentation.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): So thank you very much for having me here, even though it's only online, I hope. I will be there next time.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): he and Germany is really in the middle of the night, so I hope it works well as on my talk and afterwards at least get in touch with me. somehow, if you're interested in this topic, because in at the moment. I'm studying the world of specifically all of the things for the education attainment, for children with migration, experience or not.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And that's why actually, we all grew up with the some on the form of discipline.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): maybe by logic half the things types of things. And this is so really initial experience also in Germany. but in comparison to the relation between parents and to children, we do not know much about actually the influence

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): between the disciplines.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): I mean, they actually quite important and partners of the action. specifically, also doing it all a sense, the leaders increasingly interact with peers and also include siblings and

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): much more than also to the parents. And even though they share the same family environment, there is variance in their education attainment.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and they are kind of really a special features included in the sibling relationship.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): So in comparison to the have a child relationships, they might write more. how it's on, sir. also related in equality, in in in power and and developmental status, and they actually one of the longest relationships and family relationships in life.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and to do the calling up together. They are right, emotionally close.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and even though they have similarities, although with the peer relations outside the family and thereby offer opportunities for peer interactions. they are quite more stable and also more emotionally close.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): So actually, also, the literature already shows that they are main socialization agents, and there are different influences also running the what we're supposed to call way from the order to the young as the blink, but mainly from the All, as the links concerning cognitive and

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): learning. Social competence is because of the age related head start. And though I actually quite important sources of support and information. You can guess.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): What does the abuse which I tell us about the influence on of siblings on education attainment. So we actually have mixed findings, so many studies. Taking more. These structure features of sibling constellations into account, like both our on number of siblings, they found

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): mainly a negative influence on the occasion. Attainments. If you are data below, you are

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): much more worse off and education attainment than the All the disciplines in the household, but that this effect is not always found, or, as is it, it might be, a dependent effect. So a whole and colleagues are showing that, for instance, for a second generation migrants, there has no negative birth, order, effect.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and other research, starting to taking more the concrete resources of something also into account, also the education attainment of orders, the links showing that there are positive influences running positive spill over effects of education between all the and young as a blink

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and the as we do, we have a a mixed picture, but going more also into the really resources of the all of the things that the research is just calling. And I want to add to this research. And what is the links? Micron family might be even more important. we have

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): generally more children. in this families. of with my creation experience.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and they are collectivistic norms that also relate to the obligations of of of all as a link to take care of the young as a blink, and they have really a strong cohesion on this families, and comparison also to, for instance, of Germany, native families.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and They asked. already some, we said, showing that all of the links in the migration families might be, purchased to the majority context, cultural as well as educationally. So really also in qualitative studies, showing, though the All as a link to really showing how to behave and what's up to to choose in school.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): So my research questions relate to better orders of links resource for the education at the session under which conditions actually actually, this might depend. whether that difference between micro and non-migrant families. And you may know or may not know, that the education system and

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Germany is quite a highly stratified and different transition point. So it's kind of that you need to invest in this education to check to you. You are going through.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And I take in general, a model for the education and influences that may one, from all the siblings actually zoom capital to young as blinks

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): investments in human capital by echoes and colleagues. So it's like in extends the value theory, and I concerning the interaction frequencies we know in people's lives with all the siblings

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and concerning our social running theory, who tells us that all those things are quite attractive to compare with and to be a point of orientation? I would say they are able to really efficiently influence, motivation and beliefs, cognitive processes, and their influence, the educational decisions of young as a blink and their attainment.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): But this might depend concerning also taking into account the literature on siblings, that there might be either identification, though, that the transmission takes place or the identification not taking place so that

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): there might be people. conditions. that this happens, this transmission and this might relate to On the one hand.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): the structural characteristic of the sibling constellation. So how is the biological relatedness? How it's the h spacing to the all of the things or the gender constellation and the zipping relationship to the order of the links. But I take, I mean the other structure. Features have been often taken into account, saying that similarly, and age similar in gender, though the transmission is more identification

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and not the identification, even though they are also the opposite hypotheses, because if you are quite close, you know more likely you want to be identified. with your siblings.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): But I also take into account cultural and social related resources like the cultural capital of the of the all of the blinks or the social relation to yeah. Relating to social capital. I mean, I already talked about the more important role of all as a link in migrant families because of the all the differences of the related capital that's well, and in the economic end is

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): educational. Systems of parents often have not this resources, and we have a scouts. Any dance concerning, for instance, that siblings are really more talking in the in the majority language and the family, and that they are education and role models. And so I already told about this more important role. That's why I have actually hypothesis that does intergenerational transmission between all. And as the blink is dependent on the structural features.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): We've lost related features as well as depend on the we have families. With all this out migration background I take into account. the.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): It's quite interesting. It's a panel study. It's a quite interesting. It's a panel study, and it's a household studies or a gathering each individual. And therefore also zip links in the house, or at certain point of time, and I restricted the sample. I to a driven off of that house was at least one, all as a blink.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And you see also the child observation that there you have left the

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): with the all other things, at least at 1 point a time. during childhood, or at least

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): I take into account multi-level regression method to take the different customer into account. And you see here also the total number of observations. I have my analysis persons and the number of families you

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): see here. I mean it quite each table of the different also had variables and control. Where this I take into account, I will not go into this all, but I have a social, demographic characteristics of the respondents, the social origin measures as well as also included, of the parents. And then I have all discipline measures. So this taking into account they completed education, years of education.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): as well as independent, variable, as well as dependent, variable, or the education, attainment and years of education.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And you see also some structure features I take into account as well as so capital related features. And I you can use the also some difference between respondents of families with and this out, my creation backboard. But going more to the resides, and having this multi-variate regression analysis.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): I show you here most of all this measures, because I'm interested to see how this, where we are working, relating to gain it. It more education over time. And you can see that there is a positive

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): into a generation transmission of

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): maximum years of a completed education. And they all discipline network, because I have at some point. Even so, most of them have only one older sibling, but they are so average about 1.5, all of the links available. And for sure this also varies. So I have to add a positive in the generation transmission that I wanted to see at first.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and I have here also some other direct effects of the variables I take into account, but most of all I'm adjusted, and this one effect and the dependeness. So I show you first, here the migration background. If there's no migration background and whether they're they respondents first or second generation. And you see here that the intergeneration transmissions with the effect between all the siblings, zoom capital, and young as it brings.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): is lower in the context of any kind of migration status

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Concerning now all of the dependencies on structural characteristics, to see the the higher the number of orders of links, all the the lower is the inner generation transmission of the zoom capita in terms of the years of education. But if you also here, looking now differentiating between how this mechanism works, or does it apply between non microns and migrants, and like, when with migrate, backbone, or and or from native families.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): you can actually see that here we find only the that that it met us, and we find the differences concerning the number of orders of links for the transmission in Micron families.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): This also relates to both spacing with the larger the first space that far the on the iway concerning the bus. you know, first, the order of the links, the lowest, the transmission. And this is also actually only a meta for micron families

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): the same sex, or doesn't links easy it more actually that the transmission is stronger if they are all the other sex owners, the links available in the household, and see if that but finally, the effects are not significant for either group. If we direct, differentiate the respondents from families with and not this, and without my creation background.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): 5 by and a full biologic is the link. So if there is a biologic relatedness, so the with the mother and the father, then they ask actually transmission to stronger, and this also is a mainly a matter for respondents from Mike and family. So they are. It matter that there is biologic relatedness to the all of the things. So the transmission

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): relating to more the culture on social capital features. So zoom how much they spent together in a in a dollar sense. With the older siblings you can see that it increases the transmission of the human capital.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): But here you see that, and a comparison to the other. the fact that I showed you before that here, and the for the respondents from the native families it's met us by. It does not matter for families without, with my question that I'm sorry.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): also related to casual capitals or the catch of participation. of all the siblings also relate to a higher transmission of between the education really is of the orders of links and the younger siblings. And this is all also only related to now to the or an advantage for the native children.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): So in all I see actually, and my first study here, that there is an in intergenerational transmission of you and capital between all and young as the Bl.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Mit ctl, and and this varies by structural features of the zipping constellation, as well as with a cultural and social capital features of this zipping relationship. 250,

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and it varies by my client back on so for my friends, it's mainly met us. How the structure, features, and the conditions are so closely spaced, biological, older siblings.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And for natives it's more that the cultural and social capital related features of this zipping constellation met us for the transmission of the into our generation. Transmission of human capital in terms of

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): educational years. As an outlook. The next steps are to take into account also more closely and directly the gender of the young as a link, because this really made us so. they are also. The trans transmission may take place according to the literature, and I take into account more closely the migration background, because we have different countries of origin involved for sure in Germany, and that I want to study more closely.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Thank you very much for the attention. if you really want to get in touch with me, don't hesitate, and I'm looking forward now to your questions and thank you for your attention.

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So

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thank you. So we're open for questions and answers. Anyone from

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this room or

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the

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yeah, Louis Andre.

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you have a question.

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Louis-André VALLET: Yes, thank you very much, Marion, for

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Louis-André VALLET: for a nice presentation.

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Louis-André VALLET: What it in in your concluding slide? You you you showed differences between you

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Louis-André VALLET: between my grandchildren and non migrant children in terms of the influence of all the zipping. And

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Louis-André VALLET: well, do you have hypothesis of faults About What What could explain? In fact, these these these differences?

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Yeah, thank you very much for this question. Yeah,

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): I mean, I'm

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): not quite sure. I guess it depends that the capital

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): is, for sure, more present, and the in the native families. And that's why I was there. They they Capitol as a more count, and it is relevant. And as they are also this influences. But as as soon as you have this resources is, is not much of a meta How closely spaced the owners the links are, or if they have biologic relatedness. So this is really a resource, or we entered. And

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): yeah, for for Microsoft's children and my friend families there is. that's the importance of that. They can closely be observed, maybe because of those H spacing or that that's the biologic relatedness, so that I can really maybe the interaction taking place and then profit from the you capital, I mean, I'm taking all of the All as a link

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): with the human Capitol into account. So there is this capital, and as long as the structural features are all the then beneficial, then it's There we find that the the the transmission and so the resource related to features do not count that much so. yeah. But I' also astonished that That the structure features only a matter that

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): on in the migrant families, and we do not find that it's met at that much in the native families. So yeah, but I need to think for that about it.

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Louis-André VALLET: Thank you.

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Any other questions.  yeah. one.

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And

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but the siblings siblings are genetically 50% the same. They share 50% of the genes. But of course, the different distributions.

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and you would expect the siblings similar with respect to educational attainment and with everything else.

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Yeah. what I wonder? And

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so some of the influence could be systematic, right.

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and

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but wonder if you could use the migration

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and to ask me the migrations as a

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migration family, as additional, in fact, as it's represented special cases.

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because education, because migration families have a last connection in the best nation countries. whether it is to do a comparison with migration children.

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you know, with the ordinary duty in the country you could, you could really overcome some of this, I think.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): Thank you very much. I mean, as I could hear you, I mean, it was not that easy. But this really interesting point, I would think about it.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): because for sure, I I need to take this this into account, this genetic.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): so yeah, this is really a nice suggestion to think more. So this is, I think I can say and if you want to. maybe

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): what to discuss with with me a more closely, then, please also, you know, get in touch with me. yeah, thank you.

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Any other questions I need to look at the

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oh mine.

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If I understood your presentation correctly.

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and among the immigrants there were a clear effect of older siblings.

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but among the non-immigrants or natives there was no clear effect of older siblings. It's my understanding right.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): No, there's also a clear effect. And in the the the direct effect, it's it's it's higher. So there's a strong engineeration transmission that the conditions and how it is model way that varies. So this was some things or did On the one hand, the structural features does not matter for the transmission and the native families.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): and you know, and but they capital related features of the relationship. And this, they we were in the Macron family. So they are. The structure features counts and not the capital. So it's it's the dependent effects I'm looking at, and that there might be different mechanisms going on in my current and non-migrant families. So this is actually the aim of my research.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): That's I want to look at tomorrow. The conditions under what? we reasons it takes place. And if if there are differences between my and and my friend families.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): sorry I I just didn't understand that there was a many effects. We're also present in both. Yeah, yeah, we are sure this is really a really, maybe it was too much for the the short time. But this is actually not the case. That's There we will not find the a clear effect. We find it key effect as well, and even a stronger effect. But the motorway that effects where we are different and the different family types.

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Thank you.

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Okay, just final questions. Yes, thank you for the research. I'm Jenny from Chinese University of Hong Kong, and I would like to

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But I like your research, and especially about the effects on non-negative family, and also the migrant family, and one of the factors I've read would be for some of the migrant families. They depend very much on the resources or the capital from their original country.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): And would that be? what do you think about it? Yeah, yeah, that's it's really important to take the the capital features monitor account. And actually the sub-study I'm using also have a kind of questions relating, for instance, to the competences in the l. One. And I choose all the also a language of origin. And so I could Google

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): more closely look at this microwave related, and resources and that relating to the migrant origin, and see how this met us. There. If you are, if this is your point.

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Marion Fischer-Neumann (University Duisburg-Essen/InZentIM)): But I haven't done so far.

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Okay.

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I think we are ending this question and answer session. Thank you very much.

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Thank you very much.

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So we'll move on to the serve presentation by Yani Chen

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scissors. Thank you very much.

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Morning. Everyone. I'm Jenny Nyani-jung, from Chinese University of Hong Kong, Today the presentation of my topic is about gender participation in fields of academic study. I would settle on the global expansion of women's enrollment to free for use humanities, natural sciences, and Jewish sciences in higher education from 1990 s. To the COVID-19 era.

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 on on on gender. When I try to approach this topic, I will have some of the main research questions here. they are the guiding questions. I have. the first one. Why do modern ideologies of gender equilibrium

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in in Hong Kong in in high education become so prevalent across the world and the other one I'm I'm pretty concerned about. The question about how does gender participation look like across time

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and the last one moving? What are the underlying forces that generate a a homogeneous expansion in enrollments, with an increasing string of traditional gender gap, or even a reversal of gender gap

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and the focus of today's sharing and presentation. I will look in the women's participation in global higher education across time. And also I will look into the changes in enrollments, in free fields of study and the regional patterns is another concerned. I have to what extent it is shadowing the global trend. And can I find any global variation? Or will I find any similarities? And the other one? I will look into the increasing women's participation.

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First of all, I try to examine the partitioning effects. Would there be a concentration in traditionally female-dominated fields of academic study, and the other one will be Would there be any integrating effect which means There could be some transverse discipline with the reorganization of knowledge, for example, new categories of study in inter or multidisciplinary study.

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the theoretical approaches I adopt will be mainly too big approach, and the first one, the high education for a role approach will be the approach that to be my favorite one.

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The theoretical approach is based on new institutionalist approach, and it has to focus on looking into gender participation as a world culture where countries of developed or developing world, they usually taint the local participation of higher education by a touch of the world's most pattern, trends at the same time, due to the local situation. They will decouple their daily operations from these trends.

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And we from this theoretical approach, gender participation will be considered as the transnational effects of formalization with external links to global cultural carriers. For example, scientificization of of curriculum, or any kinds of

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equal ideology, and on the contrast, some of the theoretical approach will speak to this new institutionalist approach we based on the normative theories.

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like human capital. Capital accumulation is most in is angel in the development of higher education, and the second one will be some social differentiation theories looking into the stratification, and also the structure of explaining why there is a variation in participation, and the last one will be a rational choice theories where we having Why, people are taking different choices in in fields, especially in science, in in the stem in higher education.

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On

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my, my, my methodological approach will be based on a world region and policy method. It is an integrated framework using some comparative and longitudinal data for my study

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in in the world level of study. I have the cross National trend study in for 182 countries. in after after Second World War and in the regional study I will use a panel study. I have 51 countries from Asia. I have 2 time panels. starting from 1,950 to 1,989, and then the other one starting from 1,990. This is the most critical point of the reversal

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of gender gap. And last one I tried to use a case study a quality study. And I this time I chose Hong Kong.

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Some of the measurements and indicators I use for especially for the for the regression data analysis. I have the dependent variable, the national and enrollment in higher education and about the independent variables, because it is operate on a aggregate level of countries.

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I have the economic modernization. I have the nation building through education, and the third one will be the state strength and austerity, and the last one will be a work system integration.

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let me share with you the data sources and characteristics. I, I mainly use secondary data. it comes from the Stanford Comparative Institutional seminar team. but it ended in 209. So afterwards I would do most of the data Update by myself by using Unesco's data quality form and the work development indicators or some of the religious data archive.

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And in case there are some of the countries. They have not report the the data to Unesco. I will go to restsive archives for update

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and let me show you

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the general, the worldwide trend of higher education after World War Ii. And here is the graph and is showing an upward trend. But I want to put it side by side with

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gender participation in higher education after World War Ii. The pink line would be the female student participation, and the blue line will be

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the male student participation.

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And I think it is easier for me to put it side by side for you and share with you my observation, and how these 2 trends, showing that the overall train is increasing and also getting very rapid increase after 1990 S.

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And the other one. My one of my concern is that it is not just the number. It is also the core quality and the curriculum expansion. And I have here.

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the the available data is is pretty difficult to get, and I only get from 1,998 to 209, and I try to put it into 3 time periods. Here I have, the first time period, 1,998 to 201, the second 202 to 205, the last 1, 206 to 209,

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and I have 3 fields in

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to show this and Roman data the humanities through sciences and natural science. At the same time I try to put it in in female and also male.

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 showing them the mean percentages.

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I make a quick summary for 4 patents I identify from the table. I've just shown. First persistent increase in every disciplinary area of higher education in the world, and the increase remain constant over time in terms of enrollment to all disciplinary areas among all students, second, their Romans to humanities remain relatively stable across all time points.

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Third, Try to look into the subject matter, social sciences, and wrote the largest number of students. In less than 2 decades, about 19% of men and women in the World age group 20 to 44 were studying in show science

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and a further breakdown to compare 202 and 205, with 206 and 209, which is very second period and the second third period. Women's enrollment shows the largest proportion is allocated to show science compared to humanities and natural sciences.

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The last pattern I've identified would be sugar. Science and natural sciences increased sharply in the time periods of 2 2 to 5, and to 6 to 9.

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That shows persistent movements of women into sugar sciences and natural sciences, and men were increasingly moving into the disciplinary area of show. Science, too.

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so what exactly are the changes.

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I did some tables of intercourse relations between these 3 time periods I've selected.

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and the first one I will make a comparison. for the first time period. with 1998 to and 2,002. And I've noted from the intercourse relations all 3 expanding across time, and the shoes sign show the most apparent-legged effects

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it could be due to observation. We had on increasing women and men's enrollments in the last slide table. So what is the next step? I wanted to make a comparison. I would look into I found different from those in the first time period there is a flow of enrollments from humanities and show signs to natural sciences.

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So another change I really want to. Highlight will be I put it into free time periods.

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The first time period I noted a complementary effect, which means all fields are expanding together, and a set time, second time period is a replacing effect. There is a declined in humanities. There is also an increase in sugar sciences, and natural sciences. In the third time period I find a replacing effect, which means there is, has declined in humanities, and increase in show sciences and and natural sciences.

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So

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How would we understand that if we put into a regional understanding how common are these trends in different regions? And I look into the mean percentage of enrollment in all regions. I have to west Central Eastern Europe, sub-saharan Arab States, Latin America, Caribbean, the Pacific, and Micronesia, and also Asia. I find that It is very similar to the world percentage.

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Perhaps a visual a visualization will help us to understand how closely Asia is trying to catch up with the world trend

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and Why, if I would investigate Asia because, the real world region has a culture which is practiced by most in the world, and, secondly, it contains a local culture, and that is indigenous to some societies in the region.

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that it cannot be found extensively in other regions. And the next one is that I really want to know

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the external cultures that were spreading to these indigenous societies. would economic modernization, as most matter. Incorporation of modern education system would make them similar, or would there be? the level of offer? State authorities would make that similar? And the last one. Would there be any external languages to world policy will make 150

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high high education enrollment as different or similar.

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and I use a regression, a very simple regression model. to to to try to examine all these factors, and I have some of the results in time. One and Asia has a very consistent pattern, with across the world, and time to I I knocked a a little bit different. The world system legitimacy has been shown. Countries with characteristics of nation building.

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higher degree of state control and closer binding to the world system tend to expand expand higher education and probably there could be some of the characteristics that can be fined in Asia, because richer countries with an educated citizenry, they tend to expand more in higher education, and also there is a lower degree of State control, and, lastly,

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the lowest linkages to world or integration tend to have rapid expansion over higher education.

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If I put it in to the

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the context of gender participation in Asia, I look also in time and and time to by by the gender of men, women, and men. I have found something. the economic modernization and and education for nation building would be pretty much consistent over time, but for state authority and world system integration. I noted a a shift of the coefficients

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and what exactly the regression model of Asia tell us, and in time one it will. It can be interpreted as underlying forces for gender participation in Asia have shown consistent patterns. Authoritarian States tend to have strong control over women and men, to again gain higher education

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in time. 2 I also knocked a world system legitimacy, effect, but by gender is a little bit different. Men's participation. Countries with characteristics of nation building. A high degree of state control and type binding to the world system tend to expand higher education for men.

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but in women's case the loose binding will be a very special feature that I can find, and

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the implication here will be both lose binding and tight binding to external environments. They are always 16 with this case of gender participation.

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So it it looks a little bit unexpected. But if I put it into a case study, perhaps I can. And yeah have further answers. And I I really want you to know the underlying forces that you have this loose binding and also tight binding forces at work. And Hong Kong. Perhaps it it is the case to help me and

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Let's take a look of the high education enrollment in Hong Kong, and it has a consistent distance trend in on gender participation as that of the world and Asia. Here is the overall. It's an upward trend, and also the reverse of Gender Gap is in up to 1990 S.

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And the analysis of Hong Kong, Because of some of this special feature. It is a semi-autonomous region, with relatively weak state control, and also have some bindings to external environments in both the colonial and post-colonial period.

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And

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what shapes the patterns of gender participation in higher education, for example, the women participation will have loose binding. I can find it. One of the possible answer from the case study will be an academic tracking, and I noted there is a regrouping of curricular content in 2 or 9 in secondary school, not in higher education.

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a selected effect that I'm looking into, and which brought all the traditional categories of subjects and the tracking mechanism to an end. And also there is a a reallocation of in instructional time. So I will look into how the secondary school curriculum reform shape, the high education, education, landscape.

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And here is the all curriculum secondary school curriculum on the left hand side, and I have the new curriculum starting from 209 and

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the percentage, especially in the language has changed in the new curriculum. And let me give you a quick summary of these changes in Hong Kong's reform. That the new allocation of time reflected a Greek to emphasis on the use of languages than you all one.

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A great amount of time was devoted to Chinese and English languages, and and I've taken other course subjects they have to do liberal studies. This also required a lot of language use and critical thinking, and the core subject of mathematics receives just half a portion of the instructional time in the upper

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old Past senior curriculum, and by this new allocation of time the like, the elective subjects received only a portion of 30% in instruction.

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Sorry

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was even less than a half of the original allocation in the traditional one.

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So under such reallocation. Students who have stronger orientation to science subjects receive less instructional time than other subjects with greater language, emphasis with the strength of instructional time. Language of abilities seems to have overlaid other academic abilities relevance to students achievement in the public entrance exam to to higher education.

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So Lastly, this is the last slide. What I would like to share is the new gender regime via the curriculum regrouping that shape, the entrance to higher education. The curriculum regrouping has a significant implication. The opportunities enter into higher education.

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and with the strong emphasis on individual choices and interests, claim for greater orientation to student-centric curricula and pedagogies, the academic edges of traditional gender distinction began to move

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with the new curriculum and evaluation criteria. Female students are more likely to perform better than a male, while the traditional advantage of males in mathematic is is graduated, disappearing. The regrouping of subjects seem to have created a less favorable situation. The may students to have relatively weak language abilities and females in the same age group.

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So

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I think I I have to stop here because I've used up time. But I think we can do more in the discussion time. Thank you very much.

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Okay. So it's open to the floor. And

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so I'm going to go and ask questions.

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And many Us. Universities, major universities, the proportion of undergraduate students, male students like 60%, 65

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versus 35% female.

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we'll we'll do a

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what what would be the be for reasons for it?

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Thank you for your question, and I think I can approach the question in 2 ways, and the first one. If if the new institutional theories approach is correct or convincing.

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properly, it is due to the The secondary curriculum properly. I I think in. I'm not familiar with the Us. secondary school curriculum. Maybe. that it is pretty balanced, and it is not totally relying on language.

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Perhaps they have more so mathematics or science, or even stem education and that will explain one of the advantages for male students in the, in the final exam or the university entrance exam. They won't be having. The results won't be dropped

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by simply having more emphasis in language. abilities like that in in in the case of Hong Kong and the other one will be I guess it is also related to the eglitarian ideology of gender participation, and and also

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yes, that would be some of the subjects encouraging more women to participate. But I was wondering.

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Perhaps it's a little bit different from some of the case study I had in Malaysia or India. Not. There would not be any quota system. and and so that might explain why male dominance will be in, for example, in the engineering or the science area.

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So that would be some of my punch. Thank you. Thank you for the question.

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Oh, I know that's a question from online.

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Hanna Ayalon: Thank you for the very interesting presentation.

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Hanna Ayalon: could you tell us a little about the prestige of the different subjects, I mean the if the change in the curriculum, accompanied by changes in the prestige of the different subject, the humanities, social sciences, and natural sciences.

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Oh.

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oh, that! Let me try to Make sure I I got your correct question correct. which means, the traditional prestige of the or even selectivity.

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Hanna Ayalon: Press this and selectivity of the different subjects.

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Hmm, yeah. I I think in in Asia. most of the time for science. We will be occupying more prestige or to be recognize as a a a students with a higher score. They they will go into like medicine or engineering

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but but usually this is a male-dominated area, but in in female they they usually go for arts, humanities, and also social science. And but but this is quite interesting. In in Asia more and more

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men are entering into the sugar science area. And one of my hunch will be that there, there will be an emergence of interdisciplinary area. For example, like data, science. It's a combination of suicides and and also science.

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And I guess that will be some of the reasons, and and also some of the The the usual impression we will give to different fields of study in in Asia.

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Hanna Ayalon: Thank you.

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Thank you. 30.

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How feasible is it for you to disagree with social sciences, so sciences is

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mix up there.

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You have the economics of psychology, and so on. And I I would imagine that

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now that

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plot toward economics, whereas women would be not a heiress. So if you lump everything together and the solo science thing can be a

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so the tricky thing, hiding things, whether it will affect your theory. Testing or not, I would like to hear. Okay, thank you for the question. Yes, I think it is true.

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for the category of of of knowledge for economics and also psychology. Somehow it is pretty close to science, or in some of the university. They just put it in the faculty of science and

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and I I I looked at. This is an important thing I have to recognize. Otherwise I can not really like what you said here out exactly

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whether there could be more women entering into economics or psychology. So thank you for the question. And I think I I really need to tear it out. but actually, from the practical side, because I I've got this all aggregated data from Unesco, or from some, some, some of the very possible source I I get.

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and actually they The categorization was not done by me. They just lump it together. And so I I think.

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instead of asking whether I can really find this sort of data, perhaps I really need to start my own data and and try to make a very clear differentiation, of which area actually, that subject belong to? Is it really closer to science, or really itself is closer to humanities. And thank you. Thank you very much for your question.

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Okay, okay, very quickly. Yeah.

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You don't have to run.

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You want a quick. So right. tomorrow, science from the University of Queensland. I just wanted to ask today, well, it's not about science-based. It's not science, because even within science there's huge diversity, and, you know, depending on the country that probably might look a little bit different, but is at least in some countries there is evidence that graduates of biology which intend to be also a female-dominated field.

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we tend to earn a little bit less than even social sciences, and so on, whereas engineering it. These are the best pain fields. So I wouldn't focus on this aggregation only on social sciences, but also on stem fields.

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Okay, thank you very much for your question, and also commented, and I think that helps me to move forward to to my research. And it is not simply looking into the categories of whether belonging to science or not. And actually there is a further integration of different subjects, and one

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and the other one you've mentioned a very good point for those who are doing biology. Somehow they will do food science, and also in nursing, or some of some other areas related to health.

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and I guess this is what I really want to do, especially after the Kovat era, and I've noted some of the interviews I did. Some of the young ladies in secondary school education.

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They really want to enter into the field of science, or medical related, because they will think this is having a a more practical stand in the future. So I'm not sure whether the secondary school curriculum which is heading to us. Having more stem education, can. Will it be changing the, the the landscape of higher education? gender gap in the future?

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So thank you. Thank you very much.

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So we move. We move on to the last presentation by Hulia, which you go see?

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 this is good, I guess. So. Hello, everyone. My name's Homiya Jkoshi. I'm a Phd, candidate in sociology at Princeton University. actually, the last presentation is quite led upon to what I'm working right now, rather than focusing on college measures. some extent. It's kind of related. But I'm working on. Why, few women apply to selected colleges in in Japan. This is my one of my dissertation projects.

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Okay.

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so here's the objectives. so in this presentation, I examine how academic, very competitive high school students, they plan their educational trajectories based on what we call emerging future, like a perception about what their future looks like.

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I focus here on gender differences, me and the women and I specifically labeled the case of Japan, which is calculated by first highly uncertain admissions and also diversified higher education contexts. Japan is also calculated by the one of the most gender unequal. societies among rich countries.

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Okay, I think I don't have to explain, because The last Presidency, Professor Yani Chen. She already explained. That in many countries women outnumber men in higher education, especially in ditch countries. So

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Here's Oecd figure showing that the the the male female miners, male enrollment in higher education. So that means positive value means more women are enrolled in those institutions. And, as you can see, over 20 years. The rebels have been continuing in many countries.

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However, my question is more on kind of heterogeneity or variation within higher education. perhaps gender gap rebels, or may not be the case for selective institutions. So let's look at that. So first I collected several countries. the female, the share of female students

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in selective institutions. And first, I'm showing the 4 English-speaking countries, including Austria.

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It's kind of difficult to make a comparative kind of definition of what selective institutions? so I kind of rely on the conventional with them. So for the Uk the female share is defined by the Oxbridge, like Oxford and Cambridge, and for the Us. It's a group of Ivy League colleges, and, as you can see, many all countries for those 4 countries, Canada or Syria, Us.

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And the Uk. More than half, or at least parity is achieved for the gender Gap reversal in selective institutions.

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let's look up to East Asia, China, and this house career.

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It's not really her. It's not really parody, but still more than 40% of our students in selective institutions. Those 2 countries are women. maybe not bad.

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Let's look at the Japan.

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So only 27% of female are students are women in Japan's selective institution, which is defined by a group of 7 national selective universities, including University Tokyo, Kyoto, and Tohoku, and actually the University of Tokyo, stands out in in the sense of the underrepresented age of women, only 20% of undergraduate students in University of Tokyo are women.

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and this is really remarkable when we compare the value to the overall female attendance in BA. Like a 4 year, institutions in many countries, more than half of women attend four-year institutions, and similarly to the selective institution. However, the gap is so

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huge. For the case of Japan!

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01:22:17.010 --> 01:22:32.170
So that makes me wonder why this is happening. So one important institutional feature I want to discuss here is privatization. So in Japan, as I show shortly, women's college attendance has been driven by

451
01:22:32.400 --> 01:22:36.210
growth of less selective private sectors.

452
01:22:37.340 --> 01:22:56.950
So this is a person of email university students by institution type. So here I'm first showing the overall, like all university enrollments. And, as you can see about now, as of 2,02045% of Students of women in all BA institutions.

453
01:22:57.970 --> 01:23:11.929
But this is primarily driven by private sectors. As you can see, the the shared women endorsed private universities much higher and increasingly higher than the all universities, so that means that

454
01:23:12.020 --> 01:23:21.520
the other side is that the national university or public universities which tend to be more selective and prestigious in the Japanese context.

455
01:23:22.570 --> 01:23:28.680
it's constant. This is only for national universities, but only satisfy what sadly, 6% of

456
01:23:28.700 --> 01:23:39.200
students in those so relatively selective national universities, women and interesting thing, interestingly, is that it's been stable over 20 years.

457
01:23:40.710 --> 01:23:50.260
And another interesting practice. There is a selectivity gradient in the Shell Women, so that means the more selective. The selected college is.

458
01:23:50.740 --> 01:24:06.669
Few of women are enrolled in those institutions. So I I'm showing the 3 Top Tier University National University in Japan, University of Tokyo, Kyoto and to Tohoku, and, as you can see, there's kind of gradients in the the Shah of women.

459
01:24:09.020 --> 01:24:10.110
So

460
01:24:10.700 --> 01:24:13.729
this is at least tasering to me

461
01:24:13.750 --> 01:24:22.849
so, because first, as I showed just now, most selected colleges in other, we'll see attruce, English-speaking, and To a East Asian societies

462
01:24:22.970 --> 01:24:24.700
kind of achieve parity.

463
01:24:24.760 --> 01:24:49.679
and many Co. It selective high School in Japan at Gp. Already, although I didn't show the figure. But this is something for sure, and last 3 person and female, admitted students in those selective institutions is highly correlated with the person of female upbreakants. So the question is not really about why a few women less likely to be admitted to those university. But rather why, if you women apply

464
01:24:49.930 --> 01:24:53.440
to these selective institutions? So that's my research question.

465
01:24:54.220 --> 01:25:05.730
Specifically, I'm asking, why do then few women apply to selective national universities, even when they are academic opportunities comparable to men.

466
01:25:07.330 --> 01:25:11.660
So there are a couple of theoretical implications I could discuss.

467
01:25:11.880 --> 01:25:39.609
One is the consequence of the global increase in private education, which is not really about, which is not not not only the case in Japan, but also in many countries, private higher education has increased. And my argument here is that there is some sort of maintained gender segregation via privatization. So basically, what I found based on my Corey day of interview with high school students in selective school in Japan is that

468
01:25:39.610 --> 01:25:56.899
that perceive the future like imagine. Future is different for man to women, and based on the different future perceptions. They are choosing different kind of educational trajectories, and actually new, re-established, mostly less selective private universities. They specifically target

469
01:25:57.620 --> 01:26:09.149
the population which historically didn't have access to higher education. Very well, which is women in Japan. Then this way of approaching potential students

470
01:26:09.250 --> 01:26:40.730
among private sectors contribute to the, to the narrowing, the universe of possible futures, especially for women. and this might be specific to the only Japan, but those. But actually, I'm thinking, I I to discuss in the future that that perhaps the same mechanisms could apply to other countries. For example, the for-profit colleges in the Us. Is primary, private. It's basically targets minority populations, such as black population or Pope students. In the Japanese case, it could be women.

471
01:26:41.830 --> 01:26:45.829
So to answer the question, I focus on the

472
01:26:46.260 --> 01:26:49.759
selective high school in Japan, where

473
01:26:50.070 --> 01:27:02.069
everyone go to college. So that question is not whether they go to college or not, but rather which college they go. They are a group of either top or first-tier high school in their local region.

474
01:27:02.130 --> 01:27:08.130
and a sizable number of students admitted to the selective national universities.

475
01:27:09.050 --> 01:27:23.569
So these are 13 high schools, 5 prefectures, a mix of co-ed or single sex schools. and these results are based on my, our semi-structured Corey-tep interviews with a modern

476
01:27:23.610 --> 01:27:27.489
slavery over 100 high school students and high school teachers.

477
01:27:27.820 --> 01:27:53.059
before showing results. There are a couple of things I want to mention. to understand the higher education context in Japan. First, there's a clear institutional hierarchy in terms of prestigious selectivity. So the 7 National Selective University, as I discussed now Tokyo, Kola, and Tohok, and so on, is widely recognized by the Japanese people in Japan.

478
01:27:53.390 --> 01:28:05.969
And also another thing is that our admission is departments basic. So that means that, unlike the United States and the many other countries. You need to declare your field of study prior to entering college.

479
01:28:06.890 --> 01:28:28.889
and admission is, is done separately for each department, and another important future in Japan is that the students can apply only one or 2 national and public university which tend to be again more selective than the private university. In the Japanese context. So that means that you have a good chance of

480
01:28:29.880 --> 01:28:34.880
fair failure. If you fail, you have 2 choices. One is

481
01:28:35.750 --> 01:28:44.230
to enter your second choice or your safety school, most of your private universities, or you may have to spend another year to retake the exam.

482
01:28:45.680 --> 01:28:48.879
There's huge gender gap in the exemplary taking, by the way.

483
01:28:49.050 --> 01:28:58.560
So this is kind of basic timeline. And if you are really curious about high school students, how they take the exam.

484
01:28:58.560 --> 01:29:22.250
I'm happy to answer, but for the sake of time I'm skipping. But I just want to mention that before the National University admission is more demanding. First, you need to take. Generally, you need to take the nationwide test, which requires 5 to 7 subject, and after that, oftentimes they take the second stage Unlike the private university, which doesn't require such demanding kind of exam, kind of schedule.

485
01:29:23.080 --> 01:29:34.630
Okay? So this is a list of high schools we reach out. Then I'm going to focus primarily on 2 high school in the prefix of Saitama. It's next to Tokyo. So it's

486
01:29:35.370 --> 01:29:57.869
quite urban region, and these 2 schools are one of male and one female only high school. So these 2 scores are quite similar in terms of the the share of their students attending college 100%. That's the same, however, which college they eventually

487
01:29:57.950 --> 01:30:01.250
enter is quite different. As you can see.

488
01:30:01.330 --> 01:30:15.860
University of Tokyo and the Codo about 13% of male students. The students in male high school went to the either of University of Tokyo Kodo, whereas only 2% of the female students went there.

489
01:30:15.870 --> 01:30:33.759
and I'm not going to discuss the other 2 categories. But actually, there's a huge gender gap in terms of the aspiration and also attendance in those selective institutions. So I'm going to show you why this is happening so first in bars high school, they coordinates

490
01:30:34.540 --> 01:30:51.849
high aspiration for selected college. So, for example, this male student, who is now aiming for Coda University, the second top university in Japan. He mentioned that he, in his first year of High School. He was told that the if he doesn't have any school he's aiming for, you should aim for University of Tokyo.

491
01:30:53.250 --> 01:31:20.680
but he didn't do it because, like his friends, are all aiming for University Tokyo, so he wanted to make a difference but he's aiming for code of which is second top university, and according to the high school teacher, they mentioned that. Why, they are the why they kind of end college student to aim high. Because if you am high. That helps your carrier, and also that helps them to like overcome the limit. That's a kind of one of the school model.

492
01:31:22.580 --> 01:31:33.739
So as a result of those. high school. teachers, engagement! Many students have high aspiration for selected college, especially for men.

493
01:31:33.810 --> 01:31:49.839
and, as you can see, on the underlying sentence, he's aiming for now. Osaka University, like another top tier university in Japan. But in his first year he was aiming for university to Tokyo, because friends along him are aiming for the university to.

494
01:31:53.310 --> 01:32:07.130
Okay, I'm going to skip. But I just want to mention that the similar kind of more male-dominant narratives about aiming high without basic kind of goal and aim is also found in other selective high school in other regions.

495
01:32:07.460 --> 01:32:29.539
 so this is siren certainly reduce some sort of anxiety about the exam failure, because they are likely to fail the exam. If they are aiming for top tier. Selected National university. They have a strong belief that the Amy for this college this all of college helps their Future careers, I mean.

496
01:32:32.170 --> 01:32:43.780
Oh, okay. Oh, yeah. One day. Sorry I'm gonna skip that. Okay, so these are the male students kind of narratives, while female students. I found that

497
01:32:43.780 --> 01:33:13.499
first they tend to choose their college more based on what they want to study like in the school. So they they are relative, tend to be more detailed. And also many students talking about like female students talking about basic occupation they want to achieve in the future. So specifically like occupation license. So a couple of female students mentioned that one student she's aiming for more than a selective national university in Kantu areas.

498
01:33:13.510 --> 01:33:28.319
But the examination is no option. According to her account, it's because she is aiming for this college, because the the school provides vocational education, nursing education that's more practical, pragmatic rather than aiming for selectivity.

499
01:33:28.820 --> 01:33:39.890
They also prioritize selectivity, but also they also emphasize the specific occasional education that helps their future career. If they quit the job after chip wearing or something.

500
01:33:41.450 --> 01:33:43.260
So these are the 2

501
01:33:43.360 --> 01:34:09.089
models of emerging features I found based on my interviews. Men tend to be less clear about their future carrier pathways, but produce a strong belief that the school they will eventually attend will help their carriers. Why women do not really have that kind of aspiration, whereas they tend to have more grounded, active and pragmatic aspiration which could be concerned by their structural position in a gender unequal context.

502
01:34:09.440 --> 01:34:17.100
Last 3, those vocational program has increased indoors a higher education in Japan. So perhaps the

503
01:34:17.140 --> 01:34:29.119
like, those increase in private sectors that specifically target female students may at least sustain or exacerbate the gender segregation in higher education. That's my finding. Thanks so much.

504
01:34:37.760 --> 01:34:38.510
One.

505
01:34:42.070 --> 01:34:49.060
Thank you for introducing me to know more about Japan. But my 1 million dollar question

506
01:34:49.330 --> 01:34:50.559
is, what

507
01:34:50.600 --> 01:34:58.429
can I get away from this study? You use private sector as the key concept.

508
01:34:58.500 --> 01:35:02.790
To me, private sector is a mix of pad again.

509
01:35:03.060 --> 01:35:20.050
and depending on the context. If it is selective schools say in the Us. Is Yale, yeah, versus Harry Potter, different things. So they are following different logic. Yeah, certainly different proposals. So in the Japan case, if I look at

510
01:35:21.010 --> 01:35:27.770
the thing to take away would be, what about private sector that is

511
01:35:27.890 --> 01:35:53.429
enhancing what you came to be the gender segregation. Yeah, thank thank you for a question. Something I didn't mention created in this presentation for the sake of time is that there's also a hydrogen at within private sectors. So there are a sizeable number of very selective private university like, was it a Ko and a Sophia universities, though those are top tier kind of 3 school located in Tokyo.

512
01:35:53.680 --> 01:36:15.999
But it's also the case that the the increase of those private sectors is mostly contributed by new re-established, less selective private universities. So the heterogeneity has increased over time in terms of the selectivity within those private sectors, and the same logic can be applied to the Us. Context as well as you just mentioned. There are a lot of

513
01:36:16.000 --> 01:36:28.359
selected private sectors like Yale, Harvard, or Princeton, but actually for perfect colleges. that's private, that's for profit that's newly established has increased over 20 years.

514
01:36:29.130 --> 01:36:42.329
It oftentimes target some historically minority population who didn't access, who didn't have access to higher education like a minority population. So then, I think, like the same substantive

515
01:36:42.360 --> 01:36:49.660
findings are different. But theoretical implication could be speak to each other

516
01:36:50.050 --> 01:36:57.939
with minor true elaboration is selectivity in 2 different piers of private sectors.

517
01:36:58.460 --> 01:37:01.870
It's essential to pressing out your story.

518
01:37:01.890 --> 01:37:10.209
Who gets selected into it. Is it. The low scoring folks who tend to get into private sector right? Less selected? Right?

519
01:37:10.290 --> 01:37:13.760
Yeah.

520
01:37:14.530 --> 01:37:26.439
yes. So I specifically focus on students in selective high school. So then, they are not really going to the kind of open access private university which doesn't require almost any kind of exam.

521
01:37:26.440 --> 01:37:46.770
realisticary they are going to some selective private sectors if they fail, the National Insurance Exam. But still those universities tend to offer more occasional education that is more preferred by female students. So that that's kind of a something I found based on the interviews. But thanks for the question.

522
01:37:47.930 --> 01:37:49.550
there are questions.

523
01:37:50.830 --> 01:37:51.600
yeah.

524
01:37:53.470 --> 01:38:07.270
yeah, you have to come and speak

525
01:38:08.200 --> 01:38:09.530
so.

526
01:38:10.410 --> 01:38:14.849
I it's it's chicken or kind of problem.

527
01:38:15.030 --> 01:38:17.280
But so you study.

528
01:38:17.450 --> 01:38:26.870
you focus on privatization as a mechanism. That sort of is creating these differences in enrollment into selective universities.

529
01:38:26.910 --> 01:38:30.570
I'm wondering if that might just be a response

530
01:38:31.310 --> 01:38:35.549
to something that comes before in the sense that

531
01:38:36.670 --> 01:38:38.230
maybe

532
01:38:38.460 --> 01:38:56.199
from what you've described, like, the the women are taught not to focus on selectivity. And I imagine if you have only 20% female enrollment in place like University of Tokyo, where, if I heard correctly, they even in medical school, they actually lowered.

533
01:38:56.730 --> 01:39:02.069
Yeah, there was some like a admission scandal in the

534
01:39:02.830 --> 01:39:03.930
sort of like.

535
01:39:04.260 --> 01:39:15.489
not a nice environment for women to even aim to. So did you see something like that in the interviews? And could you imagine what, what, what do you mean by unparalleled kind of environments?

536
01:39:16.170 --> 01:39:38.450
It's not comfortable, I imagine, for a woman to go to the place which is so sort of patriarchal as university of you mean, like a selectivity selective university, like a national. Yeah. So, as I just show now, like only 20 of undergraduate students at the University of Tokyo women, and actually many female students in the top tier selected high School.

537
01:39:38.450 --> 01:39:50.769
In my interviews they told me that oh, because they don't want to nearly aim for University of Tokyo, because there are very few women that kind of stand out. So then they don't really have that kind of impression

538
01:39:50.830 --> 01:40:07.699
from like a female, especially female family members, if they told them like, Oh, I got into University of Tokyo, then friends or families, they kind of react by saying that. Oh, you are kind of genius. Congratulations that then they tend to do, not kind of accept that kind of

539
01:40:07.740 --> 01:40:12.509
do not really want to like those kind of perception.

540
01:40:12.690 --> 01:40:15.259
It's a kind of Bish your sacco cycle.

541
01:40:15.310 --> 01:40:34.939
it's as you mentioned, like a chicken egg problem. but at least. The the case I want to make is that a privatization? Some are at least sustain those gender segregation by specifically targeting the female population. But I take a point. Yeah.

542
01:40:35.230 --> 01:40:40.999
if you know when there's a sort of gender differences, it might be good to just go straight for it.

543
01:40:41.250 --> 01:40:47.300
The source of the problem which might be the gender inequality. Right? Right? Thank you.

544
01:40:49.580 --> 01:40:50.990
We have.

545
01:40:51.220 --> 01:40:54.110
Yeah, go ahead.

546
01:40:56.470 --> 01:41:03.130
I'm a I wonder whether he checked whether the profile of selective.

547
01:41:27.460 --> 01:41:34.800
There are a few of women in top tier universities, so it's not about competition from college measures, but it's also

548
01:41:36.460 --> 01:41:44.550
share women with indoors a field of study. But thanks, thanks for that. And actually like this, yeah.

549
01:41:45.940 --> 01:41:50.409
Louis-André VALLET:  yeah, thank you very much for

550
01:41:50.630 --> 01:42:20.279
Louis-André VALLET: thank you very much for your presentation. I I would just like to know to what extent this quite low share of femalees applying to to to to to be up a university, such as the University of Tokyo, the University of Kyoto, is, it? Is it considered, a problem in in Japan? By the by, these universities

551
01:42:20.280 --> 01:42:40.369
and all by the government. Or so, I'm not physically in Japan. Yeah, thank you for the question. I'm not physic or in Japan. Right now I'm in the Us. But actually, I think, if not, if I'm not mistaken. Actually, there are a little Japanese people here, so you can correct me if you want. I think like I, almost

552
01:42:40.370 --> 01:42:56.770
we Creole Atris Monastery. There's some like a news report. Problematizing the the show like the under-representation of women. either in stem and also select the college. So it's a kind of they got it as a huge social problem. But there's no. And actually the University of Tokyo is

553
01:42:56.830 --> 01:43:01.579
doing a lot of efforts to reduce the inbearance but luxury.

554
01:43:02.260 --> 01:43:09.080
the the female share has been stable over 15 years, so it's more a societal issue, I guess. Thank you.

555
01:43:09.920 --> 01:43:11.049
I'm a level of one.

556
01:43:11.320 --> 01:43:12.340
Okay, yeah.

557
01:43:12.790 --> 01:43:15.400
yeah, this is like what you like.

558
01:43:15.440 --> 01:43:24.859
I don't think I'm from Academia sneaker Taiwan. So I think I'd like to hear you more from your

559
01:43:24.889 --> 01:43:36.120
your explanation route, because I think there, I think there's and lots of it. It's a quite of interesting phenomenon. But I think there's a lot of

560
01:43:36.260 --> 01:43:40.269
explanation mechanism, like expectation or

561
01:43:40.330 --> 01:43:52.259
kind of suggestion from teachers or or another culture cultural culture things like, yeah, yeah. So what's your? I think

562
01:43:52.389 --> 01:43:54.529
I think I I want to

563
01:43:54.670 --> 01:44:10.480
hear more about your elaboration, about what kind of selection methane survey from institution or somewhere, I think, yeah. So I think I didn't have time to discuss in detail. But actually, there is a huge gender gap in aspiration for aiming high

564
01:44:10.549 --> 01:44:14.719
already happening at the entering the high school.

565
01:44:15.290 --> 01:44:38.449
So 40% of male students in the first year aiming for universal Tokyo in my sample, but actually only 20% also. So then there's a gender gap even prior to entering the high school. So that means that maybe primaries, maybe having different kind of preferences for men and women going to different kind of universities. But my argument is that a high school that also maintains those kind of gender?

566
01:44:38.510 --> 01:44:48.080
segregation. But I I sorry I didn't have time to discuss that. But yeah, there, there are a couple of explanation as as you said, yeah. thank you very much.

567
01:44:51.570 --> 01:45:03.319
Finally, I would like to call your attention that there are 2 distributed papers in this session. Unfortunately, we didn't have time to to ask them to present. But

568
01:45:03.430 --> 01:45:17.739
let me read out the the 2 distributed papers. One is careers of female early stage researchers with childcare responsibility in the COVID-19 pandemic.

569
01:45:18.410 --> 01:45:25.409
The second paper is Career plans of sociology, students in Turkey after pandemic.

570
01:45:25.500 --> 01:45:35.140
And I understand that the author, Malika, is online. Would you like to say, are you? You know words about your paper?

571
01:45:36.230 --> 01:45:52.189
Melike Akbıyık: I. I uploaded my papers in the

572
01:45:53.139 --> 01:46:03.389
okay. Sorry to put you on the spot without any notice. But there are these 2 papers. So if you are interested in, please contact the authors directly.

573
01:46:03.760 --> 01:46:14.389
Okay. So I think this is the end of the session, and I thank organizers, presenters, and also the audience for taking part in this session. Thank you.