WEBVTT

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 looking at

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the second mortality, what I want to call the second mortality transition and the extension of the human lifespan. Basically what I want to do

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the mic on.

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Yeah.

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Okay, okay. What I want to do is, look at what happens to mortality in later life, and what has been happening in particularly

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in particular, over the last 50 years. when strange things have been happening.

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if you look at mortality in the twentieth century.

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This is a group of about 16 countries with data complete data. Since 19, since after the First World War we can see that

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infant mortality has gone down dramatically. Young age. Mortality has also gone down nicely. Of course. Second World War was a bit of a bump.

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Mid-age mortality has gone down.

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and old age mortality basically stayed stable has gone down slightly in the last

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50 years, but again but very slightly, and the same thing

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is true for women. Again.

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rapid decline in infant mortality.

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good decline in young young adult mortality with a hump in the Second World War.

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mid age, mortality, and

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old age, mortality gone down very slightly.

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using since. So this is 16 countries with full data consistently higher male than female mortality. dramatic declines at younger ages and not much at all ages.

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So what I want to do is look at a long series of life tables to examine mortality at later ages. We're talking about 45 countries from 1816, June 2020.

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Most, of course, most are in the twentieth and 20 first century.

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and looking basically at changes in later life with a multi-level model which uses gear and country

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as random as random levels, in order to see how the weight of changing the rate

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of mortality increased. Changes over time.

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 come on

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the random effects. Models enables us to see things you might not otherwise see. Just a second. I seem to have

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let them do the thing.

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The

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something's gone wrong here.

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Sorry.

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If we take a simple OS model

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we can fit a straight line to the points. But if we use a multi-level model, we can see the effects of different groups and

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separate out the general trend

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from the individual grouping effects. So you have a general model of B one plus b 0 plus b one x plus the error. And the idea is that we split up the error.

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break down the air into 2 components.

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group membership, error and individual. And in general, one looks at the size of the group area. But one doesn't actually get into the details.

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And what I want to do is actually look at

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the information in their group variations in particular, for a year.

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The general shape of the mortality curb leads little introduction decline, minimum increase.

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and then

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a straight line increased from age around 4,550. We have a gompertz, which is a log, linear, straight line.

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And we can see that if we look at the Netherlands, we have, this thing repeats itself

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and all levels of mortality, the basic shape remain just its variations in the

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significance of the different effects.

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What's important is that at all ages, to all levels of mortality, we have this log linear

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button

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in older ages.

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So

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 over time, as we saw, mortality has been declining young a faster at younger than to older ages. But we want to ask what else is happening over time

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and

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using, like everybody else. H. And D. Data. 8,410 life tables.

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800 410 life tables

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for 45 countries, over 205 years. Males and females.

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Number of countries increases over time. As we can see, the concentration is in the late twentieth and early 20 first century, and again, the multi-level model should

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pretty much control for this misrepresentation for this non-random representation.

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So the model we have is

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the gompertz model X.

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Eb to eggs tag me start at age. At age 50, a set age 50 is 0.

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My age 50.5 actually is 0

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to create a a linear model

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with random effects for year and random effects for country again controlled by sex.

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and our first hypothesis is that the effects will decline over time, and the female decline will be faster than male decline.

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And this is the model. I won't go into all the all the details.

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I have a nick of 15 min.

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The important thing is, if we look at the random effects for year. We can see that there

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declining slightly

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till around 19 to the mid twentieth century.

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and then around the Second World War, they start declining quite fast, and female decline is faster than male decline.

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This is the null model. And this is the linear model, basically exactly the same.

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So we can see that, as we expect. mortality is declining.

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but it is be declining faster for females than promotes.

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But of course we haven't taken into account here. The

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level of mortality in younger ages.

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So, as mortality go down, goes down. Of course the weight goes down at age 50 the way and the decline after age 50 is going to reflect what happened also before age 50.

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So let's control for general mortality.

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and we measured general mortality by L. 50, the proportion surviving to age 50, which effectively is an indicator variable

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for life expectancy. They are almost perfectly correlated.

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except that, of course, elfits. He does not take, is not dependent on what happens after age 50, which is what we're looking at.

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And so we're going to have a third hypothesis.

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Only we're not sure what's going to happen? There are 2 possibilities.

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Either the lifespan is fixed on once everybody has to died by a certain age.

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in which case old age mortality must increase over time. because

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mortality, young ages is going down, and you've got to get to maximum mortality by age 100 or so you've got to get to the final. You've got to get to the point where everybody is going to die.

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The alternative is

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that as mortality is going down, the lifetime is actually extending is actually extending.

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in which case you're going to have a slightly lower mortality at the top ages, and the rate of aging

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the rate at which the mortality curve increases is going to

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be attenuated a little bit.

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So let's see what actually happens. Of course.

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mortality at age 50,

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M. 50 is very closely related to survivorship, to age 50,

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and this is again the model, and I won't go into the details here. But then of what happened to the random effects

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till about 1850 or so.

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Very few life tables, anyway, very few countries

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and not much pattern. We can see there

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from the mid nineteenth century.

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Up to around 1,970 or so.

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there's an increase in the level or in the rate of mortality, or rather the level of old age, mortality, net of young age, mortality.

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no

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slight increase

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in the level of mortality.

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But then, around 1,970. Something strange happens a bit earlier for women than for men.

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The rate of mortality

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begins to go down a little bit. This is mortality at older ages.

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So the level of mortality is actually going that net of the given level of young age mortality. There is actually a slight decrease.

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the level of old age mortality.

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In other words, the rate at which old age mortality is going is rising

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is actually being held back. being held back a bit more for every year we go forward.

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So, in other words, before, if we control for mortality and lower ages before the mid nineteenth century, as I said, there's no substantial trend, but very little data, anyway.

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From the mid nineteenth, late nineteenth and twentieth century

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old age, mortality, and the weight of aging actually increasing relative to mortality at younger ages.

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But since the later twentieth century, about 1,970 and 1970, s. Important, because this basically is the end of the 1960 S. Crisis in mortality, when everybody thought the mortality has leveled out and nothing was going to happen.

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Old age, mortality, and the rate of aging begin to decline again relative to mortality at younger ages.

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So my interpretation is that between 1850 and 1970, as mortality was going down

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the lifespan was effectively fixed.

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As the mortality declined. At younger ages it was rising faster at older ages, in order

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to catch up in order to make sure

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that everybody goes by the right age.

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since around 1,970 there's been a relative decrease in over ages as the age of a supermortality is being pushed back.

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and therefore the rate of which mortality increases. Not so fast. It's been slowing down a little bit. Again, we have to remember

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these graphs. This is these are

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variation. As long as the sum of all these points is 0. So it's not that it's actually going up or going down. It's going up or down relative to what is happening in other years.

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so we consider this examining the random effects, not just the variation

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by year, but the actual content of

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the effects enables us to see patterns we may not otherwise have seen, but

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and we can see that with time as level 2 variable old age. Mortality declined over time, and female mortality declined faster. But then, when we take into account

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the level of young age mortality. We can see the net of that old age. Mortality increased

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for about a century bit more

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as the deaths were pushed back, but Lifespan remained fairly constant.

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But since the mid 1970 S.

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There's been a switch in old age, mortality has begun to decline faster.

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so we can see that what I'm arguing is that random effects, not just error terms. They contain important information.

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If you want. If you want good science, you have to have sound hypotheses and keep your eyes open.

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and serendipitous findings are important, but we need to confirm them when I'm just presenting

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a first glance.

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Mortality biographers have that we've done a lot about the first, the the the mortality transition.

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What I'm suggesting is actually true. Mortality transitions one since the mid nineteenth to the later twentieth century

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in which the lifespan was effectively fixed.

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And since the late twentieth century, which since when there's been a possible, it's a possible extension of the lifespan, as all mortality is no longer rising so fast relative to younger age mortality.

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So thank you very much.

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The possibility to relate this to studies of

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one could do essentially the same thing with disability for a free lifespan. And again, this gets into the whole question of, are we talking about a compression of mortality or compression of mobility.

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The technique is

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essentially the same. One could do exactly the same thing for disability, for this healthy lack, for healthy, for a healthy lifetime.

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The of these is

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no, this database is only mortality. H. And D doesn't have.

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And the the problem is, I think, finding

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come good, comparable data across a lot of countries and a lot of years for healthy life life expectancy. And I'm not sure that's really there.

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From the second.

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Oh.

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specifically how to transition both

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people's age.

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Will you be trying to people after many days. this group

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again, where does cohort?

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Yeah, there's a very clear

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pattern over about 50 years now since 1,970. This is more than one goal.

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So yes, you're right. It could be a cold water fact. People

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born

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after the First World War. people who went through the Second World War.

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I don't know.

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I can just present what we have

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is

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period data. There's a lot of

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my personal feeling, is, there's a lot of problems with cohort, basically because you're measuring savings with people leaving and people joining. You are never quite sure what your cohort is.

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Yes, obviously.

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history plays a part in biography plays a part here, and we

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but at what point? There's period this cohort and the period begin

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because everybody alive in the 1960 S. And 70 S. A lot of them have been to the Second World War.

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born after the Second World War. And

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this is part of part of the period effect is the historical record obviously.

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thank you very much.

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thank you

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 so there's one person online.

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Okay, thank you very much for coming. My name is Adam. Turn from Hong Kong So today's presentation is about fertility patents in the contest of political polarizations. And in times of political transition into offering terrorism.

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so just give you a little bit background about Hong Kong. so fertilizer weight has been well known in East Asia that you started low. So the Hong Kong, for example, the total fertility with last me is only 0 point 7 6, and in Singapore and in Taiwan is also very close to one. So The fertility rate is very low. So it has a lot of social and economic implications because of population aging.

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So the factors are explored in the past in the past include a wide range of factors, a culture of an individualism, work, family conflict, gender, inequality, etc. Etc. But

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other than this socioeconomic factors that is related to a low fertility weight. Not many studies have pay attention to a political factors, especially in East Asia. What we have some studies talking about the political factors of fertility. Maybe in a society that is a very unstable with civil war or other developing countries, but in developed countries with very advanced economies, it seems. we don't have a lot of studies on that.

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So

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and other than that we have some aggregate level studies outside Asia find the political freedom and democratic values are related to sort of accelerate, but not really on the individual level, on how people with different political values may have different fertility patterns.

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So in Hong Kong the to do fertility wage is a consistently close to or below one. Since 2 2,019. That's a 19 is a year of Hong Kong. That is a politically unstable because of the broadcast

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in the past. a lot of studies have find that a long work hour, gender inequality at home, or lack of family support policy are responsible for the low fertility rate.

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However, this political situation is not discussed at all in all this literature about a fertility in Hong Kong. So I just give you a very brief overview about our political situation in Hong Kong. So Hong Kong is a special administrative region, a city in China. It has a very strong executive branch, with very limited control from the legislature.

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it has low universal suffrage for election of the head of government since. The handover of sovereignty from Uk to China.

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So I'll some studies like at the Economist, considered Hong Kong as a hybrid between well, which means that we have restricted political, right, limited political probabilism and unelected Catholic body.

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major political. Ca, but since the hand over because of this hybrid regime, a lot of our political campaign has been carried since 2,000 for example, there was a umbrella movement or occupying central movement in 2,014, and we had some opposition parties, and which received majority support in elections.

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however, because of the political system, that even though they get the majority of the vote, they get minority of the seat in the legislature. So we have. I'll Over the years of the political campaign we have more and more polarization, but we are very politically divided on the pro reform pole Democratic camp and the pro government can.

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So there was a a big political protest in 2,019 which is called the Anti Extradition more Amendment Bill movement. So the thing is that it's a city wide protest. It's a very big scale large scale protest, and at the end I turned into very violence conflict between the protesters and the police, and it was end in 2,020 because of

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the covid, as well as the establishment of some alleged laws. Concerning about the national securities.

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So yeah, we sounded in now a new major wave of M. Equation, since lighting. It is a lot of people who are very disappointed by the political situation in Hong Kong try to move out. So there was a politic, politically, emigrations for supporters of ported for democratic camps.

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So my question is.

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how are people's fertility preference associated with their political values and preference. In in this contest of dramatic Political change! And how are the increasing political polarization, the hatred of political out groups are related to the the the fertility pattern.

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So

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In the past there were a few studies related to how political identities and values of fat. fertility, intentions, and outcome. So, for example, studies In the past find that individuals who identify as political conservative tend to have more children than those with moderate or liberal political views.

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and the election of trump in 2,016 had a significant impact on fertilizer weight in Republican leaning counties with any increased infertility relative to democratic leaning counties. So people are who are politically

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it's satisfying. They tend not to have as much student as the other groups, and trust in political institution also lead to higher fertility. Intention.

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So the prediction is that people who hold democratic values in Hong Kong may be for fuel to them, because now that the the reform are killed by by the the lesson, the security, and also they have every dissatisfying, so they may have.

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And Another set of literature is, talk about the effective polarization. So how people hate the political outcome. So whether you hates your political opponent. So There was some literature on mass polarization in the Western contest, and mostly focused on the between group conflict

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mit Ctl. And and we find that there we are in using intolerance of out work, and when you have increasing intolerance, you have a lower sense of belonging. We have lack of feelings about the society and people may perceive the society in a more like a way, when you hate the output, because you, you find that the group is not really in solidarity 250.

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So the protection here is that people who hate members of political outlook very much preferred to them, because you don't see a future for the children, you feel that other children will be enough conflict with someone else, and people embracing democratic values are more prone to leave and have favorite children, especially when they hate the members of particular because they don't like the place anymore.

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So

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the So this, this studies want to further to talk about the individual level link between political attitude and fertility. So they have different possibilities. One is that with low effect. maybe you know, as it's because the existing stuff, they never talk about the political effect on fertility. So maybe we can assume that there is low event, or there will be an independent events. When you support democracy. You may have favorite children.

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and you can also have a hypothesis about the interaction you've. That is that when you support democracy you may be preferred to that, especially your hate, the pro government came. Okay. So so when you hate political output, and your political parties are not, you know, in in in the mainstream of the political system you may feel even more dissatisfying. And have you with children. So the data is collected in Hong Kong is from a house of survey collected in

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2,000 21. And I you to use our percentage sampling. eligible respondents are married to Chinese couples. at the end we have 1,586 men and women from 793 married couples. The response rate is about 64%.

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So I mentioned political attitudes. So the attitudes where where did they support the democracy, and like well, social harmony is more important than protecting him, and right government needs to always be strong and not making compromises. government cannot be have any achievement if you've often checked by the Legislative Council things like that. So it's about the respect for diversity or the preference of a strong government without chat.

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So this is the one of the many independent variables, the scale and another verbal is about effective polarization. So I use feeling barometer, so I ask them to wait their different political groups, and I take the standard deviation between different Their feelings on different political groups as the larger than all that, the higher they hate each other.

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So. The dependent, variable is the fertility. preference. So how many children they think is suitable in this. social environment. So what how many children do they want under this? Considering the social environment and I control our respondents and their spouse, age, education, and employment status. I also controlled for household lock, income, apartment, size, and number of lawn at the children.

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So I use a random intercept linear regression model because the the responders are from couple level. So we have men and women from the same couple. So I use the long format. So you can imagine we have 1,500 something adults

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clustered in 700 something couple. So I use the random intercept models to to take pen to to consider the the Intro class correlations in the less the data structure. So I took 2 models. One models is that I take the mini- that model. How the democrat, the attitude to democracy and effective polarization affects fertility independently, and then I also have an interaction event model.

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So this is the result. The result here is that respondents political attitudes is lackative, that so the larger the school is more support, you support democracy. So if the coefficient is negative, so it means that the more support you towards democracy, the fewer children you prefer.

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So Your own out means respond respond to this political attitude is significant to be correlated with fertility, fertility, preference, but spouse political attitude is not related to your own

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fertility preference.

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on the other hand, effective polarization independently has low role to play in strict pain, the fertility intention. So, no matter how much you hate political output, it doesn't matter in the independent models. However, if you look at the interaction effect models.

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the the interaction between the politic attitudes and effective polarizations

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significant. And it's negative, which means that

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on average, if you are more supportive to democracy, you have favorite children, you want to have failure to them, and especially if you really really hate political output, and you support democracy, which means that you hate the government, the case, the government parties

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for this group of people. They even have fewer children. So if you support democracy, but you do not really hate public output. You are, you are. You're fine. So this is the This is the interaction effect.

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So this is the effect size of political attitudes

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and at different level of effective polarizations. So what you see here is that it's on the left side. when you is the means minus 2 standard deviation, it means that you do not really hate political work. So basically, the standard deviations of the feeling parameter is very low.

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when you do the hypothetical output, it doesn't matter. Your your political attitude is not correlated significantly correlated with fertility preference. But when you're on the mean, therefore, or you from higher. So when you start to hate political out groups, when the standard deviations of the feeling bar is large. What you find is that what we find is that the political attitude is significantly larger and more negative.

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So this is the number of children they expect

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given different combinations of effective polarizations and fertility preference.

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So basically is, it's basically repeating what I just said. So you've looked at the the, the, the, the line which is so basically, it just means that if you really hate perfect output and your public attitude will respond to a fatal preference in a more dramatic matter. But if you do not hate to outgroups the, the correlation is basically more more flat.

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So the conclusion is that. How does this studies inform us of the of the phenomenon of political driven fertility? The extreme leaf low, total fertility rate of silence. 76. After 2,019 is not likely simply a result of covid lighting is also partly related to the authoritarian turn. After the 2,019 protest

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which has an impact on the fertility preference.

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So the port, as a little evidence of the impact of spouse attitudes on on responders for ticket. The preference, however, remember, the statistic outcome is a joint outcome of fertility preference of all right, so it affects it in in directly. So the the last census The policy implication is that we have talked about a lot of family policies in the past, but family policy may not be that effective in who is in politically driven

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total fertility weight. So when you have a society that the to the fertility which is low, partly because of the perfect situation. You cannot totally rely on family policies is something.

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and that's it. Thank you very much.

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Control just for women, because men not want to, even if they are consulting look for spouses.

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they are still the ones who are only making the decisions.

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So it may not be so much in

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political situation, even though I know Hong Kong had a lot of problems.

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one of them to not purchase.

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But I think that low fertility rate may have more to do with women

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working outside the home and getting college education, or a higher education than it has to do with the competence of our country, because I think in the early one that I thought this a lot of it.

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But fertility rate is going down all over the world. Okay, even if China's one-child privacy, we should get rid of it. A resilient rate is still involved. There's 2 billion. It's also a long-term in the in one. So

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there's more women getting an education

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economic situation in the country. That may be the ones in what we told you. Now, even if the economy gets good.

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I think we're still going to see? No. the okay

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asking them how many children, one and many times they say they don't what happened. And and so what we're seeing

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it may not be

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as far as and on the stages, but they're right, but just being, I think, if you might, or females against sales, your attitude maybe a little.

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but I'm no right in a sense that for some women's cash, Asian, and employment in all of responsible for the longest out there, it's a working. But consider acting to a trend in 2,019. We have but but even more than a long, because in the past 10 years maybe the the 2 degrees around one or one from one of them. Now, we're still not sure.

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So the the education of women and economists that this agreement doesn't really change dramatically after you know, since 19. So why is it going to be the moment that a long mode? But there is a way of around

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reason is called the code, it can right, but I suspect that it's not only broken. So so this is only part of the reason for the very, very low. But there's a way it's not the you saw. So I want the school team to just talk about

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it.

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Yeah, yeah.

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Just found a very brief comment, coming from a country with a fertility of 3 children per woman, and still considered a developed country. I think we need to distinguish very clearly between individual effects.

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such as education and work, which create variation around the local mean of a local average.

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And the specific, should we call it contextual ecological political effects which may

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push up

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fertility or push down fertility. And I would suggest also in Hong Kong one needs to distinguish between the effects of possibly interactive effects of the local situation

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from the individual effects of educational work.

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This is a with Us

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are you with us, Chris

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no

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JESÚS GARCÍA GÓMEZ:  you've been with us before. Video. I think you can hear me now. Yes, we can hear you. And you can start.

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JESÚS GARCÍA GÓMEZ: Okay.

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JESÚS GARCÍA GÓMEZ: So good morning. I I am connecting from Spain, so

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JESÚS GARCÍA GÓMEZ: I think he's

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JESÚS GARCÍA GÓMEZ: almost 10,000 or miles, or 16,000 kilometers away.

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JESÚS GARCÍA GÓMEZ: I would love to be there with you, but unfortunately I couldn't make it to Australia this time. So instead of

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JESÚS GARCÍA GÓMEZ: presenting this this, the paper with detail and and stuff, I'm just trying to be as quickly with this presentation as quick with the presentation as possible. So you have more time to discuss the presentation of people who

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JESÚS GARCÍA GÓMEZ: travel to Australia.

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JESÚS GARCÍA GÓMEZ: In in this case it's a paper that I I wrote in conjunction with Albert Tollre, who, who is another research at the University of Salamander in Spain.

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JESÚS GARCÍA GÓMEZ: And we have this line of research

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JESÚS GARCÍA GÓMEZ: that

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JESÚS GARCÍA GÓMEZ: consists on a studying fertility of immigrants in Spain. And specifically, we are for trying to focus on the fertility of immigrant descendants on second generation, immigrants on 1 point generation in 1.5 generation immigrants in Spain. The Spain

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JESÚS GARCÍA GÓMEZ: during the twentieth century was not an immigration country in in the world. But during the first decade of the 20 first century it was.

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JESÚS GARCÍA GÓMEZ: I think, just the third country you, in the first decade of the 20 first century by number of immigrants

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JESÚS GARCÍA GÓMEZ: only behind the us, and I think that I

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JESÚS GARCÍA GÓMEZ: I mean at least 10 country. So, considering the size of a pain which nowadays it's around 48 million people. We're talking that in just

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JESÚS GARCÍA GÓMEZ: 10 years, between 1,998 and 2,000, and the Spain received

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JESÚS GARCÍA GÓMEZ: around 10 million immigrants, and the population increased by almost 6 million in just in terms of immigration and immigration balance. So nowadays with data that are coming up with the new sensors and with the new register of data.

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JESÚS GARCÍA GÓMEZ: we are starting to be able to study the fertility of the second generation of these immigrants who came to Spain mainly from Latin American countries, microbian countries.

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JESÚS GARCÍA GÓMEZ: and over West, another Eastern European countries to Spain. Spain is also a country with very low fertility, although not as low as in the case of Hong Kong Thing. Now they see that it's around 1.2 2

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JESÚS GARCÍA GÓMEZ: children per woman.

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JESÚS GARCÍA GÓMEZ: and

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JESÚS GARCÍA GÓMEZ: in in the remaining of my presentation I'm going to be talking about the completed fertility of second generation Latin American immigrants in Spain.

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JESÚS GARCÍA GÓMEZ: They were seen as a group who had the potential to

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JESÚS GARCÍA GÓMEZ: to. We elevate the total fertility

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JESÚS GARCÍA GÓMEZ: they for to put a stop to the declining population in Spain. But

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JESÚS GARCÍA GÓMEZ: the results that as work, when I see are that this generation of immigrants are not gonna

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JESÚS GARCÍA GÓMEZ: continue with the higher fertility that we saw that we started seeing a decade ago on this first generation of immigrants. The in this case.

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JESÚS GARCÍA GÓMEZ: in these graphs.

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JESÚS GARCÍA GÓMEZ: in modern one we are only controlling for.

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JESÚS GARCÍA GÓMEZ: and we are campaigning. The total fertility.

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JESÚS GARCÍA GÓMEZ: or the total number of children, had by age 45, and for Latin American immigrants of these 3 different generations, compared to not, if it native a Spanish women.

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JESÚS GARCÍA GÓMEZ: In the second model we are controlling for variables, such as

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JESÚS GARCÍA GÓMEZ: level of education, labor, market participation, and some other common variables that are found in census data.

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JESÚS GARCÍA GÓMEZ: and the result is very clear.

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JESÚS GARCÍA GÓMEZ: We can see how. while first generation immigrants. they had a higher completed for 3 t. Compared to native, he Spanish women. When we go to the ascendants of this Latin American immigrants.

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JESÚS GARCÍA GÓMEZ: we can see how those who are finishing the less children, on average when compared to native Spanish women.

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JESÚS GARCÍA GÓMEZ: We went a little bit farther with this

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JESÚS GARCÍA GÓMEZ: research, and we try to see if. when we desegregate the category of Latin American immigrants. Among

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JESÚS GARCÍA GÓMEZ: almost 20 countries in Latin America we can see the same pattern of we, or if we observe differences among countries, and to some extent we kind of serve the same pattern, but we also serve out of

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JESÚS GARCÍA GÓMEZ: for a very large. different, very large differences between categories. So what we try to do was to explain

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JESÚS GARCÍA GÓMEZ: or to. We try to use variables. To explain the differences that we have served in between countries

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JESÚS GARCÍA GÓMEZ: and the of the origin. Country

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JESÚS GARCÍA GÓMEZ: was a variable that explained almost all of it, all of it, all of this viability.

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JESÚS GARCÍA GÓMEZ: In these graphs we subdivided each of these 3, Me run generations

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JESÚS GARCÍA GÓMEZ: by the total fertility rate is specific to the origin country, and we can see how, when we look at first generation, immigrants only those who originated

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JESÚS GARCÍA GÓMEZ: from countries in Latin America, with a total for it right that was higher than 5,

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JESÚS GARCÍA GÓMEZ: had a completed fertility in Spain that was much higher than that of native Spanish women.

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JESÚS GARCÍA GÓMEZ: and in the case of immigrant descendants, in both generations we have that

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JESÚS GARCÍA GÓMEZ: all, regardless of the total of their origin, country, they level of activities very close to that of a Spanish women.

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JESÚS GARCÍA GÓMEZ: And it's even height, and it's even lower these

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JESÚS GARCÍA GÓMEZ: a line. This dotted line represents a 10% variation. So

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JESÚS GARCÍA GÓMEZ: if

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JESÚS GARCÍA GÓMEZ: politicians and people and commentators in that pain, we're very excited with this. Immigrants coming from higher 50 countries compared to Spain in the first decade of the 20 first century, we can see how the effect was just temporary, because the the standards of this immigrants they are already having lower.

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JESÚS GARCÍA GÓMEZ: Then the Spanish women. At least, when we look at this second generation immigrants, we can see how they have even lower 13.

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JESÚS GARCÍA GÓMEZ: And

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JESÚS GARCÍA GÓMEZ: for the last minute of this presentation. I just wanted to introduce another paper on this similar topic that we just happened to publish.

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JESÚS GARCÍA GÓMEZ: I think, a month ago or 2 months ago, and in this case we were looking at every cell wearing of Emir and women and their descendants in Spain. We were using the very same data set.

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JESÚS GARCÍA GÓMEZ: and we were studying just aly fertility, and we were comparing migrants, which is another important immigrant group in Spain

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JESÚS GARCÍA GÓMEZ: to Latin American. So for now

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JESÚS GARCÍA GÓMEZ: I would like to finish the presentation here. and I would like to encourage you to contact me in this email address. If you have any questions, and specifically, if you have

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JESÚS GARCÍA GÓMEZ: any interest on this topics, on the fertility of immigrants as a whole.

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JESÚS GARCÍA GÓMEZ: and we and if anybody is willing to try to develop a comparative paper where we can study Spain and compare what's going on in Spain. What with what's going on in another different country or a group of countries. So thank you very much for for your time for inviting me to present this paper on the conference, and I hope you enjoy your time in Australia. Thank you very much.

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Thank you. He can you hear us properly?

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We take one questions from the from the audience.

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if there are any.

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Oh, yeah.

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yeah, sure you said that that second generation immigrants have the low fertility, and then that native Spanish Spanish women.

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But at the start of your presentation you said that it's 1.22 in. In. In Spain. I didn't sort of get that combination. In my own country, Norway. We find the second generation. Immigrants have a fertility lower than the parents, but still higher than the native nations. So if you can elaborate a little bit on that.

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JESÚS GARCÍA GÓMEZ: okay, so

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JESÚS GARCÍA GÓMEZ: I think that I don't think if I have understood very well the question or the first part of your comment. But The thing is that in a Spain that the total rate is around 1.3.

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JESÚS GARCÍA GÓMEZ: And when we have the results that they have presented are not for total for T. Rates, but for completed fertility.

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JESÚS GARCÍA GÓMEZ: So in the case of a Spanish women, if you look at

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JESÚS GARCÍA GÓMEZ: carbon sensors data, you you see that women who are finishing the reproductive period are having around 1.7 children.

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Okay, that that, and then the study. Thank you.

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JESÚS GARCÍA GÓMEZ: And I. I I don't know if that was the the point that you were trying to make. But.

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JESÚS GARCÍA GÓMEZ: thank you very much for for your call.

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You you clarify it. It was particularly at the end of the of the get it?

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Okay, thank you very much. Have a good day

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and now, we have a good

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isn't it well.

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 I'm not sure where it's not studying.

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Do you want to go on to the fourth speaker, while I get support

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there's been problems with the pre-recorded in the other rooms

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yesterday. It worked wonderfully. Okay. So we go on.

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And our contact text.

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she should be online, shouldn't she?

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 We don't have a

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the only half heads in someone is, we only have the previous state of mind, you know. Announce that.

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 Okay.

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we go for on that.

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Okay.

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even more time

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I'll contact tech support about young

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good morning, friends.

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My paper deals with the social structure and status of girl child in the Rural Tamiladu, India.

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with the special reference to implication for population change.

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your phone is to be touched.

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But next to your 4 data.

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okay.

355
00:51:16.840 --> 00:51:19.930
yeah. See, the content of

356
00:51:20.420 --> 00:51:23.290
the pepper deals with the prelude.

357
00:51:24.750 --> 00:51:28.299
with your focus on social structure and its elements.

358
00:51:29.570 --> 00:51:41.530
family, marriage. caste, religion. gender values and norms it. and finally. gender inequality.

359
00:51:44.120 --> 00:51:50.120
The second part of this proper deals with the discriminations faced by real child

360
00:51:51.250 --> 00:51:55.820
on the third part deals with the specific problems of guilt. Sign.

361
00:51:56.010 --> 00:52:00.560
Fourth, one is the castas of female infanticide.

362
00:52:00.810 --> 00:52:05.759
and the fifth deals with the status of status and the role of her child.

363
00:52:07.180 --> 00:52:11.219
and a methodology adapter in this investigation.

364
00:52:13.080 --> 00:52:17.190
The next is analysis with reference to the theoretical

365
00:52:17.260 --> 00:52:18.440
aspects.

366
00:52:20.930 --> 00:52:22.700
then application of the

367
00:52:23.250 --> 00:52:26.539
implications for population change at conclusion.

368
00:52:26.630 --> 00:52:33.920
These are the summary of this, but Indian social structure is marked by inequality

369
00:52:35.090 --> 00:52:41.319
and the inequality with reference to cost cost. In the sentence

370
00:52:42.480 --> 00:52:46.540
there is the system of social stratification in which

371
00:52:47.690 --> 00:52:54.379
the social segments are placed in terms of a Brahmin, Chatriyavasia, Sudra.

372
00:52:55.350 --> 00:52:58.039
based upon their birth.

373
00:52:58.110 --> 00:53:02.970
It is believed that that drama give the creation

374
00:53:03.370 --> 00:53:08.780
those who, born from her at the top, that is, Brahmins

375
00:53:09.340 --> 00:53:13.340
and those who won from the soldier chatrias

376
00:53:13.650 --> 00:53:21.380
involved in the defensive, while the province involved in the priestly activities

377
00:53:22.710 --> 00:53:29.459
on the third Vcrs inward in commercial activities born from the type part of dot.

378
00:53:30.340 --> 00:53:33.119
Finally, the bottom part.

379
00:53:33.330 --> 00:53:37.320
where is the protein? Those who burn from the foot

380
00:53:37.450 --> 00:53:39.709
part of that.

381
00:53:39.770 --> 00:53:43.529
and accordingly they involved in the menial

382
00:53:43.770 --> 00:53:49.100
and the service activities to the remaining Upper 3 Arena people.

383
00:53:51.320 --> 00:53:55.750
Therefore. here the costs

384
00:53:56.440 --> 00:53:58.740
religion which

385
00:53:59.660 --> 00:54:01.200
Euler Jesus

386
00:54:01.400 --> 00:54:03.470
set in, believes.

387
00:54:03.980 --> 00:54:04.920
creates

388
00:54:05.090 --> 00:54:06.799
social practices.

389
00:54:08.460 --> 00:54:13.329
and when this is interpreted from the point of view of religion.

390
00:54:14.720 --> 00:54:21.520
the gender is very much affected, because there is differential role of a

391
00:54:22.020 --> 00:54:27.009
men women, while men are the breadwinners and women

392
00:54:27.420 --> 00:54:30.089
to care after the household needs.

393
00:54:31.230 --> 00:54:41.510
Therefore, women were mostly confined in household, and men were the as breadwinners were involved in outside activities.

394
00:54:43.460 --> 00:54:49.589
Therefore women must never be independent, is viewed solely as the mother and wife.

395
00:54:49.670 --> 00:54:52.209
and these roles are idealized.

396
00:54:53.910 --> 00:54:58.530
The ideal life is faithful and uncomplaining.

397
00:54:58.540 --> 00:55:09.790
and her which you rise in services she renders to the husband practices like giving away of girls in marriage and importance attached to sons

398
00:55:10.150 --> 00:55:19.960
for maintaining continuity of line have strengthened the patriarchal social structure of Hinduism, which is the major religion. India.

399
00:55:21.430 --> 00:55:25.180
Now this is to be linked to with the religion.

400
00:55:27.140 --> 00:55:30.040
Social structure is a patriarchal

401
00:55:30.410 --> 00:55:33.010
Betty Lionel and Patty Law.

402
00:55:33.310 --> 00:55:36.339
Again, it affects the women.

403
00:55:37.200 --> 00:55:48.689
Women never be independent and always dependent before marriage, parents after marriage. Husband after the death of husband sons.

404
00:55:48.880 --> 00:55:59.069
So that type of yeah, dependency syndrome affects very much the status of women, more particularly the child. Daring practice of girl children.

405
00:56:01.130 --> 00:56:11.609
So religion makes the husband the family head there, and demands obedience and service from the Indian family system is Karaks by patriarchy, male authority.

406
00:56:12.470 --> 00:56:25.930
patriarchy of the establishment of practice, of male dominance over women and the children, is a historical process formed by men and women with the patriarch of family serving as the basic unit of organization.

407
00:56:28.330 --> 00:56:44.879
These labs are generated processes and practices especially referred to social, cultural, political, institutional forms of domination under oppression of women. therefore the social structure is implicated with the reference to how it affects it. Women

408
00:56:46.890 --> 00:56:53.819
women generally lead, restrict their lives, and usually play only a secondary role in decision making.

409
00:56:54.520 --> 00:57:06.399
She is expected to back up but the early morning, and goes to sleep late in the night and eat whatever remains out, or others have eaten, and not to complain on anything to anyone else.

410
00:57:07.310 --> 00:57:22.109
As a social success is marked by inequality inherent in it. Women are considered to perform such a restricted roles, and the perform within the cultural confines and other compulsion. Invariably these have implications for social status.

411
00:57:26.440 --> 00:57:28.400
So what are all the discriminations

412
00:57:28.420 --> 00:57:32.079
faced by women in general, and

413
00:57:32.230 --> 00:57:34.470
where children in particular

414
00:57:35.100 --> 00:57:43.769
see, women are considered as a certain because of her dependency, identity must say a liability.

415
00:57:45.070 --> 00:57:50.200
and this liability is considered as him

416
00:57:51.920 --> 00:57:54.499
always incurring expenditure.

417
00:57:55.870 --> 00:58:05.900
Here there is in the, from the cultural point of your life cycle ceremony, right from birth and up to death a lot of life cycle ceremonies.

418
00:58:06.020 --> 00:58:08.759
It may be delivery later, last time of birth.

419
00:58:09.070 --> 00:58:10.870
Then, later on.

420
00:58:11.370 --> 00:58:18.599
naming ceremony. Then, in the case of we all try half we are half wearing.

421
00:58:18.680 --> 00:58:26.689
then the airborne Kansuri. Then When situation? Underrelated poverty related

422
00:58:26.730 --> 00:58:28.230
ceremony.

423
00:58:28.240 --> 00:58:34.709
then marriage marriage let at ceremonies, fixing a bright rumor, then dowry

424
00:58:35.120 --> 00:58:50.060
until it goes on, then when she gives birth to baby again, it starts. That baby is to be given. Gifts by the parents of this woman who delivered it. Baby.

425
00:58:50.160 --> 00:59:03.099
Therefore girls are this condition from very beginning to accept that situation under the ideology of main supremacy which makes them a pract to a whole range of discriminatory practices.

426
00:59:03.780 --> 00:59:12.240
A girl acquires quality of submissiveness, weaknesses, and the self-sacrifice the so-calledation process reinforces these stereotypes.

427
00:59:12.690 --> 00:59:23.450
but all levels in the society, making her a prisoner of gender, unable to read, relatiate, and retaliate against the implicit and explicit

428
00:59:23.500 --> 00:59:25.049
even justice.

429
00:59:27.600 --> 00:59:41.500
Therefore, these customary and traditional practices seem to affect the status of women and parents are motivated asper culture to have more number of cents, a and less number of data.

430
00:59:41.560 --> 00:59:56.709
Therefore the male preference is in built in the Socialistics. Or why? Because May males. Our sons are the haves and the heads are to succeed. The UN.

431
00:59:56.920 --> 00:59:58.719
I haven't access it.

432
00:59:58.730 --> 01:00:03.560
Are they have to inherit property from the parents or grandparents like that.

433
01:00:03.580 --> 01:00:16.249
That's your male. line of authority in the form of patriarchy goes on in the Indian Association. Obviously it affects the strat of the children as well as child daring practices of the Gail, child.

434
01:00:17.320 --> 01:00:39.630
Therefore unwillingness are parent to send daughters to Co. Educational schools, where there are no female teachers, or to schools which are not at the distance requiring the girls to escort them leave of a parents, that the education is of little value to girls whose life will be devoted to a carry of family.

435
01:00:39.820 --> 01:00:43.230
So this is how it supplements my earlier statement that

436
01:00:43.620 --> 01:00:51.870
men for outside household work, for inside household wats. So as long as these cultural restrictions

437
01:00:52.110 --> 01:01:04.990
which is perpetuated through the socialization process. We men continue to be dependent, and they need to be subservient and exploited.

438
01:01:05.250 --> 01:01:09.360
Therefore the status of wealth is a obvious.

439
01:01:11.550 --> 01:01:28.470
while gender discrimination exists in providing care to girl child in areas of health, nutrition, education, distribution of work during hail each lods. This gets further heightened in that one top over T. Therefore, girls are denied

440
01:01:28.590 --> 01:01:32.640
setting basic aspects like healthy notice and education.

441
01:01:33.090 --> 01:01:45.910
Yes, the parents tend to think that, after all, this girl is for after marriage is taking care of the household only, and the C. Need not be given higher studies.

442
01:01:46.570 --> 01:01:59.480
Moreover, she she is considered as a liability as a girl who is seen as more vulnerable. Numerous restrictions are imposed on her, and her movements and behavior are concerned.

443
01:02:00.890 --> 01:02:04.230
Therefore the practice of dowry.

444
01:02:04.310 --> 01:02:11.820
Another important social evil which makes a liability for family contrastingly, sons are necessary for

445
01:02:12.090 --> 01:02:16.529
material and spiritual advancement of their parents.

446
01:02:18.120 --> 01:02:22.220
Now, when you look at their problems faced by the girl child.

447
01:02:22.440 --> 01:02:28.839
The girl children, due to societies of jurisdiction leads to life of ancat for neglected under

448
01:02:28.910 --> 01:02:31.060
is an inferior. Be.

449
01:02:31.390 --> 01:02:37.100
as I said, of socialization of the girl she has been described as unwanted.

450
01:02:37.150 --> 01:02:42.090
disrespectful, undeveloped, underdeveloped liability and explication.

451
01:02:44.510 --> 01:02:47.250
Grandchildren are trained for their marriages.

452
01:02:48.520 --> 01:02:49.660
future, of

453
01:02:49.760 --> 01:02:55.740
which a roll of a house wife, or which formal education is not required.

454
01:02:55.800 --> 01:02:57.060
that phone

455
01:02:58.200 --> 01:03:10.969
these girls especially to keep the household activities, medie her married as early as possible before poverty was a religiously uprud, and it was considered proper.

456
01:03:11.510 --> 01:03:17.779
from the view of her accommodation household family also, therefore, the cultural restrictions

457
01:03:18.550 --> 01:03:22.750
about their mobility. about her perception

458
01:03:23.530 --> 01:03:34.480
that to see is a liability, and very many expenditures are in specific problems of welfare in this regard.

459
01:03:34.700 --> 01:03:41.280
from from the social structural point of view, is a daily marriage, dowry, physical violence.

460
01:03:41.360 --> 01:03:45.250
sexual violence. and a female in find a side.

461
01:03:46.580 --> 01:03:49.350
Why, a female in the city is staying in place

462
01:03:50.690 --> 01:03:54.350
with the reference, associate success, and when status of we, child is them.

463
01:03:55.540 --> 01:03:56.929
as I stated

464
01:03:57.440 --> 01:04:02.690
men are, I mean, boy is considered as our son is considered as a

465
01:04:02.710 --> 01:04:04.000
an asset.

466
01:04:04.470 --> 01:04:08.519
and then our data is a liability.

467
01:04:08.830 --> 01:04:13.730
and son is to continue the lineage suddenly is the hate

468
01:04:13.790 --> 01:04:38.319
and daughter, in any case, is to get out of the parental, and after marriage go to the husband's house. and that life cycle ceremonies. As I started right from birth to death, the empty number of her life. Cycle, said, one is right from delivery under to her marriage and death related thing. Therefore

469
01:04:39.220 --> 01:04:50.319
the real child or women continue to remind as a secondary. and there no preference is given by respect to Alpha, the importance

470
01:04:50.510 --> 01:04:54.210
in the family and the the cultural restrictions.

471
01:04:56.710 --> 01:04:59.730
Therefore this female infant decide.

472
01:05:00.060 --> 01:05:06.459
is widely prevalent, and their parents tend to think. Having too many

473
01:05:06.480 --> 01:05:08.130
daughters in the household

474
01:05:08.410 --> 01:05:11.570
is affecting the economy of the family.

475
01:05:11.630 --> 01:05:12.720
and it

476
01:05:13.790 --> 01:05:16.290
they are prepared to have one

477
01:05:16.440 --> 01:05:19.679
are at the maximum. 2. That.

478
01:05:19.850 --> 01:05:21.719
And in case yeah.

479
01:05:21.910 --> 01:05:30.089
the third daughter is delivered means in a rural camelado, particularly poor among the poor families.

480
01:05:30.340 --> 01:05:40.560
The third girl may be. he is vulnerable to incident the upper female in bank site. At the same time fetuside is also taking place.

481
01:05:40.680 --> 01:05:43.849
Pet decided, in the case of those

482
01:05:43.890 --> 01:05:44.910
who are rich.

483
01:05:45.250 --> 01:05:51.279
taking advantage of a medical technology, particularly scanning procedure

484
01:05:51.880 --> 01:05:54.320
if they come to know about it. There

485
01:05:54.600 --> 01:06:02.040
pregnancy is a growing female baby they respect to

486
01:06:02.230 --> 01:06:07.710
a buster. Taking advantage of a medical termination of pregnancy, Mtp. Active.

487
01:06:07.740 --> 01:06:10.450
but in the case of poor parents

488
01:06:10.580 --> 01:06:14.880
they are unable to, they are unable to.

489
01:06:14.910 --> 01:06:30.060
Ahhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh

490
01:06:31.340 --> 01:06:47.280
the cast of female in French I just but want of time just to read out patriarchal associates that's a rational reputation, liability risks in looking out at dowry, too many lifecycle ceremonies in which teammate a pregnancy, poverty, lack of aness, and a family planning methods.

491
01:06:50.200 --> 01:07:02.940
As I said on already that the status of a girl child, as well as the person of whale sale, is more confined to their household. Therefore she is not getting the importance in the family situation.

492
01:07:06.310 --> 01:07:15.279
Now this is the interpreter from the theoretical framework, particularly from the Marxist feminism sources, feminism, radical feminism.

493
01:07:15.510 --> 01:07:17.030
and

494
01:07:17.040 --> 01:07:22.279
sociological interpreted from the structural possible. theory!

495
01:07:23.020 --> 01:07:36.940
Why? Because this is something related to the family marriage and the structural function when the structure is somewhat rigid and a culture based.

496
01:07:37.110 --> 01:07:42.329
It affects the women very much and offer secondary treatment.

497
01:07:46.730 --> 01:07:53.819
The implication of the implication for population is a low-sex ratio of low population growth. Male Sarnism

498
01:07:54.040 --> 01:08:14.440
Demar, we trans. In in the period is higher female extinction. Population, stability and affected suicides are also taking place, and the female trafficking, aeronomy, awareness and female, for it is said, and the in bandicide. And finally, I come to the conclusion stating that

499
01:08:14.990 --> 01:08:22.089
unless until this structural change. particularly the cultural change takes place.

500
01:08:22.550 --> 01:08:28.130
It is very difficult to improve the status of women and occurred.

501
01:08:28.920 --> 01:08:30.270
Gender equity

502
01:08:30.550 --> 01:08:50.200
are 6, equality in the Indian social instruction, and a lot of programs are being in to protect the importance and image status of Well side. But it is going on. It will take the some more time to generate that type of a gender equity.

503
01:08:50.290 --> 01:08:52.930
Thank you very much for your

504
01:08:54.940 --> 01:09:01.800
unfortunately, the recording is not there, so we have time for discussions

505
01:09:02.090 --> 01:09:05.200
at questions, comments

506
01:09:07.590 --> 01:09:08.310
the

507
01:09:09.760 --> 01:09:17.190
like to ask if what is the variation in the status of women? I mean.

508
01:09:17.220 --> 01:09:22.139
there are educated women in academia, they are women in politics.

509
01:09:22.760 --> 01:09:26.760
How do they make the way through

510
01:09:29.370 --> 01:09:38.840
as relaxed education of women as I have already pointed out, that as long as there is a sex inequality

511
01:09:38.930 --> 01:09:43.889
and differential importance is a to a male female

512
01:09:44.120 --> 01:09:47.860
which is integrated in the socialization process.

513
01:09:48.010 --> 01:09:51.620
which A is nothing forever.

514
01:09:51.910 --> 01:09:56.550
we are saying, are women, of course, in politics. A very few women

515
01:09:56.750 --> 01:09:59.340
less than a 5%

516
01:09:59.350 --> 01:10:02.080
get themselves elected to Parliament.

517
01:10:02.130 --> 01:10:12.150
But of course, these days, you know the policy of protective discrimination where women are getting an opportunity to protest in elections.

518
01:10:12.350 --> 01:10:34.169
and there are reservation for women at the grassroots level to represent in. So it is gradually getting momentum. But again, you know, there is a saying by a very successful man there is a

519
01:10:34.250 --> 01:10:46.780
so again, man is the descent maker, and the female are lady representative in the pajamas. As for the dictates of a man.

520
01:10:46.800 --> 01:10:49.530
so gender inequality

521
01:11:00.420 --> 01:11:01.120
okay?

522
01:11:05.570 --> 01:11:12.079
did you check for intra-copal similarity in fertility? Preference?

523
01:11:12.140 --> 01:11:33.490
say, well, if the couple have the same political attitudes, they know the preference, you may get similar. No, if you will. I I'm I'm thinking, if you want to make an argument for the impact of political attitude on for the fertility preference. Then

524
01:11:33.610 --> 01:11:43.700
you know, if you can show that if they have very divergent political additives, then they know their similarity would be low if they have similar political attitudes.

525
01:11:43.790 --> 01:11:53.260
If a typical preference will be similar and also be low. So I'm I'm just wondering whether you check for intra-couple similarity. Thank you.

526
01:11:56.260 --> 01:12:00.529
Yeah, thank you very much for questions. Act actually,

527
01:12:00.740 --> 01:12:25.220
the similarity in political attitude did not predict a fertility preference, however, it predicted merit of quality and marriage quality is a protector of fertility preference so it has an indirect effect in a sense that give one is very supportive to the and

528
01:12:25.390 --> 01:12:29.399
slightly affect the at the

529
01:12:29.670 --> 01:12:48.290
and another issues related to the similarity of attitude is m equation you. Someone is very supportive to a democracy, and the other one is not. It may also affect their migration intentions. because some of them actually disagree with anything in Hong Kong.

530
01:12:48.290 --> 01:13:01.379
so that that is a way to to migrate to other societies, but on on fertility purpose, that if I is, or I would say, the correlation is not significant in the direct, direct way, but we need it directly. Thank you.

531
01:13:02.700 --> 01:13:04.799
What? She said.

532
01:13:05.290 --> 01:13:18.260
 thank you. Okay, I was thinking that people who get married.

533
01:13:18.710 --> 01:13:22.370
Many are getting married because they want to start families.

534
01:13:22.530 --> 01:13:33.579
But we haven't taken into consideration single people who don't get married because they, too, are contributing to that lower fertility rate.

535
01:13:33.620 --> 01:13:43.299
So so my my comment is that maybe we need to take into consideration single people, and simply ask the married couples

536
01:13:43.400 --> 01:13:46.410
if they got married because they wanted to have children.

537
01:13:57.650 --> 01:13:58.820
More questions.

538
01:14:01.360 --> 01:14:05.080
Okay? Then we conclude. thank you very much.