Lesson video

Hello, my name's Miss Gilyeat and I'm your geography teacher for today.

In today's lesson, we are going to be analysing patterns of globalisation using digital maps and data.

Let's get started.

Our lesson outcome for today is that you can analyse patterns of globalisation and explain why some countries are more interconnected than others.

So we've got three key words for today's lesson.

The first one is interconnection, and this is the way people, places, and things are linked together through movements of people, goods, money, information, and ideas.

The second key word is visualise, which is to form a mental or physical image of something, making it easier to understand.

And finally, to analyse is to look carefully at data to identify patterns, trends, and relationships.

So we've got two learning cycles.

So to start off with, we are gonna have a go at visualising patterns of globalisation using digital tools.

And then, we are going to start analysing globalisation using those digital tools as well.

So let's get started.

Now, globalisation describes the growing interconnection of the world's economies, populations, and cultures, okay? So there's lots of different kind of aspects to globalisation.

And as Izzy says there, "It's as if the world is getting smaller," okay? So hundreds of years ago, you might not have even heard of a different country of the world.

But today, we can travel to different countries.

We can see films from different countries, okay? There's a bigger connection between different parts of the world.

Okay, let's check our understanding.

So can you fill in the missing word? globalisation describes the growing something of the world's economies, populations and cultures.

That word is interconnection.

So well done if you got that correct.

Now, globalisation can be broken down into political interconnection, so this is countries working together to make decisions or solve problems. So governments around the world, acting, yeah, acting together to help solve things.

Cultural interconnection, which is ideas, traditions, music, food, and fashion spreading between countries.

Economic interconnection, so countries trading goods, services, and money with each other.

Social interconnection is people around the world connecting through migration, communication and education, okay? So we can see there that there are four main aspects of how we can be connected to different countries around the world: through politics and governments, through culture, through economies, and also people.

Let's check what we've just learned.

Can you match the type of globalisation with the correct statement? Might be worth pausing the video to do this checking for understanding.

Okay, let's go through the answers.

So political interconnection is countries working together to make decisions or solve problems. Cultural interconnection is ideas, traditions, music, food, and fashion spreading between countries.

Economic interconnection is countries trading goods, services, and money with each other.

Social interconnection is people around the world connecting through migration, communication and education.

So well done if you got those correct.

Now, globalisation has not happened equally in all places around the world.

Some places are more interconnected than others.

So I want you to have a think.

How might some places be less connected? What could restrict one country connecting with another? Okay, have a quick think.

So we're gonna look at different ways that a country could be less connected through the different aspects.

So for example, political interconnection.

Now an example of why a country might not be as politically connected is that not all countries are in the United Nations, okay? So that's just one example of how a country might not connect with other governments around the world, if they're not in the United Nations.

But there's also other different global organisations that a country might not be a part of.

Cultural interconnection, so some countries actually ban foreign films from other countries.

Economic interconnection, some countries limit trade with other countries.

And social interconnection, some countries restrict migration and limit foreign communications, okay? So some countries are very connected with the outside world and other countries, but some like to be more isolated.

Now maps and graphs can help us see how different parts of the world are interconnected.

So what types of data could we use to show how interconnected a country is? Have a quick think.

Okay, we've got an answer from Laura here.

So, "Data showing how much a country trades with other country would help us understand economic interconnections." So Laura's correct there.

So looking at how much a country trades.

I've got an answer from Sofia.

So, "Data showing how much people in a country watch TV and films from other countries might help us understand cultural interconnections." Fantastic answer, Sofia, there.

Now Our World in Data is a website that uses reliable sources to create maps and graphs that help us understand global patterns and trends.

It allows us to visualise spatial data, which can reveal evidence of globalisation around the world.

So we're gonna watch this video going through the Our World in Data website to look at trade as a share of GDP.

So, we'll watch this together.

<v Presenter>In this recording,</v> we are going to use the Our World in Data website to visualise some evidence of globalisation.

Now, the Our World in Data website uses reliable data to help us understand our world.

And it essentially contains lots of data, but it transforms that data into maps and graphs which help us understand how things have changed over time and how things change over geographical space.

Now this website doesn't just contain things about globalisation, it contains data about lots and lots of different things.

And you can see on the top here where it says Popular Pages, and it gives us a range of different topics.

There's two key ways, I would say, which are useful for us in finding the data that we want to find.

So I'll show you the two ways.

The first way is to go to the top and you can see along this menu at the top, it says Browse by topic.

So I'm going to click on this and we can see a range of different topics come up.

Now if I go down to Poverty and Economic Development and I click on this and if I go along here, I can see right at the far right, I can see Trade &amp; Globalisation.

And that's a useful thing, I think, for us to be able to visualise evidence of globalisation, so if I click on this.

Now that will come up with a page and it's really interesting, page lots of data on here, and it's gonna come up with lots of graphs and maps that I can use.

And you are welcome to read through that.

I'm not gonna do that on this recording now.

But if I come right to the bottom of this page, it will have the key charts and graphs that it used in the article is useful for us to understand globalisation.

And you can see this one here, it says Trade as a share of GDP.

And I'm going to click on this here.

And now it's already up on the right hand side.

So if I click on Enter full screen, the full page now comes up.

Now the first thing to look at when you see a map like this is to look at the title: Trade as a share of GDP.

That means gross domestic product and that's the amount of goods and services produced in a country within a year.

And then, it gives a little bit of information.

Some of the exports and imports of goods and services divided by the GDP expressed as a percentage.

And this is known as the trade openness index.

So it's essentially saying how much a country trades with other country, both through its imports, what it buys in; and its exports, what it sells to other countries.

And we can see at the bottom here, we have a key which gives us our different percentages.

The darker colours, the higher the trade openness index, the more it's trading with countries around the world.

So we can immediately start to visualise which countries are trading a lot and which countries are not trading much.

There's some handy tools that this does, we can go to the bottom key and it will isolate each category to see which countries are in each category.

And that's really going to help us when we start to analyse some trends.

And there, again, we can see here the countries with the highest trade openness index in the world.

And we can see up there to the west of the UK, we can see Ireland.

What I might want to do is click on that.

I can even just hover over it.

It gives me some more information.

So 237.

2% of GDP, which is incredibly high in terms of its trade, it shows how much it's changed over time as well.

If I click on it, it just holds the number in place there.

So it's easier for me to compare with another country.

On the opposite end of the spectrum, there's Sudan and we can see that it was up at 36.

7% and now it's dropped in 2023, down to 2.

5%.

And you'd have to do a little bit of research to find out what that is about.

But if you do that research, you'll find out that this is to do with conflict.

And usually when conflict occurs, that can really have a devastating impact on trade.

So this is a fantastic way of being able to visualise, but, well, trade.

But in this case, it's really thinking about globalisation, how much economic interconnectedness each country has with the rest of the world.

The other thing I can do is I can play a time lapse.

So if I play the time lapse, it will go from the beginning figure, so this is 1960, and it will go all the way through.

When you have a country with these hatch lines, it means there's no data for those countries.

But you can see how this has changed over time.

And we can see that actually the biggest trend there is that it's getting darker over time, that countries are trading more and more.

Now this map is primarily concerned with economic globalisation, economic interconnectedness.

So if we want to look at maybe something else like social interconnectedness, we'd have to find some more data.

Now what I cannot do here is click on another layer of data and put this onto the same map.

And in this way, this is why this is.

Although it has certain characteristics which make it like a geographic information system, we can visualise data, we can analyse data, we can compare by looking at different maps.

It doesn't have the functionality of a dedicated GIS application.

So what I'm going to have to do is I'm going to have to open another map.

So if I open another tab, so I've still got the old one in a different tab, I can find another map which might maybe be able to help me.

Now I could go and Browse by topic again, but if I know what I'm gonna find or I want to find, I can type it in here.

And here you can see that I've typed in international migration.

Now, word of warning here, there's actually two and they're very, very similar maps.

In fact, they show the same data, but the one that we want is the one where it says, underneath it, people living in a given country who were born in another country.

That's really what we want.

And this is going to help us understand something about social interconnectedness and how much people are moving around.

Now, again, I can put this into full screen, which I'll do in a second.

This at the moment is given as the total number of people in the country who were born in another country.

The problem with this is you can see there, the United States is over 52 million, which is an awful lot.

It's a lot more than, for example, in Norway with 1 million.

But the problem with that is because it's not taken into account the overall population, I think it's a bit more useful to look at a percentage or proportion.

So at the top here, we can see per capita / share of the population where it stays under the sub-metric.

So I'm gonna click on this and it changes it slightly.

You can see now the United States is given as a percentage and it's 15%, it's actually lower than Norway than 18%.

I can go into full screen here and we can do the same again.

We can start to kind of compare different parts of the world.

We can see where the kind of areas with very low numbers of people born in other countries.

So China, India, Democratic Republic of Congo, and Nigeria, Brazil, low numbers living in those countries.

And then, you can see in these really dark blue areas, let me just hold over there where we have the places where we've got high proportions of people who come from overseas.

So if we go to Ireland for example, 23.

1%.

I go to Saudi Arabia, 40.

3.

If we go to Qatar, we can actually see it's down at 76.

7%.

So hopefully, you can see from this just how useful Our World in Data maps are at visualising globalisation or evidence of globalisation around the world.

Our first map showed us which countries are more economically interconnected through trade.

And this map shows us how many people born in other countries and gives us an idea about how socially interconnected each country is with other countries around the world.

<v ->So let's check what we've just learned.

</v> More people migrating around the world seek better opportunities would best be described as: A, social globalisation; B, economic globalisation; or C, political globalisation.

The answer to that is A, social globalisation.

Well done if you got that right.

Okay, we're on to our first task for the lesson.

What I'd like you to do is go onto the Our World in Data website and you can use the link on the slide here.

You're going to click on Browse by topic.

Then, click on Poverty &amp; Economic Development.

Click on Trade Globalisation.

Scroll down to the bottom of the page where it shows Key Charts on Trade &amp; Globalisation.

Click on and open Trade as a share of GDP, and then Enter full screen.

So I've just highlighted there what the Enter full screen little icon looks like.

And then, you're going to use your mouse to hover over countries and see the percentages to see which countries are trading the most at the least, okay? Good luck.

And what I'd like you to do is open Our World in Data again.

But this time, you're going to use the search tool, okay? And type in Share of the population that was born in another country into the search component.

Then, you're going to do a similar thing.

Hover your mouse over different countries to find out what percentage of that population was born in another country.

Click on the percentages at the bottom of the page to highlight countries of similar percentages.

So pause the video and have a go at that second task.

Okay, and then for your third task, you are going to investigate the social and economic interconnectedness of a country of your choice.

You are then going to fill in the table to show your findings.

So you need write down what country it is that you're going to look into.

What continent it's in, okay? Whether it has a high or low amount of trade openness, so using the first map that you looked at.

Then, find out whether it's got high or low percentage of people who are born overseas.

And then, give your final verdict on how interconnected you think that country is and explain your answer.

Okay, let's have a look at the answers then.

So for tasks one and two, your screen should have looked a little bit like this.

So the map on the left shows the Trade as a share of GDP map.

And the map on the right shows the share of the population that was born in another country.

And I've put an example answer here for the third task.

So I investigated Sweden, which is in Europe.

It's got a really high percentage of trade openness.

So, 106.

4% of the GDP.

It's also got a very high percentage of people that were born in another country, okay? So I've put: I think the country is very interconnected as they are very open to trade with other countries and a lot of their population will have strong links with where they were born, okay? So, that's my answer.

You've probably done another country, but that's fine.

We're onto our second learning cycle now.

So we're going to have a go at analysing globalisation using digital tools.

Now, geographers need to be able to analyse data.

Analysis is when we look carefully at data to identify patterns, trends, and relationships.

Now analysis can be spatial, so over a geographic space.

And in general, we would use maps to look at that because we can see different areas of the world or a country or just an area and look at the data and what the data shows to see if we can see any patterns, okay? Analysis can also be temporal.

So over time, okay? So we've got a line graph here, which is the trade as a share of GDP, okay? But on the bottom access, we've got between 1960 and 2023 and we've got percentage on the Y-axis.

So these maps are showing a similar kind of thing that we are looking at, trade as a share of GDP, but one's looking over a spatial area and one's looking how it's changed over time, okay? And we can see from the temporal graph that, in general, countries and the world are seeing an increase in percentage of trade as a share of GDP.

Now maps and graphs from Our World in Data can be used to analyse the extent of globalisation across different regions of the world.

So we're going to watch this video together of how we can do this.

<v Presenter>In this video,</v> we are gonna use Our World in Data to analyse patterns of globalisation.

Now you will see from the map on the screen that I've still got the trade as a share of GDP open at the moment.

I've also got another tab which has the share of the population that was born in another country and I can make that full screen.

But I'm also going to add another tab and it's going to be data that we can compare with those other layers of data.

So here's my new tab.

Now, I know what I want to find and I want to find what we call GNI per capita.

You can see it's come up there, Gross National Income per capita.

So I can click on that.

And then, it comes up with this map.

Now the Gross National Income per capita is similar to the GDP, but it's not the same.

It measures the total income and by residents of the country, but it includes income earned abroad.

So we sometimes see it as a little bit more, a bit better measure than GDP per capita.

And I'm using this, I'm going to put it in full screen, I'm using this so we can compare this with some of our other maps and see how this compares the income of the country with how globalised the country is.

So a good way of seeing patterns is to come to the key at the bottom and just hover over there; at the moment, the highest income category, and we can see that they come up straight away there.

And you can see, it's unsurprising, North America, Western Europe, parts of the Middle East like Saudi Arabia and Australia, they're coming up as our High Income Countries with the other place just dotted around.

If I want to hover over those, if I go to Ireland, we can see it's incredibly high, $90,884 per person.

If I go to Saudi Arabia there, $50,000.

If I go to Qatar, it's over $100,000.

These are very High Income Countries.

UK as a reference point, again, is over $50,000 and that's per year and per person.

If I scroll down the data, we know probably from your work earlier in geography that our lower income countries tend to be in Sub-Saharan Africa, and you can see Afghanistan highlighted there.

So we know roughly speaking where the low income countries are and High Income Countries are.

Now, unfortunately, I can't just add the other map layers onto this like I could if it was a fully functional GIS system.

So I'm going to have to click on my other tab and I can click on the migration tab.

So this is the share of the population that was born in another country.

And if I hover over where it's over 20%, we can see Australia's there, Saudi Arabia, a lot of the Middle East, bits of Western Europe, Canada's in there.

You can see Ireland's in there as well.

And again, you can hover over these to check the actual figure.

The category below this between 10 and 20%, that sort of fills in the other bits of Western Europe, like the UK, and over North America, the USA.

So they're the places where there is a higher percentage of people that were born in another country.

Now that seems to correlate pretty strongly with our High Income Countries.

They're not exactly the same, but it's a very strong correlation, very strong relationship.

If I go to our low countries so that where there's a low proportion of people born in other countries, it tends to correlate quite strongly with our lower income countries.

So a lot of countries in Sub-Saharan Africa there.

So if again, if I hover over them, we can see exactly the figure.

So I would say that's something, a pattern that we could analyse, and we can see that it tends to be certain with this higher income countries and the proportion of people bond to the country, it tends to correlate fairly strongly.

So we can often say from this, or we might say from this, there is a relationship between how higher income the country is and how socially globalised they are in terms of migration, how many people are moving into that country.

So you can investigate that a little bit further.

If I go into trade and globalisation and I click on those where there is a high trade as a share of GDP, now you'll notice that, all of a sudden, it's a little bit more complex and it doesn't come up in those really, really high categories as all the High Income Countries.

And if I go down, it's a bit of a mixed picture.

We can see countries from Sub-Saharan Africa there, countries from Southeast Asia, Mongolia's in there, a lot of Eastern Europe.

And I can go down and actually I would say the pattern, if we compare that with the income of the country, doesn't seem to be very strong.

So it doesn't seem a very strong relationship in that regard.

But it might be, well, that's just not, that's not what is dictating whether a country has a lot of trade with other countries.

It's not about how higher income they are.

Maybe there's another something else which is affecting it.

So let's have a look again with those countries that have got very, very high trade.

And do you notice anything about which is common to all of them? Let's now go to one of our lower categories.

So there's only Sudan in the lowest category and none between 10 and 20%.

So this is where one of the lowest categories where we get lots of countries.

And what do we notice which is different about a lot of these countries versus these countries? What you may have noticed is that certainly in this lower category, we have a lot of the biggest countries in the world.

You can see Russia's there, China, India, Australia, Brazil, United States.

So there's a huge number of these bigger countries and that potentially gives us something to work on to think about why that might be the case and why some of the smaller countries are the countries which have a lot of trade with other countries around the world.

So that is an example of spatial analysis using different maps to analyse data over geographical space.

And in this case, try and come up with reasons, analyse patterns, but then come up with reasons about why certain parts of the world are maybe more economically globalised and where other parts of the world are more socially interconnected or socially globalised.

But that's a spatial relationship.

It's not a temporal or a relationship over time.

If I want to show a relationship over time, I could play this time lapse at the bottom and look for changes in colour.

So I can do that now.

And we can see the colours change and maybe they're going a bit darker there, but it's very hard to be sure and specific about whether that's a real pattern or not, like a pattern over time.

So what I can do instead is I can go to where it says Chart and I can click on the Chart.

And now it gives me a graph showing, in this case, it shows me the world, India, China, the United States of America, and shows their trade over time and how their trade openness index has changed.

If I want to add another country on here, I can just go to the right and tick a country.

So I ticked Ireland on there.

We can see that huge growth in trade in Ireland over time.

I'm gonna unclick that for now and I want to see a pattern for the world at the moment.

So if I unclick India, China, and the United States and look at the world, I can see this pattern over time or, I should say, the trend really over time.

And the trend from 1970 certainly goes upwards, doesn't it? But if we're gonna be really accurate there, is that a uniform increase in trade openness or can we actually break this graph up? Now, I would suggest that from 1970 to this point in 2008, there's a fairly steady increase in the trade openness.

But after this point, I would say that it's more of a fluctuating trend that actually it's staying relatively close to around 55%.

So again, that gives us some, and that's allowed us to analyse over time.

And from this point, we can then start to think of reasons why maybe after 2008, things changed and it changed the amount that countries who were trading around the world and actually tells us something about economic globalisation over time.

<v ->Okay, let's check what we've just learned.

</v> Which of the following statements is correct? The answer is B.

So Higher Income Countries are more likely to have a higher percentage of their population born in another country.

Well done if you got that correct.

Now, after identifying patterns, trend or relationships in data, we can use our geographical knowledge and understanding to help explain them.

So I want you to have a think.

Why might Higher Income Countries be more likely to have a higher percentage of their population born in another country? What do you reckon? So we've got an answer from Jun here.

So he's put: "Higher Income Countries might be more likely to have a higher percentage of their population born in another country because people may want to migrate there to earn more money and have a better standard of living." That's correct, Jun, well done.

Okay, I want you to have a look at Jun's answer of what he's just put there.

And can you tell what word in that answer shows that it is an explanation? That's "because," okay? Explanations often start with because.

Well done if you found that.

Okay, we're on to our final tasks for this lesson.

What I'd like to do is go onto the Our World in Data website and you can use that link there.

And in three separate tabs, you're going to search and open these maps.

So GNI, Gross National Income per capita, now that's the amount of money in a country that it's earning per person, so they divide it by its population.

Share of the population that was born in another country.

And finally, trade as a share of GDP.

First, I'd like you to compare the GNI map to the share of population that was born in another country to see if you can spot any patterns.

And then, I'd like you to compare the GNI map to the trade as a share of GDP map to see if you can spot any patterns.

So pause the video and get analysing.

Okay, our final task for this lesson is I'd like to place a cross on the line representing your opinion for this statement.

High Income Countries are always more interconnected with other countries around the world, okay? Once you've put your cross on the line, you're going to state your opinion.

So do you agree, disagree, or partly agree? And then, you are going to justify your opinions.

So give reasons for and against the statement.

Are there factors other than income that influence country's interconnectedness? Okay, so pause the video and have a go at this final task.

Okay, so for the first task: In general, the countries with a high GNI also have a high share of the population that were born in another country.

But for the second map, there tends to not be a strong relationship between a high GNI and trade as a high share of country's GDP.

Instead, you might have noticed that smaller countries in terms of a land area tend to have trade as a high share of their GDP.

So well done if you spotted those patterns.

So here we've got a model answer for this question, okay? Now I partly agreed with the statement, okay? You didn't have to agree with what I've put, but here's a model answer of how you would structure your answer.

So I partly agree with this statement.

On the one hand, there is a clear relationship between countries with higher GNIs and a higher percentage of people that were born in another country, for example Sweden and Australia.

However, there does not appear to be a strong relationship between a high GNI and trade as a high share of a country's GDP.

Instead, smaller countries in terms of land area tend to have trade as a high share of their GDP, such as Ireland and the UAE.

Okay, we've got a summary for today's lesson here.

Some places of the world are more interconnected than others.

Digital maps and graphs can help us visualise and analyse patterns and trends in globalisation.

And the wealth and size of the country can influence economic and social globalisation.

Right, that's it from me.

Fantastic job on today's lesson and I'll see you next time, bye.