Name: マップメーカーが2020年のアメリカ選挙に勝つ方法｜Maptastic ep 2 (How map makers will win the 2020 US election | Maptastic ep 2)
Uploaded: 2021-01-14T08:54:46.000Z
Duration: 19 min 34 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

We're going to look at how elections can be won and lost

based on the decisions of some of the most important people

in politics - the map-makers that draw the electoral

We'll explore some examples from America's past

Let's start by looking at just some of the basic principles

We've got these Tiddlywinks here to help us see what

So when we're talking about election maps,

people don't normally think of it in terms of points.

But that's what we're actually visualising,

isn't it, is information about individuals and how they voted.

And one of the big challenges of not just election maps but maps

from individuals who voted, in this case,

and convert that into information about areas.

If we modify our aerial unit, which is essentially

the areas that we're going to group people into

- if we group them together in different ways,

we're going to get a different answer to the question

So we're going to keep moving stuff around all the time.

So we're going to have a look now at these imaginary voters

So as you change the size of the area, you know,

the colour with the most counters changes

You can see that on the summary results here,

we're changing who's the overall winner simply by varying

a bit of the density of the points as well.

you could get away with a very big area for our constituency

or district, but not many people live in it.

If you did the same thing in an urban area,

you're going to be exacerbating potential issues in a way

that you wouldn't be in the rural because, you know,

There's much more variety and diversity in the way

As these areas get bigger, we can see quite clearly -

from yellow to red to blue - it's easy to see how the area

size can completely change your view of whether an area is

affiliated to one particular political organisation

So what we're going to do now is take all of these counters

back off the screen and just go focus down

So if we take this fictitious voting area here - so

- just four voters to keep this nice and simple.

And we want to divide this area just into two summary areas.

Where we draw the line makes a big difference.

If we draw the line width ways across the screen,

we've got a perfect balance of two in each area.

if we just change the orientation of this line

and divide it the other way, we end up with 1 and 3.

in each area just based on where the line's being drawn.

That's okay when everybody's voting yellow.

The issue starts when we take two of these yellows

away and say, well, actually, they're voting red.

And now what happens is that the line makes a big difference

to the outcome of our imaginary election,

With the line oriented this way, this side

is 100 per cent yellow, and over here it's two thirds red,

What's going to happen when we change our line?

We've actually completely reversed the scenario.

This zone out on the left-hand side is now 100 per cent red,

and this zone over here is now two-thirds yellow and one-third

So this is an example of the zoning problem.

And the reason why this is so significant when

we're thinking about social characteristics

like how people vote - people with similar characteristics

But what we're actually dealing with here

is how people with similar views tend to cluster together.

You hear this all the time about target seats

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マップメーカーが2020年のアメリカ選挙に勝つ方法｜Maptastic ep 2 (How map makers will win the 2020 US election | Maptastic ep 2)

perspective

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