The best stats you've ever seen | Hans Rosling

TED
16 Jan 200720:36

Summary

TLDRDer Video-Skript spricht über globale Entwicklung und stellt heraus, dass selbst hochqualifizierte schwedische Studenten über die Welt nur wenig wissen. Es zeigt, wie Länder wie China und Indien sich in Bezug auf Bevölkerung, Lebenserwartung und Familiengröße verändert haben. Es betont die Notwendigkeit, Daten zu visualisieren und zugänglich zu machen, um ein besseres Verständnis der globalen Veränderungen zu ermöglichen. Das Skript fordert dazu auf, offizielle Statistiken für alle zugänglich und durchsuchbar zu machen, um ein tieferes Verständnis der Welt zu fördern.

Takeaways

  • 😲 Die Studie zeigt, dass selbst hochqualifizierte schwedische Studenten statistisch signifikant weniger über die Welt wissen als Schimpansen.
  • 🌟 Die Visualisierung von Daten durch Software, die Länder als Blasen darstellt, ermöglicht es, Veränderungen in Bevölkerungsgröße, Geburtenrate und Lebenserwartung über die Zeit zu verfolgen.
  • 🌍 In den letzten Jahrzehnten haben sich Länder wie China und Vietnam in Bezug auf Familiengröße und Lebenserwartung signifikant verbessert.
  • 📈 Die Welt hat sich von einer getrennten in eine mehr zusammengewachsene Welt entwickelt, wo die meisten Menschen in den mittleren Einkommensgruppen leben.
  • 💰 Die Weltverteilung des Einkommens ist nicht mehr geteilt in reiche und arme Länder, sondern es gibt jetzt eine breite Palette von Einkommensniveaus.
  • 🔍 Es gibt große Unterschiede innerhalb von Ländern, wie Afrika, Südasien und Arabische Staaten, die bei der Diskussion über globale Entwicklung berücksichtigt werden müssen.
  • 📊 Die Visualisierung von Daten kann helfen, die Komplexität der globalen Entwicklung besser zu verstehen und die Diskussion über globale Herausforderungen zu vertiefen.
  • 🌐 Die Verwendung von interaktiven Datenvisualisierungen kann dazu beitragen, die Daten besser für Studierende, Entscheidungsträger und Unternehmen zugänglich zu machen.
  • 🚀 Die Veröffentlichung von öffentlich finanzierten Statistiken als durchsuchbare Daten könnte die Art und Weise revolutionieren, wie wir globale Trends und Entwicklungen analysieren.
  • 🌐 Der Zuwachs der Internetnutzer pro 1000 Einwohner und die wirtschaftliche Entwicklung der Länder gehen oft Hand in Hand, was auf eine Annäherung der Länder aneinander hindeutet.

Q & A

  • Welches Land hatte nach der Umfrage bei den schwedischen Studenten die höchste Kindersterblichkeit?

    -Die Türkei hatte die höchste Kindersterblichkeit.

  • Wie oft haben die schwedischen Studenten richtig geantwortet, wenn sie versucht haben, das Land mit der höchsten Kindersterblichkeit zu identifizieren?

    -Die Studenten haben in etwa 1,8 von 5 möglichen Antworten richtig erkannt.

  • Was hat der Sprecher über die Leistung der schwedischen Studenten im Vergleich zu Schimpansen gesagt?

    -Der Sprecher hat angemerkt, dass die schwedischen Top-Studenten statistisch signifikant weniger über die Welt wissen als Schimpansen, da diese bei einer Zufallswahl in etwa die Hälfte der Fälle richtig beantworten würden.

  • Wie hat sich die Welt seit 1962 in Bezug auf Familiengröße und Lebenserwartung verändert?

    -Seit 1962 haben sich viele Länder in Richtung kleinere Familien und längere Lebenserwartungen entwickelt. Industrieländer hatten kleinere Familien und längere Lebenserwartungen, während Entwicklungsländer umgekehrt waren. In den letzten Jahrzehnten haben sich auch Entwicklungsländer in diese Richtung bewegt.

  • Was zeigte die Visualisierung der Welt mithilfe von Blasen, wobei die Größe der Blasen die Bevölkerung und die Achsen die Geburtenrate und die Lebenserwartung darstellen?

    -Die Visualisierung zeigte, dass sich Länder wie China und Lateinamerika in Richtung kleinere Familien und längere Lebenserwartungen bewegt haben, während andere wie die arabischen Länder größere Familien hatten, aber keine signifikanten Verbesserungen in der Lebenserwartung.

  • Wie hat sich die Einkommensverteilung in der Welt verändert, und welche Bedeutung hat dies für das Konzept der Entwicklungsländer?

    -Die Einkommensverteilung hat sich von einer deutlichen Kluft zwischen Arm und Reich zu einer kontinuierlichen Verteilung gewandelt, wobei die meisten Menschen in der Mitte liegen. Dies macht das Konzept der Entwicklungsländer zweifelhaft, da es jetzt eine Überschneidung zwischen reichen und armen Ländern gibt.

  • Was hat der Sprecher über die Veränderungen in Asien in den letzten Jahrzehnten gesagt?

    -Der Sprecher betonte, dass die sozialen Veränderungen in Asien, insbesondere die Verringerung der Familiengröße und die Verbesserung der Lebenserwartung, die wirtschaftlichen Veränderungen vorausgingen und dass dies oft unterschätzt wird.

  • Wie vergleicht der Sprecher die Entwicklung von Südkorea und Brasilien seit 1960?

    -Der Sprecher zeigte, dass Südkorea eine schnellere Entwicklung erleben hat als Brasilien, wobei Südkorea schneller in Richtung kleinere Familien und längere Lebenserwartungen aufgestiegen ist.

  • Was ist die Hauptbotschaft des Sprechers über die Notwendigkeit, Daten effektiv zu nutzen?

    -Der Sprecher betont die Notwendigkeit, öffentlich finanzierte Statistiken leicht zugänglich und durchsuchbar zu machen, um ein besseres Verständnis der Welt und ihrer Veränderungen zu ermöglichen.

  • Was ist das Ziel des von dem Sprecher erwähnten Non-Profit-Ventures 'Gapminder'?

    -Das Ziel von 'Gapminder' ist es, Daten visualisierbar und durchsuchbar zu machen, um eine bessere Verständigung und Nutzung von öffentlich finanzierten Statistiken zu fördern.

Outlines

00:00

🌏 Globale Entwicklung und Vorurteile

Der Sprecher erzählt von seiner Erfahrung, globale Entwicklung an einem schwedischen Universitätskurse zu lehren. Nach 20 Jahren der Zusammenarbeit mit afrikanischen Institutionen, die Hunger in Afrika erforschten, sollte er über die Welt Bescheid wissen. Er begann an der Medizinischen Fakultät, dem Karolinska Institut, mit einem Kurs namens globales Gesundheitswesen. Um herauszufinden, was seine Studierenden schon wussten, machte er eine Vortestung. Er stellte fest, dass sie statistisch signifikant weniger über die Welt wussten als Schimpansen. Dies führte zu der Erkenntnis, dass es notwendig ist, über globale Gesundheitsthemen zu kommunizieren. Er entwickelte eine Software, die Daten über die Welt in Form von Blasen darstellt, wobei die Größe der Blasen die Bevölkerung und die Achsen das Kindheitssterblichkeitsrisiko und die Lebenserwartung repräsentieren. Er zeigte, wie sich Länder wie China und Indien entwickelt haben und wie sich die Bevölkerungsstruktur und Lebenserwartungen verändert haben.

05:01

📊 Einkommensverteilung und soziale Veränderungen

Der zweite Absatz behandelt den Vergleich zwischen den Vereinigten Staaten und Vietnam im Jahr 1964, wo die USA kleine Familien und längere Lebenserwartungen hatten, während Vietnam große Familien und kürzere Lebenserwartungen aufwies. Der Sprecher zeigt, wie sich Vietnam im Laufe des Krieges entwickelt hat, insbesondere durch die Einführung der Familienplanung. Er diskutiert auch die Weltverteilung des Einkommens und stellt fest, dass es keinen mehr großen Unterschied zwischen Arm und Reich gibt, sondern dass die meisten Menschen in der Mitte der Einkommenspyramide leben. Er betont, dass der Begriff 'Entwicklungsländer' zweifelhaft ist, da die meisten Menschen in der Mitte der Einkommensverteilung leben. Der Sprecher verwendet Datenvisualisierungen, um die Veränderungen in der Welt zu veranschaulichen, wie zum Beispiel die Verbesserung der Lebenserwartung und die Verkleinerung der Familiengröße in verschiedenen Ländern und Regionen.

10:01

🗺️ Unterschiede zwischen Ländern und Regionen

In diesem Absatz spricht der Sprecher über die Unterschiede zwischen verschiedenen Ländern und Regionen der Welt. Er zeigt, wie Länder wie Ghana Handelsbarrieren abbauen konnten und wie dies ihre Wirtschaft beeinflusste. Der Sprecher betont die enorme Variation innerhalb von Afrika und zeigt, dass nicht alle afrikanischen Länder gleich sind. Er verwendet Datenvisualisierungen, um die Unterschiede zwischen verschiedenen Ländern und Regionen zu veranschaulichen, wie zum Beispiel Südasien, Arabische Staaten und Osteuropa. Er diskutiert auch die Bedeutung von Daten und wie sie zur Verbesserung der Welt beitragen können, aber auch die Herausforderungen, die damit verbunden sind, wie zum Beispiel die Tatsache, dass Daten oft nicht leicht zugänglich sind.

15:01

🌐 Datennutzung und Visualisierung

Der vierte Absatz konzentriert sich auf die Notwendigkeit, Daten effektiv zu nutzen und zu visualisieren, um ein besseres Verständnis der Welt zu erhalten. Der Sprecher beschreibt, wie er und sein Team eine Non-Profit-Organisation namens Gapminder gegründet haben, die darauf abzielt, Daten leichter zugänglich und verständlich zu machen. Er diskutiert die Herausforderungen, die damit verbunden sind, wie zum Beispiel die Tatsache, dass viele Daten in Datenbanken versteckt sind und nicht leicht für die Öffentlichkeit verfügbar sind. Er fordert eine verbesserte Datennutzung und -visualisierung, um ein besseres Verständnis der Welt und ihrer Veränderungen zu ermöglichen.

20:04

🎨 Kreativität und ihre Bedeutung

Der letzte Absatz des Scripts ist eine Art Schlussfolgerung oder Appell an die Zuhörer, die Wert auf Kreativität und Ideen legen. Der Sprecher spricht über die Bedeutung von künstlerischer Vision und inspirierenden Designideen, die zur Entwicklung von ultimativen Fahrzeugen beitragen können. Es ist eine Art Aufruf, die Bedeutung von Ideen und der Kreativität zu schätzen und zu schützen.

Mindmap

Keywords

💡Global Health

Global Health bezieht sich auf die Verbesserung der Gesundheit und das Verringern von Gesundheitsungleichheiten zwischen verschiedenen Ländern und Bevölkerungsgruppen. Im Video wird dies durch die Darstellung von Gesundheitsdaten verschiedener Länder und deren Entwicklung über die Zeit veranschaulicht.

💡Child Mortality

Kindersterblichkeit ist ein Maß für die Anzahl an Kindern, die vor ihrem fünften Lebensjahr sterben. Im Skript wird dies als zentrales Thema verwendet, um die Unterschiede in der Gesundheitsversorgung zwischen verschiedenen Ländern aufzuzeigen.

💡Fertility Rate

Die Geburtenrate gibt die durchschnittliche Anzahl an Kindern an, die eine Frau im Laufe ihres Lebens zur Welt bringt. Im Video wird gezeigt, wie sich die Geburtenrate im Laufe der Zeit verändert hat und wie sie mit dem Lebenserwartung und der wirtschaftlichen Entwicklung zusammenhängt.

💡Life Expectancy

Die Lebenserwartung ist eine Schätzung der durchschnittlichen Anzahl an Jahren, die ein Mensch nach seiner Geburt erleben wird. Im Video wird die Lebenserwartung verwendet, um die Verbesserung der Gesundheitsversorgung und Lebensbedingungen in verschiedenen Ländern zu veranschaulichen.

💡Preconceived Ideas

Vorurteile sind vorher festgelegte Meinungen oder Annahmen über etwas, ohne dass tatsächliche Fakten oder Daten zugrunde gelegt werden. Im Skript wird darauf hingewiesen, dass die Studie die Vorurteile der Studierenden über die Welt und deren Gesundheitszustand aufdeckte.

💡Data Visualization

Datenvisualisierung ist die Darstellung von Informationen und Daten in graphischen Formaten, um sie leichter verständlich und zugänglich zu machen. Im Video wird dies durch die Verwendung von Diagrammen und Animationen gezeigt, um komplexe globale Gesundheitsdaten zu erklären.

💡Gapminder

Gapminder ist eine non-profit Organisation, die darauf abzielt, Daten über globale Entwicklung leicht zugänglich und verständlich zu machen. Im Video wird Gapminder als Beispiel für die Bedeutung von offenen und zugänglichen Daten genannt.

💡Income Distribution

Die Einkommensverteilung beschreibt, wie das Gesamteinkommen in einer Gesellschaft oder Gruppe auf die einzelnen Mitglieder verteilt ist. Im Video wird gezeigt, wie sich die Einkommensverteilung über die Zeit verändert hat und wie sie mit der wirtschaftlichen Entwicklung zusammenhängt.

💡Economic Growth

Wachstum der Volkswirtschaft bezeichnet die Steigerung des BIP pro Kopf über einen bestimmten Zeitraum. Im Video wird das wirtschaftliche Wachstum verschiedener Länder und seine Auswirkungen auf die Lebensqualität und den Gesundheitszustand der Bevölkerung diskutiert.

💡HIV Epidemic

Die HIV-Epidemie ist eine weit verbreitete Ausbreitung der HIV-Infektion, die zu einer erhöhten Sterblichkeit und einer Verringerung der Lebenserwartung geführt hat. Im Video wird die Auswirkung der HIV-Epidemie auf die Gesundheitsversorgung und die Lebenserwartung in Afrika besprochen.

💡Internet Users

Die Anzahl der Internetnutzer gibt an, wie viele Menschen Zugang zum Internet haben. Im Video wird dies als Indikator für die Verbreitung neuer Technologien und die potenzielle Verbesserung der Informationszugänglichkeit und -kommunikation verwendet.

Highlights

Ten years ago, the speaker embarked on teaching global development to Swedish undergraduates after studying hunger in Africa for 20 years.

The course was initiated at the Karolinska Institute, a medical university known for its connection to the Nobel Prize in Medicine.

A pretest revealed that Swedish students had a poor understanding of global health issues, with only 1.8 out of 5 possible correct answers.

The speaker humorously compared the students' knowledge to that of chimpanzees, emphasizing the need for education.

A software tool was developed to visually represent global health data, with bubbles indicating countries and size representing population.

The visualization showed a shift in global demographics, with countries moving towards smaller families and longer life expectancies.

The talk highlighted the significant changes in Asia, particularly in family planning and economic growth, before the economic boom.

The speaker compared the development trajectories of the United States and Vietnam, illustrating the convergence of life expectancy and family size.

The presentation showcased the changing global income distribution, with a shift from a bimodal to a more even spread.

The concept of 'developing countries' was questioned, as the majority of the world's population now falls in the middle-income bracket.

The talk emphasized the importance of data visualization in understanding global trends and the need for accessible data.

The speaker advocated for making publicly funded data searchable and freely available to the public for better understanding and utilization.

The presentation ended with a call to action for the liberation of data and its visualization to foster a deeper understanding of global development.

The speaker's venture, Gapminder, aims to link data to design, making complex global statistics accessible and understandable.

The talk concluded with an optimistic view of the future, where the internet and technology will play a crucial role in democratizing data access.

Transcripts

play00:06

[Music]

play00:24

but ten years ago I took on the task to

play00:27

teach global development to Swedish

play00:30

undergraduate students that was after

play00:32

having spent about 20 years together

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with African institutions studying

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hunger in Africa so I was sort of

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expected to know a little about the

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world and I started in our medical

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university Karolinska Institute an

play00:45

undergraduate course called global

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health but when you get that opportunity

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you get a little nervous I thought these

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students coming to us actually have the

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highest grade you can get in Swedish

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college system so I thought maybe they

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know everything I'm going to teach them

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about so I did a pretest when they came

play01:02

and one of the question from which I

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learned a lot was this one which country

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has the highest child mortality of these

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five pairs and I put them together so

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that in each pair of country one has

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twice the child mortality of the other

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and this means that it's much bigger the

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difference than the uncertainty of the

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data I won't put you to test here but

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it's Turkey which is high as there

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Poland Russia Pakistan and South Africa

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and these were the results of the

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Swedish students I did that so I got the

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confidence interval which was pretty

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narrow and I got happy of course at one

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point eight right answer out of five

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possible that means that there was a

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place for a professor of international

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health and for my course but one life

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late night when I was compiling the

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report I really realized my discovery I

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have shown that Swedish top students

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know statistically significantly less

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about the world than the chimpanzees

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because the chimpanzee would score half

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right if I gave him two bananas with Sri

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Lanka and Turkey they would be right

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half of the cases but the students are

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not there the problem for me was not

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ignorant it was preconceived ideas I did

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also an unfair unethical study of the

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professors of the Karolinska Institute

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that hands out the Nobel Prize in

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medicine and they are on par with the

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chimpanzee there so this is where I

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realized that there was really a need to

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communicate because the data or what's

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happening in the world and the child

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health obviously every country is very

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well aware so we did this software which

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displays it like this every bubble here

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is a country this country over here is

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this is China and this is India the size

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of the bubble is the population and on

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this axis here I put fertility rate

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because my students what they said when

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they looked upon the world and I asked

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them what do you really think about the

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world huh well I first discovered that

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the textbook was Tintin mainly and they

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said the world is still we and them and

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we is Western world and them is third

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world and what do you mean with Western

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world I said well that's long life in

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small family and third world is short

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life in large family so this is what I

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could display here I put fertility rate

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here number of children per woman 1 2 3

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4 up to about eight children per woman

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we have very good data since 1960 to

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1968 on the size of families in all

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countries the error margin is narrow

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here I put life expectancy at birth from

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30 years in some countries up to about

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70 years and 1962 that was really a

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group of countries here that was

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industrialized countries and they had

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small families and long lives and these

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were the developing countries they had

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large families and they had relatively

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short lives now what has happened since

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1962 we want to see the change or the

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students right it's still two types of

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countries or have these developing

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countries got smaller families and they

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live here or have they got longer lives

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and live up there let's see we stopped

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the world and this is all UN statistic

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that has been a

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here we go can you see that it's China

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they're moving them against better

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health they are improving there or the

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green latin-american countries they are

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moving towards smaller families your

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yellow ones here or the Arabic countries

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and they get larger families but they no

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longer life but not larger families the

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Africans are the green down here they

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still remain here this is India

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Indonesia is moving on pretty fast and

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in the 80s here you have Bangladesh

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still among the African countries there

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but now Bangladesh it's a miracle that

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happens in the 80s the Imams start to

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promote Family Planning and they move up

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into that corner and in 90s we have the

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terrible HIV epidemic that takes down

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the life expectancy of the African

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countries and all the rest of the world

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moves up into the corner where we have

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long lives and small family and we have

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a completely new world

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[Applause]

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let me make a comparison directly

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between United States of America and

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Vietnam 1964 America had small families

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and long life Vietnam had large families

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and short lives and this is what happens

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the data during the war indicate that

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even with all the death there was an

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improvement of life expectancy by the

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end of the year the Family Planning

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started in Vietnam and they went for

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smaller families and the United States

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up there is getting for a longer life

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keeping family size and in the 80s now

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they give up communist planning and they

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go for market economy and it moves

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faster even in social life and today we

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have in Vietnam the same life expectancy

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and the same family size here in Vietnam

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19 2003 as in United States 1974 by the

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end of the war I think we all if we

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don't look in the data we underestimate

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the tremendous change in Asia which was

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in social change before we saw the

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economical change so let's move over to

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another way here in which we could

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display the distribution in the world of

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the income this is the world

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distribution of income of people $1 $10

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or $100 per day there's no gap between

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rich and poor any longer this is a myth

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there's a little hump here but there are

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people all the way and if we look where

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the income ends up the income this is

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100 percent of world's annual income and

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the rich is 20% they take out of that

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about 74 percent and the poor is 20%

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they take about 2% and this shows that

play07:04

the concept developing countries is

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extremely doubtful we sort of think

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about aid like these people here giving

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aid to these people here but in the

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middle we have most a world population

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and they have now 24 percent of the

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income we heard it in other forms and

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who are who are these these where are

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the different countries

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I can show you Africa this is Africa

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10% of world population most

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impoverished this is oacd

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the rich country the country club of the

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UN and they are over here on this side

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and quite an overlap between Africa and

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oacd and this is Latin America it has

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everything on this earth from the

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poorest to the richest in Latin America

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and on top of that we can put East

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Europe we can put East Asia and we could

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South Asia and how did it look like if

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we go back in time to about 1970 then

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there was more of a hump and we have

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most who lived in absolute poverty were

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Asians the problem in the world was the

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poverty in Asia and if I now let the

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world move forward you will seen that

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wild populations increase there are

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hundreds of millions in Asia are getting

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out of poverty and some others get into

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poverty and this is the pattern we have

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today and the best projection from the

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World Bank is that this will happen and

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we will not have a divided world we have

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most people in the middle of course it's

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a logarithmic scale here but our concept

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of economy is growth with percent we

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look upon it as a possibility of percent

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increase if I change this and I take GDP

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per capita instead of family income and

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I turn these individual data into

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regional data of gross domestic products

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and I take the regions down here the

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size of the bubble distill the

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population and you have the OECD there

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and you have sub-saharan Africa there

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and we take off the Arab states they're

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coming both from Africa and from Asia

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and we put them separately and we can

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expand this axis and I can give it a new

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dimension here by adding the social

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values their child survival now I have

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money on that axis and I have the

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possibility of children to survive there

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in some countries ninety-nine point

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seven percent of children survive to

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five years of age others only seventy

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and here it seems that this a gap

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between oacd

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Latin America East Europe East Asia Arab

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states South Asia and sub-saharan Africa

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the linearity is very

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strong between child survival and money

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but let me split sub-saharan Africa

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health is there and better help is up

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there I can go here and I can split

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sub-saharan Africa into its countries

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and when it bursts the size of East

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country bubble it's the size of the

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population Sierra Leone the down there

play10:00

more reaches up there

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now reaches was the first country to get

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away with trade barriers and they could

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sell those sugar they could sell their

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textiles on equal terms as the people in

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Europe and North America there's a huge

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difference between Africa and Ghana is

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here in the middle in Sierra Leone a

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humanitarian aid here in Uganda

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development aid here time to invest

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there you can go for holiday it's a

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tremendous variation within Africa which

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we very often make that it's equal

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everything I can split South Asia here

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India's the big bubble in the middle but

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huge difference between Afghanistan and

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Sri Lanka and I can speed Arab states

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how are they same climate same culture

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same religion huge difference even

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between neighbors Yemen Civil War United

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Arab Emirates money which was quite

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equally and well used not as the methods

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and that includes all the children of

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the foreign workers who are in the

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country data is often better than you

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think

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many people say data is bad there is an

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uncertainty merge but we can see the

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difference here Cambodia Singapore the

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differences are much bigger than the

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weakness of the data East Europe Soviet

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economy for a long time but they come

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out of the ten years very very

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differently and there is Latin America

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today we don't have to go to Cuba to

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find a healthy country in Latin America

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Chile will have a lower child mortality

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thank you but within some few years from

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now and here we have high-income

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countries in OECD and we get the whole

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pattern here of the world which is more

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or less like like this and if we look at

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it how it looks the world in 1960 it

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starts to move 1960 this is mouths a

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tomb he brought health to China

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and then he died and then thanks your

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ping came and brought money to China and

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brought them into the mainstream again

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and we have seen how countries move in

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different directions like this so it's

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sort of sort of difficult to get an

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example country which shows the pattern

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of the world but I would like to bring

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you back to about here at 1960 and I

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would like to compare South Korea which

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is this one with with Brazil which is

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this one the label went away for me here

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and I would like to compare Uganda which

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is there and I can run it forward like

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this and you can see how South Korea is

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making a very very fast advancement

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whereas Brazil is much slower and if we

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move back again here and we put on

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trails on them like this you can see

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again that the speed of development is

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very very different and the countries

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are moving more or less in the same rate

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as money and health but it seems you can

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move much faster if you're healthy first

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than if you are wealthy first and to

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show that you can put on the way of

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united arab emirate they came from here

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a mineral country they catch all the oil

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they got all the money but health cannot

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be bought at the supermarket you have to

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invest in health you have to get kids

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into schooling you have to Train health

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staff you have to educate the population

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and sheikh zayed did that in a fairly

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good way and in spite of falling oil

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prices he brought this country up here

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so we got a much more mainstream

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appearance of the world where all

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countries tend to use their money better

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than they used in the past now this is

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more or less if you look at if you look

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at the average data of the countries

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they are like this now that's dangerous

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to use average data because there's such

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a lot of difference within countries so

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if I go

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look here we can see that Uganda that

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today is where South Korea was 1960 if I

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split Uganda there's quite a difference

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within Uganda these are the quintiles of

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Uganda the richest 20% of Uganda's are

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there the poorest are down there if I

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split South Africa it's like this and if

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I go down and look at Nigeria where

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there was such a terrible famine lost

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Lee it's like this the 20% poorest of

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Nigeria is out here and the 20% richest

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of South Africa is there and yet we tend

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to discuss on what solutions there

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should be in Africa everything in this

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world exists in Africa and you can't

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discuss universal access to HIV for that

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quintile up here with the same strategy

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as down here the improvement of the

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world must be highly contextualized and

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it's not relevant to have it on regional

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level we must be much more detailed we

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find that students get very excited when

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they can use this and even more

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policymakers and the corporate sectors

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would like to see see how the world is

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changing now why doesn't this take place

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why are we not using the data we have we

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have data in the United Nation in the

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National Statistical agencies and in

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universities another non-governmental

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organization because the data is hidden

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down in the databases and the public is

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there and the internet is there but we

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have still not used it effectively all

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that information was so changing in the

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world does not include publicly funded

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statistics there are some webpages like

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this you know but they take some

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nourishment down from the databases but

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people put prices on them stupid

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passwords and boring statistics and this

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won't work

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so what is needed we have the databases

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it's not a new database you need we have

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wonderful design tools and more and more

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I added up here so we started a

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non-profit venture which we called

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linking data to design we call it

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Gapminder from London Underground where

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they warn you mind the gap so we thought

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gap mind was appropriate and we started

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to write software which could link the

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data like this and it wasn't that

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difficult

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it took some person years and we have

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produced animations you can take a data

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set and put it there we are liberating

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you and data some few UN organizations

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some countries accept that their

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databases can go out on the world but

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what we really need is of course a

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search function a search function where

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we can copy the data up to a searchable

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format and get it out in the world and

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what do we hear when we go around I've

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done anthropology on the main

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statistical units everyone says it's

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impossible this can't be done our

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information is so peculiar in detail so

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that cannot be searched as other can be

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searched we cannot give the data free to

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the students free to the entrepreneurs

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of the world but this is what we would

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like to see isn't it the publicly funded

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data is down here and we would like

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flowers to grow out on the net and one

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of the crucial point is to make them

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searchable and then people can use the

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different design tool to animate it

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there and I have a pretty good news for

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you I have a good news that the present

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new head of UN statistic he doesn't say

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it's impossible he only says we can't do

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it

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and that's a quite clever guy so we can

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see a lot happening in data in the

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coming years we will be able to look at

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income distributions in completely new

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ways this is the income distribution of

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China 1970 this is the income

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distribution of the United States 1970

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almost no overlap almost no overlap and

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what has happened what has happened is

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this the China is growing it's not so

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equal any longer and it's appearing here

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overlooking the United States almost

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like a ghost isn't it it's pretty scary

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but I think it's very important to have

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have all this information we need we

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need really to see it and instead of

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looking at this I would like to end up

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by showing the Internet users per 1000

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and this software we access about 500

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variables from all the countries quite

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easily it takes some time to change for

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this but on the accesses you can quite

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easily get any variable you would like

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to have and the thing would be to get up

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the database is free to get them

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searchable and with a secondly to get

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them into the graphic formats where you

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can instantly understand them now the

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statisticians doesn't like it because

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they say that this will not this will

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not show the the reality we have to have

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statistical analytical methods but this

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is hypothesis-generating

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I end now with a world where the

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internet are coming the number of

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Internet users are going up like this

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this is the GDP per capita and it's a

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new technology coming in but in

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amazingly how well it fits to the

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economy of the countries that's why the

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$100 computer will be so important but

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the nice tenders it's as if the world is

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flattening off isn't it these countries

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are lifting more than the economy

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and will be very interesting to fall of

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this over the year as I would like you

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to be able to do with all the publicly

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funded data thank you very much what if

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great ideas weren't cherished what if

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they carried no importance or held no

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value there is a place where artistic

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vision is protected where inspired

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design ideas live on to become ultimate

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driving machines

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you

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