FP7 – EuroBroadMap Analysis of Question B EUROBROADMAP PROJECT - FP7-SHS Visions of Europe in the World Claude GRASLAND (CNRS) Timothée GIRAUD (CIST) Laurent BEAUGUITTE (CNRS)

A Worldwide survey 18 Countries 43 Cities 9341 Students Arts Business Politics Engineer Health Social Science

The concepts of knowledge and asymetry A. GENERAL FRAMEWORK EUROBROADMAP PROJECT - FP7-SHS Visions of Europe in the World The concepts of knowledge and asymetry

General framework for analysis DO NOT MENTION … WOULD LIKE TO LIVE IN … WOULD NOT LIKE TO LIVE IN … LIVE OR HAS LIVED IN ..

(1) Analysis of countries quoted DO NOT MENTION … WOULD LIKE TO LIVE IN … WOULD NOT LIKE TO LIVE IN … LIVE OR HAS LIVED IN ..

(2) Analysis of countries knowledge or ignorance DO NOT MENTION … WOULD LIKE TO LIVE IN … WOULD NOT LIKE TO LIVE IN … LIVE OR HAS LIVED IN ..

(3) Analysis of countries appreciation by origin DO NOT MENTION … WOULD LIKE TO LIVE IN … WOULD NOT LIKE TO LIVE IN … LIVE OR HAS LIVED IN ..

Knowledge: Example of Tunisia

Knowledge: Comments on Tunisia France is quoted in 1st rank by 79% of Tunisian, which is more than usual (51%) USA are quoted in 2nd rank by 53% of Tunisian, which is a bit less than usual (60%) Neighbours countries are over-mentionned ( Algeria, Lybia, Egypt, Italy …) Iraq and Iran are less mentionned than usual (which means less negatively …) Etc…

Knowledge: general results

Knowledge: General results

Asymmetry: Example of Tunisia

Asymmetry: Comments on Tunisia Some countries are more positive for Tunisian : ex. France (+0.95 instead of +0.67) Some countries are less positive for Tunisian : ex. UK (+0.31 instead of +0.77) Some countries are more negative for Tunisian : ex. Morocco (-0.36 instead of -0.05) Some countries are less negative for Tunisian : ex. Iran (-0.56 instead of -0.95) Some countries reverse from negative to positive : ex. Turkey (+0.83 instead of -0.37) or Syria (-0.95 to +0.57)

Asymmetry: General results

Asymmetry: General results

K & A : Example of Tunisia

K & A: Example of Tunisia

Legend of the maps In which countries would you like to live in the near future ? The SIZE of circles should be proportional to the degree of KNOWLEDGE by students. The COLOUR of circles should be related to ASYMMETRY. With opposite colours for LIKE and DISLIKE.

WORLD MAPS (Tunisia)

ZOOM MAPS (Tunisia)

ANAMORPHOSIS From … The SIZE of countries should be proportional to the degree of KNOWLEDGE by students. The COLOUR of countries should be related to ASYMMETRY. With opposite colours for LIKE and DISLIKE. … to

ANAMORPHOSIS (Tunisia)

B. COMPARISON OF MENTAL MAPS OF STUDENTS EUROBROADMAP PROJECT - FP7-SHS Visions of Europe in the World Empirical analysis of states where students would like or not like to live

OLD MEMBER STATES

France

Belgium

Sweden

Portugal

NEW MEMBER STATES

Malta

Hungary

Romania

EASTERN NEIGHBORHOOD

Moldova

Turkey

Azerbaïdjan

Russia

SOUTHERN NEIGHBORHOOD

Egypt

Tunisia

Senegal

Cameroon

BIG EMERGING COUNTRIES

Brazil

India

China

SYNTHESIS ???

Typology of world states

Correlation between positive visions (LIKE) Cameroon & Senegal Egypt & Tunisia CHINA INDIA EUROPEAN UNION RUSSIA BRAZIL

Correlation between negative visions (NOT LIKE) Cameroon & Senegal CHINA BRAZIL Turkey WESTERN EUROPE Egypt & Tunisia EASTERN EUROPE & RUSSIA INDIA

C. MODELIZATION OF STUDENTS PREFERENCES EUROBROADMAP PROJECT - FP7-SHS Visions of Europe in the World Which factors can explain the countries where students would LIKE to live ?

Qualitative assumptions Because they have heard of the country Because it is rich Because it is open to migration Because it is not far Because it has historical linkage Because it has a common language …

Quantitative formalisation

(1) Size effect Hypothesis: BIG countries are more attractive than SMALL countries. 83 2

(1) Size effect H1 is true for all countries with very high level of significance

(2) Economic effect Hypothesis: RICH countries are more attractive than POOR countries. 59 20

(2) Economic effect H2 is true for all countries with very high level of significance

(3) Density effect (migratory policy) Hypothesis: EMPTY countries (open to migration) are more attractive than FULL countries (closed to migration) 48 16

(3) Density effect H3 is true for all countries but significant only for 6 out of 18

(4) Distance effect Hypothesis: NEAR countries are more attractive than REMOTE countries 188 47

(4) Distance effect H5 is true for all countries but not very significant for France and not at all for China

(5) Neighbourhood effect Hypothesis: CONTIGUOUS countries are more attractive than NON CONTIGUOUS 15 2

(5) Neighbourhood effect H5 is true only for France and Azerbaïdjan. The reverse hypothesis is true for Tunisia, Egypt, Cameroon and Russia.

(6) Language effect Hypothesis: countries with COMMON LANGUAGE are more attractive than others 11 3

(6) Language effect H6 is true and significant for the majority of countries. But it is sometime not significant and is reversed in the case of Azerbaijan

(7) Historical effect Hypothesis: countries with former COLONIAL RELATIONS are more attractive than others 59 188

(7) Historical effect H6 is true for some countries (India, Malta, Tunisia …) but reversed for others (Azerbaïdjan, Cameroon, Senegal).

D. FURTHER STEPS … EUROBROADMAP PROJECT - FP7-SHS Visions of Europe in the World

1. Benchmarking States / Cities

1. Benchmarking States / Cities

2. Countries focus (ex. USA)

2. Countries focus (ex.USA)