1. First names in the Netherlands from preferences of parents to socio-geographic representations Gerrit Bloothooft Institute of Linguistics OTS Utrecht University

2. Linguistics Groningen - 20052 The Netherlands  Population of 16 million people

3. Linguistics Groningen - 20053 A full population study  (almost) all children born since 1983 –first name –year of birth –family code –postal code  from the National Social Security Bank

4. Linguistics Groningen - 20054 A very rich source  3.5 million children (1983-1999)  1.9 million families  152.274 different first names –100.868 unique names –3.120 names with frequency > 100 represent 3 million children

5. Linguistics Groningen - 20055 Naming and subcultures Hypothesis:  There are subcultures with own naming preferences  These subcultures may relate to –culture/language (Frisian, Arabic, Turkish, Surinam, Antillean,..) –religion (Catholic, Protestant, Islam,..) –sociological status (education, income,..) –geography (urban, rural, regional,..)

6. Linguistics Groningen - 20056 Naming and subcultures Issue:  We don’t exactly know the subcultures nor their membership  Reversily: Can we identify subcultures on the basis of the first names given to children?

7. Linguistics Groningen - 20057 Naming and subcultures Research aims:  Identification of subcultures (and their naming preferences) on the basis of the first names of children per family  Study of the relation between these subcultures (first names) and socio- cultural and geographic factors

8. Linguistics Groningen - 20058 Note  Analysis (grouping) of first names on the basis of the choices of the parents NOT on any other scientific assumption

9. Linguistics Groningen - 20059 Contents  Method  Sets of first names  A map of name sets  Geographic distribution of name sets  Socio-cultural factors of name sets  Conclusions

10. Linguistics Groningen - 200510 Method (a chain of names)  Parents choose first names from a set that is popular in their subculture (relatives, friends, neighbors,..) (with higher probability)  This is informative only if there is more than one child (more than one name)  Pairs of first names (from a family) as unit for analysis

11. Linguistics Groningen - 200511 Method (a chain of names)  Family: Mark, Peter, Linda If Mark is popular in a subculture, then Peter and Linda may be popular as well Name pairs: Mark - Peter, Peter - Mark, Mark - Linda, Linda - Mark, Peter - Linda, Linda - Peter

12. Linguistics Groningen - 200512 Method (a chain of names)  Select all families with two or more children (1.17 million families, 2.81 million children)  Derive all pairs of first names (from a single family) (in all, 2.12 million different pairs)  Compute the frequency of each pair  The higher the frequency of a pair, the more likely the first names in the pair belong to the same set

13. Linguistics Groningen - 200513 Most frequent name pairs FrequencyPair of first names 1091JohannesMaria 790JohannesJohanna 754JeroenMartijn 727JohannaMaria …. 572MohamedFatima 459LarsNiels

14. Linguistics Groningen - 200514 Clustering of first names Example:  Esther –7.967 girls –12.973 brothers and sisters –276 times sister Judith (= 2.1 %)  Judith –4.828 girls –8.033 brothers and sisters –276 times sister Esther (= 3.4 %)  Geometric average (2.7 %) –A symmetric measure of relationship between the two names

15. Linguistics Groningen - 200515 Clustering of first names  Name pairs from a (subculture-related) set have the highest relation measure Esther: Judith2.7 Mirjam2.4 Ruben1.2 David1.1 Judith: Esther2.7 Mirjam1.6 Ruben1.0 Miriam0.8

16. Linguistics Groningen - 200516 Clustering of first names  Iterative procedure to find sets of first names  4.013 first names –frequency of a pair > 4  340 name sets  top-25 is most illustrative –2.887 first names –2.64 million children (75%)

17. Linguistics Groningen - 200517 Features of name sets  Period of maximum popularity –Traditional, Pre-modern (1950-1980), Modern  Language –Dutch, Frisian, English, American, French, Spanish, Italian, [Arabic, Turkish] –Common Western  Topic area –Nature, History & Culture, Old Testament  Length –Short (one syllable), long

18. Linguistics Groningen - 200518 A map of name sets  Presentation of a map of name sets –Based on mutual relations between name sets  The closer two name sets on the map, the more related the sets

19. Linguistics Groningen - 200519 Spanish & Italian Long American & English Short American & English Pre-modern English & French Names from the Old Testament Names from nature Names from history and culture Short modern Common Western Pre-modern Common Western FrenchScandinavian Pre-modern Dutch Short modern Dutch Traditional Dutch Short traditional Dutch Frisian

20. Linguistics Groningen - 200520 Dimensions Long Short Traditional Pre-modern Modern Foreign Common Western Dutch, Frisian

21. Linguistics Groningen - 200521 Spanish & Italian RICARDO Long American & English MICHAEL Short American & English Pre-modern English & French DENNIS KIM Names from the Old Testament DANIËL Names from nature IRIS Names from history and culture LAURENS Short modern TIM Common Western Pre-modern MARK Common Western FrenchScandinavian NIELS CHARLOTTEPre-modern Dutch JEROENShort modern Dutch BART Traditional Dutch JOHANNES | JAN Short traditional Dutch TEUN Frisian JELLE

22. Linguistics Groningen - 200522 Intermediate conclusion  Name sets can be identified but  What do parents have in common, who choose first names from the same set? –Geography –Religion –Income

23. Linguistics Groningen - 200523 Geographical analysis  Based on postal code (3.584 units)  Further grouping of name sets into –Foreign(24 %) –Traditional Dutch(12 %) –Pre-modern (11 %) –Short (11 %) –History & Culture( 6 %) –Frisian ( 2 %)

24. Linguistics Groningen - 200524 Spanish & Italian Long American & English Short American & English Pre-modern English & French Names from the Old Testament Names from nature Names from history and culture Short modern Western Pre-modern Western FrenchScandinavian Pre-modern Dutch Short modern Dutch Traditional Dutch Short traditional Dutch Short Pre-Modern Foreign Traditional Frisian History & Culture

25. Linguistics Groningen - 200525 Geographical analysis Characterize each postal code area:  Compute deviation from the grand average percentage (NL) for each name group  Most deviating name group gets that area

26. Linguistics Groningen - 200526 Frisian Pre-modern [rural] History & Culture [cities & suburbs, higher education, higher income] Short [Catholic, rural] Foreign [lower education] Traditional Dutch [Protestant, rural]

27. Linguistics Groningen - 200527 Conclusions  Full scale population studies are very promising (and the only way to reliably study naming patterns)  The existence of subcultures can be derived from naming within families  Many more details were found but could not be presented here  Comparable studies of neighboring foreign regions would add an interesting dimension

28. Linguistics Groningen - 200528 Contact  E-mail: Gerrit.Bloothooft@let.uu.nl  Homepage: www.let.uu.nl/~Gerrit.Bloothooft/personal  Mail: Trans 10, 3512 JK Utrecht, The Netherlands

29. Linguistics Groningen - 200529 Religion Catholic Protestant None Religion

30. Linguistics Groningen - 200530 Religion Lowest Highest Income

31. Linguistics Groningen - 200531 Education level Educational level Lowest Highest