Construction of a longitudinal and intergenerational database Antwerp, Prof. K. Matthijs Dra. S. Moreels

2 History of the project (1) Research areas 1.Contemporary demographical and family sociological social structures and developments (marriage, remarriage, divorce, female labor participation, family functioning, etc). 2.Historical research: mainly 19th century Start of historical demographical projects: 1995 Main sources 1. Vital statistics (birth, marriage, death certificates) First step: ad hoc initiatives, taking into account different levels and timing of industrialisation, urbanisation, proletarianization and agricultural activities Towns: Aalst, Ghent, Leuven, etc. Small villages: Bierbeek, Poederlee, Appelterre, etc. Second step: structural strategies of data gathering on a broad geographical scale Towns: Antwerp Whole provinces: Western Flanders, Flemish Brabant Long run: Flanders (nothern part of Belgium)

3 History of the project (2) 2. Population registers Leuven Antwerp 3. Other sources General population censuses (“stock”-statistics) Agricultural and industrial censuses

4 Why Antwerp? (1)Data collection should begin in a big city for which less historical-demographical information is available and which can serve as a model for other regions. Antwerp was the city chosen for this purpose; (2)Antwerp was the logical choice for our focus because it was the fastest growing city of Belgium in the 19th century. That was mainly the result of massive immigration; (3)Due to their varying socio-economic and cultural background, the various groups of migrants wrote a different demographical history with respect to fertility, marriages, divorce, family formation, family networks, chain migration and death; (4)An interesting question is whether modern integration today is following (or will follow) the same path as in the past (that is the standpoint of the so-called ‘continuity school’), or whether the modern processes are unique (that is the standpoint of the so- called ‘uniqueness school’). The latter standpoint is based on the fact that the circumstances are now different: the welfare state is fully developed, there is a social security system, the migration policy is different.

5 Why ? (1)Pragmatic motive: reliable population accounting began in Belgium around the beginning of this period. The first official census of the independent Kingdom (1830) took place in The was the start of the opening of the first Population Register; (2)During the second half of the 19th century, the fertility transition reached cruising speed. The total fertility index fell from 4 or 5 in around 1850 to less than 2 in around With the Antwerp data, it is possible to reconstruct and interpret the transition, including the take off, the timing and the intensity of fertilty, mortality and nuptiality trends, respectively, for the native born and foreigners, for internal and external migrants, in a urban or semi-urban environment, and for both first, second and even third generations of migrants.

6 Features of the Antwerp data (1)It spans nearly six decades of time (1846 to 1920) and covers three generations; (2)The members of these generations are coupled; (3)The data base contains extensive micro-data on individual life courses and family patterns; (4)The information on individuals and their families is connected to a rich array of contextual data; (5)Given the fact that the groups of migrants are being followed over a period of time, it is possible to compare successive generations (the first, second and sometimes even the third generation) with each other and with the native population; (6)The intergenerational structure makes the sample unique for Belgium. The data base enables the investigation of questions regarding social and cultural change which could not be considered with any other Flemish data base,

7 Contexts for comparison (1) (1)Since the data relates to the entire district of Antwerp, urban processes can be compared with semi-urban and rural processes: (1)Native versus foreign-born populations (2)Metropolitan versus suburban long-term developments (3)Intra- and intergenerational comparisons (4)All of which can be situated within both national and international context; (2)The Antwerp immigration was often motivated by the employment opportunities at the port. Dock work is physically demanding and consequently there was a relatively high male labour migration to Antwerp. That as opposed to, for example, the developments in Ghent and Aalst where there was a greater ‘import’ of female labour in the textile sector. That difference allows one to make relevant comparisons of the interaction between gender, work sector and migration status;

8 Contexts for comparison (2) (3)For the period , the study group had access to all the information contained in the population register of Leuven. Therefore, it is also possible to draw a comparison between Antwerp and Leuven. Our comparative analysis may also incorporate the Walloon city of Verviers (data available from George Alter). These three cities provide a significant range of cultural, social and economic characteristics; (4)Moreover we are able to bring an international dimension to our comparative research. The Historical Sample of the Netherlands (hsn)-project for instance shares a number of features with the Antwerp sample.

9 Added value (1)Linking of a large number of data elements (from different sources) relating to individuals; (2)Reconstruction of family characteristics, sibling systems and life courses (migrant versus non-migrant, urban versus semi-urban and rural); (3)Supplementing the individual information with contextual data; (4)Development of an intra- and intergenerational longitudinal perspective (period ). This is really a new perspective that the Antwerp-sample brings to the study of migration and migrant reproductive behavior. We can indeed identify cor- subjects who lived in the Antwerp area before and after their migration. Only a few other data sets can do this.

10 Construction of the data base Procedure (1)Data collection started with the population registers. After that the data will be supplemented with information from the certificates from the Register Office (birth, marriage and death); (2)In order to make useful comparisons, information must not be collected from just the city of Antwerp, but from the entire district; (3)The information on individuals must be supplemented with socio- economic and cultural information at the regional and local level. The letter sample It was decided that it is best to work with an alphabetical sample, with selection on the basis of the surname. After analysis of the geographical and socio-demographical representative distribution of surnames, the letters COR were chosen. This represents 0.4% of the population.

11 The letter sample Choice of the letter sample: three reasons The letter combination COR: –Geographical distribution –Socio-demographic representativety –Language sensitiveness –Diversity in family names –Disadvantages of the letter combination Sample size: 0,38%

12 Sources Population registers 1846, 1856, 1866, 1880, 1890, 1900 and 1910 Vital registration records (certificates of birth, marriage and death)

13 Population Register: example

14 Data collection

15 Data cleaning First name cleaned + standardized to Latin variant Last name standardized according to 23 simple rules Place of birth standard municipality codes of the NIS or foreign code Date of birth (day/month/year)

16 Data linkage (1) First step (automatically) selecting potential pairs of observations by 13 queries Second step (semi-automatically) evaluating the potential linkages

17 Data linkage (2): second step Automatically –Positive decision (linking): full resemblance of family name, first name, birth-place and birth-date –Negative decision (not linking): match score < 8,8 Manually Individual coupling form in Access

18 Data linkage (3) + Check Third step (automatically) assigning new identification numbers (new ID’s) to the records Vital registration check Correcting & completing the database with birth, marriage and death certificates

19 Converting into a database From data-entry file to database: –1 table with all fixed information and ID –4 tables with variable characteristics of the individual and ID: Sequences: individual life cycles Marriage and civil state Kinship Events Abstracting analyse tables for research

20 Database structure

21 Extending the database Linking new information: two steps –Data cleaning and linkage of the new data: new table with unique persons –Linking the new table with the original database (selecting potential linkages, automatical and manual evaluation and assigning new ID’s to the linked records) Completing with the new vital registration records Converting into new analyse tables

22 Status Quaestionis