Published on July 1, 2009
The social capital of migrants and individual ICT use. A comparative analysis of European countries Dr Frank Thomas FTR Internet Research Rosny-sous-Bois France Contact: Tel. +33 1 48 94 36 90 Email: email@example.com Abstract The free movement of people within the European Union is a major political objective in Europe as is the creation of a socially integrated Information Society. The link between social capital and access to ICT is tested for geographically mobile persons, migrants. Based on results from the EU project SOCQUIT the text reviews the state of the scarce research about migrants and their individual ICT use and the corresponding survey data. In a globalising world individual communications become a major tool to maintain links between migrants. A new definition of migrant is empirically tested, extending the simple equating of migrants with foreigners. Regular ICT use is then analysed under the effect of social capital, social trust, migrant status, controlled for socio-demographic variables. It emerges depending on social and context variables migrants more regularly use the Internet than non-migrants, as well the inverse. Migrants are close to others lacking the economic, educational, social and cultural resources that help in taking up the Internet. Using the Internet is linked to living with an extended network of weak links. The effects of social position and the focus an urban areas reflect the ongoing diffusion process. Deviations from this pattern are discussed for groups of countries, as well as demands for further research.
1 Introduction1 The free movement of people within the European Union is a major political objective in European policy to create a common European social space. Also, the EU’s research agenda strongly incites to use Information and Communication Technologies (ICTs) to further e- inclusion, i.e. social, economic, and cultural integration into the emerging Information Society. However, behind the political will is there any evidence that there is a link between the fact of being a migrant and the individual’s use of I? Do migrants differ from non- migrants in their ICT use? Here, stress is laid on the question: does social capital help in getting access to ICT? This is an eminently political question. Do the socially well-connected get more rapidly a place in the Information Society which would translate the social inequality into a technological inequality? In the backyards of the Information Society in this case social exclusion would be translate into e-exclusion, the contrary of what the European Union intends to achieve. The link between ICT use and social capital has been examined in detail in a number of studies, and the EU projects e-Living (Anderson 2004) and SOCQUIT (Social capital, quality of life and ICT) (Heres, Anderson, and Thomas 2006) are one of the latest. Here the specifics of a population are studied that might play a strategic role in Europe’s way to an inclusive Information Society. The following paper we shall first overview the policy context of the question at hand, review the research about migrants, social capital, and the use of ICTs, and then define the central research question. After a critical view on the official and survey data on migrants a multivariate analysis will scrutinise the major drivers of migrant’s regular ICT use. The paper will then discuss the results and its limits. Finally ways shall be proposed how to integrate the results into mainstream European research and policy. Although today European countries often do not consider themselves as immigration countries, in fact migrants are numerically quite important. The 1st January, 2005, in the European Union 459.5 million inhabitants lived in the borders of the recently extended Union. In 2002, there was a net migration balance of 1.7 mill. persons, or 3.7 per thousand inhabitants ((Bundesamt 2004, p.29)). This average statistic does not show the large variation between countries. In Cyprus and in Spain, in 2003, there were more than 17 immigrants per 1,000 inhabitants. However, in EU the mean rate is only at 4.7 immigrants per 1,000 inhabitants (European Commission 2005, p.74). To this a non-estimated number of illegal immigrants should be added. The immigrant rate is not an indicator for the level of foreign- born in a country as there is a certain geographical mobility of foreign migrants within the European Union which reduces the rate especially in the Mediterranean countries. The statistics show that migration can be an important phenomenon even if the numbers will not show the social effects a lack of migration or the contrary, a strong influx, can exercise. Though migration is a phenomenon as old as mankind and was particularly important during the industrialisation of the world economy in the late 19th century and beginning 20th century today international migrations are the demographic bottom-up side of economic and cultural top-down globalisation. There were large migration waves, but in Western Europe countries were more often the senders than the receivers of migrants so their culture was not challenged by newcomers. It is only with the forced migrations due to the First and Second World Wars and its consequences that migrants, though often from the same country or the same culture, became an issue. For instance, in Western Germany in 1950, one-fifth of the 1 The text is is based in part on SOCQUIT deliverable D11 [Anderson, 2006 #563] and further develops its ideas, see www.socquit.net
population did not live on the same territory in 1939. What is new today in Europe is the numerical size of the immigration, and its origin often from countries with a culture or ethnic background that largely differ from Europe. From 1960 to 1973, the number of foreign workers in Western Europe doubled from 3 to 6% of the workforce. After a standstill due to restrictions after the first petrol crisis immigration resurged. Now, a considerable part of immigrants are often asylum seekers or war refugees, for instance from what once was Yugoslavia. In the last decade in what is today the territory of the EU net migration rose from 1993: 826,000 to 2004: 1,852,000.2At the same period, the U.S. received a constant net migration of about 900,000 persons per year. That means that the countries of the European Union now receive a migration that is about at the same level as the USA which is a historic country of immigration. As a result of this continuing net immigration, in Europe outside the countries of the former Soviet Union the percentage of foreigners in the total population nearly doubled from 3.3% in 1960 to 6.4% in 2000 (United Nations p.24, Tab. II.1). The Policy Context The starting point of the current European immigration policy is the understanding that the European way of life can not be maintained in the future if the European economy will not be more competitive and, at the same time, socially more inclusive. Therefore, the European policy favouring the coming of the Information Society intends to promote the diffusion of Information and Communication Technologies (ICTs) to wider parts of the economy and fostering research and development in advanced ICT while deliberately counter-steering a socially unequal evolution of the European societies. The central notion for this policy is the so-called e-Inclusion. Initially, in the Lisbon Strategy in October 2001 the European Union understood with e- Inclusion a better integration of the elderly and the disabled into the information society, in providing ICT, training and other learning to disadvantaged people, promoting digital literacy, mainstreaming a gender equality approach in e-Inclusion policies. The ongoing eEurope2005 strategy extended this approach in trying to achieve an inclusive digital society. If the Information Society for all will be achieved it will provide economic opportunities for all and will thus minimising the risk of a 'digital divide'. Here, the European policy has to turn to the user and orient policy to the demand of specific social groups (as well as geographic areas). In 2005, the debate on the social implication of a competitive Europe in a globalising world has widened. A step in this direction has been made with the final report of the eEurope Advisory Group on e-Inclusion (eEurope Advisory Group 2005). The Advisory group understands e-Inclusion as “… the effective participation of individuals and communities in all dimensions of the knowledge-based society and economy through their access to ICT.” The Advisory Group recommends a policy oriented towards an empowerment of the citizen- user and not only to facilitate adoption and use. The new i2010 policy proposal “A European Information Society for growth and employment “ (COM(2005) 229) published in late 2005 does not fully follow these ideas as it is stresses more technology and economy as drivers and is less society-oriented, although a considerable way has been achieved compared with the first policy intentions in 2001. The recent i2010 proposal states that “the 2005 Spring European Council called knowledge and innovation the engines of 2 Data from Eurostat New Cronos: http://epp.eurostat.cec.eu.int/portal/page? _pageid=1996,39140985&_dad=portal&_schema=PORTAL&screen=detailref&language=en&product=Yearlies_new_popul ation&root=Yearlies_new_population/C/C1/C11/caa14608
sustainable growth and stated that it is essential to build a fully inclusive information society, based on the widespread use of information and communication technologies (ICT) in public services, SMEs and households.” This is another policy program to reach the Lisbon objectives of higher growth, more and better jobs and greater social inclusion by 2010 in an integrated manner. The new strategic framework promotes an open and competitive digital economy and emphasizes ICT as a driver of inclusion and quality of life. One of the three objectives proposed by the European Commission is “achieving an Inclusive European Information Society that promotes growth and jobs in a manner that is consistent with sustainable development and that prioritises better public services and quality of life.” The measures intends to make ICT products and services, especially public services, more accessible, to improve the quality of life of citizens through new ICT enabled medical and welfare services, and to make ICT systems easier to use for larger swaths of the population. Obviously, migrants can be understood as a population requiring integration because they may provide crucial advantages for the future Europe. E-Inclusion and migrants A large part of migrants can be understood as a social group that translates well the notion of a disadvantaged social category as well as a solution for a set of problem that Europe has to solve. The i2010 policy directive does not explicitly address immigration policy. However, if Europe wants to achieve an integrated Information Society migrants - which constitute about one in 10 inhabitants - have to form a part of it. This is also a conclusion of the eInclusion@EU project (IST-502553) that recommends to class migrant workers as one of seven important target groups in need of a better integration into the European labour market with the help of ICT. 3 Yet an inclusive Information Society comprises more than the question of work, even if it central; a full integration includes the Social, the Cultural, and the Political, too. Thus, the case of migrants can be used to measure the effective levels of inclusion of today's Information Society and analyse the reasons for the current divides. There is still some way to go to integrate migrant issues in European and national Information Society policy agendas. One example is the e-inclusion example of Ireland. In its policy against poverty and social exclusion the European Union incites member states to systematically report about national policy plans furthering social inclusion4. Yet even in Ireland, one of the few countries that explicitly includes migrants in their national inclusion policy and which shows an advanced level of ICT diffusion, electronic tools are not yet part of the instruments used to help migrants getting a job and better training (Minister for Social and Family Affairs, n.d.). As a traditional emigration country the Republic today faces serious social and cultural challenges due to the relatively strong influx of economic migrants, which are, contrary to other countries, seen as necessary and are welcomed. But ICT has not yet emerged as a tool in her policy plans. eInclusion@EU lists several examples in which ICT themes can be related to migrants: (i) the employment potential of multilingual migrant workers in teleworking, (ii) ICT as facilitator and assistant in social integration, (iii) access of migrants to technical infrastructure in public resource centres, (iv) special provisions for digital literacy of migrants, (v) ICT potentials for maintenance of contacts with the country of origin, as well as (vi) migrants and 3 http://www.einclusion-eu.org/Document.asp?MenuID=80 4 http://europa.eu.int/comm/employment_social/social_inclusion/naps_en.htm
transfer of work-related skills and qualifications. 5 Recapitulating, the e-inclusion of migrants can be seen as a social challenge, but also as the solution to the problem of an ageing population: Europe needs a larger active working population if it wants to maintain current living standards when a larger part of the population has retired. The inclusion of this population in the emerging Information Society becomes necessary if the expected solution should not become a problem. Current research results on migrants Two main research lines will be mentioned that can help to elucidate e-inclusion and migrants: The research on trans-national migration and on social capital and migration. But first it has to be defined what can be understood under social capital and under a migrant. What means “social capital” ? There is a long and ongoing debate on how to define and how to measure social capital and its links with ICT adoption and use which had been reviewed in (Ling, Anderson, Døffler, Frissen, Heres, Mooy, Pierson, and Thomas 2004). Social capital can be understood as an element of the social structure of a society based on the social interaction of its individual members and its voluntary organisations and on the social attitudes and values that support these interactions and are reinforced by them. Following Ling's et al. literature analysis social capital can be understood as composed of three sub-dimensions: Bonding capital: the informal, social relations in everyday life between people who know each other well. These are the strong links between kin, friends, and close acquaintances or colleagues. Bonding capital appears to necessary for creating a sense of identity and social belonging. Bridging capital: the social integration in formal, voluntary associations but also into the new forms of civic involvement, like informal self-help groups, single-issue citizen movements, and the like. In comparison to the strong links with family and friends social links in associations can be considered as weak. There are different levels of social involvement in associations. People can limit their involvement to a simple membership, that is, nominal membership. This can happen when someone wants to show his or her affiliation to an issue without further engagement. An active membership demands participating in meetings, or helping in sending out the membership bulletin, for instance. There is an obvious scale of engagement from simple membership to volunteering but which is not mutually exclusive: people can be simple member in one association and become member of the board in another. Social trust is closely linked to these forms of social life. Trust can be considered as a prerequisite to a civic engagement, or as a result of it. There are different forms of social trust: trusting well-known persons, for instance members of the own family, should be distinguished from trusting strangers, for instance people met in public transport. The latter form of trust is called interpersonal or generalized trust. Interpersonal trust can be learned in meeting strangers in voluntary associations, or through the parents in childhood. Putnam (Putnam 2000) posits that once people have learned to collaborate with strangers within an association they can then transfer the acquired trust to social life with strangers outside the protected world of an association. Very different from interpersonal trust is the trust in the institutions of a country. But trust in institutions helps to acquire trust in strangers as functioning (legal) institutions will guarantee that deviant social behaviour will be sanctioned. In this way, the social behaviour of an unknown individual becomes more predictable. So, a strong trust in institutions will facilitate interpersonal trust and, indirectly, 5 http://www.einclusion-eu.org/Document.asp?MenuID=80
bridging capital. Migrants or foreigners? Migrants are difficult to define, and should not be confounded with foreigners or minority members. Excluding inner-country removals migrants are, by definition, people that move, more precisely: residents of a country who declare to be born abroad. Foreigners are residents who do not have the citizenship of the country they reside. Thus, migrants can be foreigners but need not be. And foreigners need not to be migrants. The separate definitions are important as Central and East European history shows numerous examples where people stayed put while political borders moved, for instance after the demise of Yugoslavia. So, without any migration nationals became foreigners. A more socially realistic definition of what a migrant is should therefore integrate several aspects. Dimension of migrant status can be citizenship, the country of origin of the individual and of the parents; visible race, language spoken, subjective cultural identity, and religion, see (Lambert 2004). The advantage of the index Lambert creates from a selection of these indicators is that it can discover second-generation immigrants who might not be visible in official statistics based only on citizenship but who can feel being treated as a foreigner in everyday life. For migrants, their legal status will play a crucial role for their everyday life. There is quite a difference in the legal status and thus, the perspectives for their future social integration, of “Aussiedler” (ethnic Germans from East Europe, unobservable to official statistics because they are automatically considered as German nationals), EU residents, civil war refugees from former Yugoslavia, asylum seekers, refugees declared illegal and in custody attending deportation etc. – In addition, any illegal resident will, of course, remain invisible. Very often, in public discussions, all these categories are just used in completely exchangeable way. According to which migrant definition is used the size of the population can considerably vary. Getting a representative picture of migrants is expensive due to their small number. The case of resident foreigners is exemplary. Resident foreigners can be considered to be a minority in most of European countries. In most countries they represent less than one in ten residents, besides the special cases of the two small countries of Switzerland and Luxembourg with their high concentration of migrants of 19.8% resp. 36.9% of the resident population. Thus, to get a representative picture the small population demands either over sampling or large representative surveys. Both solutions are onerous and therefore, in standard European comparative surveys migrants – even if well sampled – are only covered at the expense of a considerable sampling error. In addition, there are difficulties in sampling with any geographically mobile individual and the issue of cultural differences also has to be taken into consideration. Interviewees who do not well understand the language of the questionnaire, i.e. in general the official language(s) of the country, are barred from participation. In the Candidate Countries Eurobarometer run by the European Commission up to 2003 residents with other than EU member state or Russian citizenships (in the Baltic states) have been screened. These deliberately set filters seriously distort the data, cannot be undone through weighting and thus considerably reduce the quality of the interpretation that can be run on the basis of these data. Lambert, in his critique of ethnicity and migration data in major comparative surveys concludes that the available data available is messy and problematic. He notes that it is difficult to develop a classification scheme for migrants that applies to comparative studies in a comprehensive but meaningful way . As a consequence for the following statistical analysis a migrant will have to be defined in multiple ways and in particular, a wider, more cultural definition than the restricted one based on citizenship will have to be adopted.
Trans-national migration A major line of research on migrants is currently focused on what is termed trans-national migration. Under the effect of globalisation today social structures get more fluid, people get less sedentary, and migration becomes part of the life experience of at least a certain part of the population. There is the theory that the migrant worker becomes the new condition of modern Man in the network society (Castells 2000), what Portes calls the bottom-up side of globalisation (Portes 1997). Also, since the end of Communism in Europe new wars, especially in the Balkans, created large waves of wartime refugees (Kaelble 2007; Migration 2005). It is not only the scope of migration that is changing but, according to researchers, also its form. Trans-national migration can be understood as a new form of diaspora, i.e. of the dispersed global settlement of an ethnic group, but at a more important scale than the historical, Jewish one. The diaspora as a way of living existed since the expulsion of the Jews from Palestine in 70 B.C. but its importance has grown. Trans-national migration emerged with the globalisation process starting in 1980s: mass transport became less expensive, mass media reached even lonely territories, the cost of communication technologies dropped considerably (Dufoix 2003). These processes together allowed that today, a part of migrants do not settle definitively once they arrived but continue to shuttle between country of origin and new home. Here the focus is on individual- or household-level communication use. However, trans- national migration at the level of the individual or the household is difficult to study with the data from survey research at hand: there are no data, neither from cross-sectional nor from longitudinal surveys that allow generalising. As this form of migration is more of an emergent phenomenon and sample sizes in international comparative, representative surveys are necessarily small current research on trans-national migration can hardly be representative. So, empirical studies up to now are qualitative in nature. Moreover, as work and organisational as well as mass communications are more visible and thus easier to study there is a general lack of research on private and residential communications of trans-national migrants (see for instance the EU project European Media Technology and Everyday Life Network EMTEL and its studies of diaspora communication). The implications of trans-national migration for communication patterns are several-fold: due to the shuttle process the migrant remains in his intermediate position between the old and the new world. As a potential consequence the acculturation process of a migrant into the new host society will slow down, and a strong demand for international communication and transport between the country of emigration and of immigration will emerge. The exchange between the sending and the receiving countries of migrants become less one-sided as migrants often work as innovation agents: they are the personified bridging capital, between the new and the old home country. The social innovation is that this phenomenon no longer is restricted to middle-class or elites, but can touch the underclass (Diminescu 1999; Portes 1997). The implications for social capital will be discussion in the following chapter. In short, trans- national migration can lead to more social cleavages and to more an opener, culturally more diversified society. Social capital and migration Another major research strand that interests here focuses on social capital. Social capital and communication studies can show a certain bias in favour of behavioural analyses which does not sufficiently reflect on the societal context of social capital. When it comes to migrants the bias has been attacked when the debate about the most appropriate integration measures for
migrants reached the debate on social capital and on social trust. New immigrants will in many cases differ from the host population and will initially increase the social inequality in a country. The question is: does social dissimilarity or diversity negatively influence the inclusion of migrants? Should migrants be made to rapidly assimilate to the culture of the new home country, as this is the case in the US or in France? Or should they retain a part of their culture of origin so that the host society will become multi-cultural? This is the immigration policy model of Canada and of Great Britain. The question of ethnic diversity at the level of a country can translate into more or less ethnically diverse networks at the individual and family level. Social capital can have its downsides when the social ties within a family or a neighbourhood become too exclusive, at the detriment of links to non-members that provide a bridge to other informal or formal networks (Portes and Landholt 1996). Thus an immigrant family’s supporting network which is necessary for mutual help and can provide identity, can become a cage which enforces conformity with social values of the country of origin (Janssen and Polat 2006). A strong bonding capital without an equally strong bridging capital can inhibit people to adapt to changes in the outside world, for instance accepting a new role of woman. Besides these structural reasons there can be negative effects of effective social capital. The Mafia is the best-known example of a high bonding capital among ‘The Family’ and a controlled bridging to the outside world. Another effect can be that trust becomes ‘enforceable’ which means that it is no longer voluntary, a result of positive experiences or a specific attitudes to fellow man but a result from social obligation the social control (Portes and Sensenbrenner 1993). The relative importance of inner-ethnic family bonds and voluntary associations in comparison to trans-ethnic social relations when marrying, playing sports or voting is a central concern in the current political debates about the relative merits of multiculturalism and or assimilation to a country’s way of life (Geißler 2003; Halm and Sauer 2006). Linked to this debate about the relative importance of bonding and bridging among migrants and their ethnic composition is the question of migrants’ bridging capital, in particular volunteering. When we look at the traditions of the originating cultures we are able to see that often there is not a strong tradition of volunteering among migrants. Also, the low social, educational and economic resources of the majority of working class migrants make it improbable that they will rapidly get involved. Tenants of an assimilation model such as Esser will not welcome the founding of immigrant associations because they are understood as an indicator of a ghettoisation process at work and might undermine the social cohesion of the host society in creating an ethnic underclass (Esser 2001; Halm and Sauer 2006). On the other hand, proponents of a multi-cultural model see the civic involvement as a stepping- stone to further inclusion, even if it initially is in socially exclusive migrant associations only (Halm and Sauer 2004; Hoppe 2003). These latter views can draw support from the experience that a social interest such as living as an immigrant has to be organised to be able to get introduced into the policy process in West European democracies (Hartmann 1992). So the question can be asked: does the civic engagement in separate immigrant associations slow down or accelerate the assimilation and integration process? A historical fact is that in the US, after their arrival, immigrants often lived in immigrant neighbourhoods and later dispersed in the country. This is an historical process whose reflection in space has been called “invasion and succession” by the Chicago school of social ecology. In the American society of immigrants the socio-spatial separation in “ghettos” or ethnic neighbourhoods with a concomitant organisation in ethnic associations was the typical way of social integration for the non-black population into mainstream society (Friedrichs 1977). If we can infer from a number of national policy programmes and accompanying surveys in fact, ethnic self- organisation appears to be the dominant frame of civic engagement in a first phase of integration followed later by a mixture of ethnic associations and membership in associations
of the host society (Halm and Sauer 2006; Huth 2003b; Niessen and Schibel 2004). The civic engagement of migrants is understood by the European Commission as an important leverage used against social exclusion, with the projects MEM-VOL Migrant and Ethnic Minority Volunteering, in the framework of the Community Action Programme to Combat Social Exclusion and the running project INVOLVE in the INTI policy field to integrate non-EU third-country nationals (Huth 2003a)6. POLITIS is yet another EU programme which employs civic involvement to advance the social inclusion of migrants (Cyrus 2005). The fact that a public policy programme is needed to promote volunteering and self-help of migrants (and ethnic minorities) already speaks for a problematic relation between migrants and civic engagement. Rarely in any of these programmes individual electronic communications are conceived or analysed as a means to communicate among or with migrants (an exception (d’Haenens 2004) cited in (Wal 2005). The research interest is more on mass media, be it through radio, TV, or the Internet (for instance, the EMTEL project (Georgiou 2003)). There is another caveat to be mentioned when it comes to the potential for inclusion arising from volunteering. There are probably considerable class obstacles in the way of using volunteering as a tool for better integration of migrants. Historically volunteering was, and even today more or less still is, a middle-class phenomenon (see for Germany, France, and the UK (Li, Pickles, and Savage 2005; Prouteau and Wolff 2004; Rosenbladt 2000)). However, a large part of today's migrants do not belong to the middle classes. So, they are in a disadvantaged starting position when it comes to civic engagement. From the late 19th century onwards a notable exception to the middle-class bias existed which helped to integrate workers and migrants in voluntary associations and which provided them a bridging capital: namely religious and ideology-based institutions. The Catholic, the Socialist, and the Communist socio-cultural milieus and their institutions overcame these class barriers. But today these milieus have lost much of their binding forces. So, it remains to be seen whether the involvement in associations can help migrants get socially more included. As national differences, particularly in social policy are known to be still important, inputting the national context into the quantitative models is understood to be important. The use of ICTs for interpersonal communication at the individual level by migrants has not yet been really treated in an empirical way that allows drawing general results. If existing at all, there are case studies, for instance (Paragas 2004; Pertierra, F.Ugarte, Pingol, Hernandez, and Dacanay 2002; Wolf and Gournay 2005). It is important to note that these studies all concentrate on mobile phone calling and text messaging, and not on email or chat use. In fact, a mobile phone being the most individual and at the same time (geographically) mobile communications means it adapts particularly well to people on the move. (Diminescu 2002) shows how well the mobile phone fulfils the need of continually up-to-date information on security and work of Romanian immigrants. When it was still illegal for them to enter EU members states and to work there the mobile phone allowed exploiting the smallest chance to advance and to fight for a better living. The case of trans-national migrants also confirms the weight of the ICT use for their lives: trans-national migrants are strong consumers of ICT services, and can act as diffusion agents for ICT in their countries of origin. With their desire to reduce cost for individual communications they can be very ‘innovative’ when it comes to both legitimate and illicit ways of reducing cost (Diminescu 1999). Trans-national migrants can be seen as an indicator for a heavily ICT-oriented population that might presage future ways of life and of communicating. There is a master piece in cultural and social studies that treats the trans-national communication of migrants at the beginning of the last century: the epoch making enquiry of 6 http://www.mem-volunteering.net
the acculturation of Polish peasants in North America used the letters exchanged between the Polish family left behind and the new home country as source material (Thomas and Znaniecki 1918-1920). As a result, the main lines of reasoning can be restated as: − Migrants can not be simply equated with non-nationals. A wider definition has to include the cultural dimension of migration. − The civic involvement of migrants can probably play a role in social capital but its exact importance has to be determined. − The results have to be interpreted with the knowledge in mind that the one-way trip from a sending to a receiving country is no longer the standard way of migration. − Individual ICT use of migrants is not well researched and should also integrate the use of mobile phones. The description of a migrant and a review of available survey sources The main difficulty with comparative social surveys when it comes to migrants is the multi- dimensional character of what can be considered to be a migrant, problems of sampling, and their small sample sizes. As a result of the discussion of the definition of the characteristics the term of migrant should not be confounded with a foreigner. The available comparative survey data sets allow more or less leeway and precision in working with a cultural definition of a migrant. The following comparison of the quality of representative survey data sets for the quantitative analysis of migrant behaviour shows that of all the recent data sets that cover a large majority of the analytical dimensions of the study only the first round of European Social Survey 2002/03 provides the smallest deviations from the official numbers which exclude an unknown number of illegal immigrants. Other surveys cannot match the advantages of the ESS 2002/03. The e-Living survey, which also covers the same dimensions, is slightly less recent and covers far less countries. Eurobarometer surveys had to be excluded because of the exclusion of foreigners from non-member states from the sampled population. The more recent, second round of the ESS which was published in September 2005 is of no use as it does not include the wealth of questions on civic engagement of its first round. Eurescom’s P903 fieldwork date from late 2000 already and did not include questions on quality of life. In other words, the quality of the sampling of foreigners or migrants is still a desideratum of survey research. The ESS allows to base the description of the migrant status on four indicators as Lambert proposes: (i) ha foreign nationality, (ii) having one or two parents born in a foreign country, (iii) speaking a language at home which is not one of the country's official languages, and (iv),self-definition as belonging to a minority group in the country, Table 1: Comparison of levels of foreign and migrant population in European official statistics and social surveys OECD EUROSTAT EURESCOM Lambert Source: New Cronos P903 EVS ESS (ESS) Indicator Citizenship Citizenship language citizenship citizenship migrants Field survey in: 2001 2001 2000 2001 2002/03 2002/03 Austria 8.8% 8.9% 1.4% 4.3% 22.0%
OECD EUROSTAT EURESCOM Lambert Source: New Cronos P903 EVS ESS (ESS) Belgium 8.2% 8.4% 11.2% 4.9% 18.0% Czech Republic 2.0% 5.1% 0.5% 0.4% 12.0% Denmark 5.0% 4.8% 12.4% 4.1% 2.4% 10.0% Finland 1.9% 1.8% 0.5% 1.6% 6.0% France 5.6% 5.6% 8.7% 1.4% 4.3% 25.0% Germany 8.9% 8.9% 6.7% 2.5% 5.0% 16.0% Greece 7.0% 7.0% 1.0% 5.3% 20.0% Hungary 1.1% 1.1% 0.2% 12.0% Ireland 4.0% 4.1% 1.4% 3.2% 12.0% Italy 2.4% 2.5% 5.9% 0.1% 0.3% 5.0% Luxembourg 37.5% 36.9% 37.3% 34.0% 55.0% Netherlands 4.3% 4.2% 21.4% 2.4% 1.9% 13.0% Norway 4.1% 8.1% 2.7% 11.0% Poland 0.1% 0.3% 0.0% 9.0% Portugal 3.4% 2.0% 2.0% 2.3% 8.0% Slovenia 2.3% 0.1% 0.1% 14.0% Spain 2.7% 3.3% 10.2% 2.6% 8.0% Sweden 5.3% 5.4% 4.2% 2.9% 19.0% Switzerland 19.7% 19.8% 10.4% 32.0% United Kingdom 4.4% 9.6% 3.0% 2.8% 18.00% Sources: (2005), data from (EURESCOM-P903 2001), (Lambert 2004). Data for Slovenia: (Slovenia 2005). Data for France: Census 1999. The outlier in the Dutch data for EURESCOM P903 incites to interprete them with caution. Lambert proposed to create a cumulative index based on these characteristics as well as on the country of birth of the respondent and the length of residence in the country. However as the analyses have proved, the index does not seem to differentiate for ICT use among migrants and non-migrants any better than the original, separate measures. For the sake of the analysis, as the necessary cell frequencies for a detailed study lack, the index was simplified: someone is called a migrant if he or she fulfils at least one of Lambert’s migrant indicators composing the index. If not, the person is classified as non-migrant. Classification of countries according to their social capital. A classification of the study countries seems to be helpful in order to take the societal contexts of migrant’s ICT use and its link with social capital into consideration. Often, a certain behavioural bias influences the analysis of migrant behaviour as if individual migrants do not live within a society, an economy, and a culture which they can influence but which also constrains individual action. Classifying countries on the basis of their levels of social capital should allow to shed some light on the common conditions of the choices and constraints of European moving towards a socially inclusive Information Society. There are several country classifications which cover parts of the three aforementioned dimensions. Esping-Andersen and his followers examine the societal context of social capital formation, the welfare regime. He based his three ideal types of welfare regimes on the dominant way of welfare delivery in a country, be it the welfare state, the market or the family (Esping-Andersen 1990). Leibfried further distinguishes a rudimentary, Latin model
(Leibfried 1992). And Räsänen extended this model to incorporate former Communist countries in Eastern Europe (Räsänen 2004). These typologies grounding in the institutional and policy structure can be confronted with a typology based on social agency of the individuals. Dekker and van den Broek succeeded in classifying Western societies by the scope and intensity of engagement in voluntary associations. They distinguished a set of countries with high nominal membership levels in the general population and high rates of volunteering among the members (Canada and the US), a second set with low membership rates and high rates of volunteering (basically the South European countries), and a third, intermediate one with high membership rats but low intensity, to be found in Scandinavia, West Germany and the Netherlands (Dekker and Van den Broek 1998). The authors are able to confirm in part the typology of welfare regimes because the institutional structure of a country and its social history interact with the social agency of its inhabitants. This is the case for the extremes constellations, the Scandinavian welfare states and the South European family-based welfare regime. The middle ground, the countries with a liberal, a corporatist, or a welfare regime in transformation, rests to be better explained. Another, more practical reason for classifying countries is the low number of people of specific types (such as migrants) in the available survey data sets. Regrouping countries on the basis of their similarity allows the aggregation of individuals across countries and thus acquiring larger sub-samples for more in-depth analysis. The variables that operationalise the analytical dimensions represent a somewhat limited choice as they are to mirror the substantive questions, be representative, cover large parts of Europe, and should be recent. The choice was made to base the analysis on the data from the high-quality European Social Survey 2003 as it covers social capital in detail, as well as a large selection of 20 Nordic, West and Central European as well as Latin and East European countries. Luxembourg was excluded as its small size would distort results. The missing data for the Czech and Swiss respondents had to be replaced by multiple imputation. . TABLE 2: Variables and data sources for country classification Dimension and its operationalisation Source Year of field study Bonding capital Mean number of weekly socialising contacts with family & friends ESS 2003 Family judged more important than friends (calculated) ESS 2003 Subjective importance of contacts with family ESS 2003 Subjective importance of contacts with friends ESS 2003 Bridging capital % Nominal membership in voluntary organisations ESS 2003 % Active membership in voluntary associations % Volunteering in voluntary associations ESS 2003 % Helping outside family, associations, work ESS 2003 Trust Mean Interpersonal trust ESS 2003 Mean trust in institutions with sanctioning power (police, legal ESS 2003 system)
To classify the countries based on their similarity a hierarchical cluster analysis using the variables shown in the preceding table was done. The procedure resulted in the following dendrogramme. Fig. 1: Dendrogramme of country clustering A clear dichotomy appears between countries with different forms of social capital. The theory of welfare regimes allows their easy description. There is a major group of countries from North and Central Europe, composed of countries with a social democratic, a liberal or a corporatist welfare regime, and another one from the Latin and East European countries, composed of familistic and transformation countries. Both major groups are each composed of two sub groups. The Northern group is composed of countries with a social democratic (Denmark, Norway, Sweden, Finland), or liberal background (Great Britain, Ireland, Switzerland), and a second one with a Corporatist welfare regime: Germany, Austria, Belgium, and the Netherlands. The Southern group consists of Latin countries, but also includes Slovenia and the Czech Republic, two East European countries who either have a long, though broken history of a civil society, or which never closed to Western European influences even when belonging to a Communist state, as in the case of Slovenia. In fact, the classification is not very pure as the group of the transformation countries consists of Hungary and Poland, but also of Greece. The four clusters can be described as follows: social-democratic and liberal countries are relatively weak in bonding capital but strong in bridging capital. The corporatist countries are slightly stronger in bonding and slightly weaker in bridging capital. Their specific trait is the
emergence of a new form of civic engagement in informal and self-help groups. Latin countries is clearly more family-oriented and lacks a strong civil engagement of its inhabitants. Transformation countries are clearly the most family-oriented as they need to replace the lacking welfare state and civil society institutions. All in all, the structure found here in other social capital studies based on a variety of sources (see (Esping-Andersen 1990), (Leibfried 1992), (Fenger 2005), (Delhey and Newton 2005), (Pichler and Wallace in print)). TABLE 3: Social capital forms and European country types Country type Social- democratic Transfor- & Liberal Corporatist Latin mation Bonding social capital - Socialising 26.4 33.5 34.2 56.8 - Importance of family 9.5 9.0 9.4 9.7 - Importance of friends 8.7 8.4 8.2 8.1 - Family more important than friends 33.9 43.3 50.8 60.0 Bridging social capital - Nominal membership 80.1 75.3 40.5 33.1 - Active membership 44.1 42.2 26.7 14.7 - Volunteering 24.8 21.9 10.6 8.8 - Informal & Self-Help 35.0 45.4 25.3 21.5 Multivariate analysis In the following sections an attempt is made to study whether being a migrant makes a difference when it comes to explain the different forms of social capital and of ICT use. Therefore, after introducing a set of influences that mirror the societal context, the individual resources and the different analytical dimensions the last variable introduced is always the migrant status. Tables show the odds of a change in the status of the dependent variable of regular ICT use in a logistic regression. The data source is the European Social Survey round 1 of 2002/2003 (2003). The independent variables are composed of a group of socio-demographic control variables, indicators for bonding and bridging capital and for trust, and migrant status. The indicators for bonding social capital are the weekly frequency of socialising with friends and colleagues, and the perceived importance of the family (on a 11-item scale) and with friends (dto.). To overcome the skewed distribution the variables were dichotomised into a reference group with the lower two-thirds of the distribution and the remaining higher third as the effect group. The indicators for bridging social capital are being a nominal member in at least one out of 12 different voluntary organisations, being an active member in them, and volunteering in any of them. The voluntary organisations listed were sports club or club for outdoor activities, an organisation for cultural or hobby activities, a trade union, a business, professional, or farmers' organisation, a consumer or automobile organisation, an organisation for humanitarian aid, human rights, minorities, or immigrants, an organisation for environmental protection, peace or animal rights, a religious or church organisation, a political party, an organisation for science, education, or teachers and parents, a social club, club for the young, the retired/elderly, women, or friendly societies, any other voluntary
organisation than the ones previously mentioned. Social Trust is measured with the standard question “[G]enerally speaking, would you say that most people can be trusted, or that you can't be too careful in dealing with people?” on an 11-point scale from “Do not trust at all” to “Complete trust”. Trust in institutions is measured by a composite index of the questions of trust in norm-setting and sanctioning institutions, i.e. the (national) Parliament, the legal system and the police. Respondents could answer on an 11-point scale from “Do not trust at all” to “Complete trust”. For the analysis the variable has been nationally standardised to reduce bias due to skew and national answer styles in opinion polls. ICT use, the dependent variable, has been operatioas regular use of the Internet and email for private purposes. Based on a question on the frequency of use, respondents were grouped into a reference group composed of non- and irregular users (usage less often than once a week) and users with weekly usage or more often, the effect group. Because of the small size of the sample for migrant internet users the following analysis can neither analyse the intensity nor the content of the use. Results It appears from the following four tables that regular use of the internet can best be explained by, in decreasing order of importance, − The resource equipment: above all social position (education and household income), the stage in life cycle (age, living with children), gender, size of community, − Elements of bridging capital: the extent of nominal as well as of active memberships, − Elements of bonding capital: in some of the countries the frequency of socialising with friends, relatives, and work colleagues, − migrant status − Social trust: interpersonal trust in some of the countries. As a main result in can be stated that after introducing the controls of resource equipment and social integration into the new society in countries with a strong ICT development (Denmark, Finland, the Netherlands, the United Kingdom) migrants have the same odds to regularly use the Internet as non-migrants. In several countries with a a strong young immigration that can work in IT-oriented jobs or that are accustomed to live with ICTs, such as in Norway or Ireland, ceteris paribus migrants are more often a regular Internet user than non-migrants. The contrary effect can be observed in Sweden, in Germany, and in Greece: here migrants are less probably regular Internet users than non-migrants. For Germany this might be explained by the visibly disadvantaged situation of the large population of Turkish origin. It is remarkable that in most of the countries educational attainment exercises the strongest of all the effects, before household income. In 2003, after half a decade of Internet diffusion, in all of the European countries studied the domestication of the Internet and email still followed the social hierarchy. The strong effects of age on Internet usage, present in all of the countries, as well as the effect of the size of community are all indicators for the Internet still being in a process of social and spatial diffusion process. Effective efforts to take the Internet to help the education of one's children, though well-known to incite parents to take the Internet (Lelong, Thomas, and Ziemlicki 2004), can only be observed in some social- democratic and liberal countries.
TABLE 4: Results from logistic regression on regular Internet use in social-democratic and liberal countries, by country United Denmark Finland Norway Sweden Kingdom Ireland Control variables Odds ratio Odds ratio Odds ratio Odds ratio Odds ratio Odds ratio Age group - 30-60 yrs 0.356*** 0.167*** 0.305*** 0.323*** 0.402*** 0.547** - 61 + yrs. 0.085*** 0.051*** 0.081*** 0.075*** 0.119*** 0.227*** Gender (male) 1.447* 0.92 1.853*** 1.489** 1.12 1.19 Living as a couple 1.11 1.26 1.28 0.79 1.18 1.401* Living with children in 1.36 0.88 0.99 1.57 1.15 0.74 preschool age Living with young children 1.51 1.679** 1.418* 1.552* 1.454* 1.04 Living with adolescents 1.31 1.471* 1.37 1.00 1.17 1.706*** Educational attainment - secondary level 2.149*** 2.098*** 2.911*** 2.2*** 3.424*** 2.834*** - tertiary level, degree 5.503*** 5.539*** 7.403*** 4.842*** 5.045*** 6.195*** Household equival. income - second quartile 1.27 1.16 1.24 1.689** 1.481* 1.10 - third quartile 2.316*** 1.747** 2.462*** 2.905** 2.874*** 3.034** - fourth quartile 3.693*** 3.815*** 3.871*** 6.738*** 6.105*** 4.23*** Size of community 1.31 1.95*** 1.822*** 1.22 0.85 1.904*** Social capital: bonding Informal socialising 1.648** 1.10 1.718*** 1.485** 0.78 1.14 Importance of friends 0.92 0.87 0.726* 0.669** 0.91 1.02 Social capital: bridging Nominal membership 1.06 1.26 1.461* 0.89 1.44 1.33 Active membership 1.37 1.392* 1.566** 1.378* 1.345* 1.29 Volunteering 1.612* 1.40 1.413* 1.05 1.31 1.22 Informal volunteering 1.15 0.91 1.02 0.87 0.87 0.95 Interpersonal trust 0.86 0.77 1.25 0.90 1.06 1.09 Trust in institutions 1.693*** 1.15 1.529** 1.527** 1.25 0.94 Migrant status - migrant 0.86 0.61 1.765* 0.658* 1.06 2.02* Sample size 1,237 1,741 1,918 1,753 1,723 1,572 Missing cases 269 259 118 246 329 474 Nagelkerke's R 0.40 0.47 0.48 0.47 0.46 0.41 Source: European Social Survey 2002/2003. Table show odds ratios, *p<0.05, **p<0.01, p<0.001 Comparing the impact of bonding and of bridging capital on ICT usage a general trend is not evident in every country. In some countries with a high social capital, as in Norway, the Internet connection correlates well with a socially well-integrated life. Here, the Internet helps more to maintain the socially weak contacts with voluntary associations than the strong bonding contacts with friends and family. This effect is even more visible in countries with a corporatist social structure, in Belgium, Germany, and the Netherlands.
Table 5: Results from logistic regression on regular Internet use in corporatist countries, by country Austria Belgium Germany Netherlands Control variables Odds ratio Odds ratio Odds ratio Odds ratio Age group - 30-60 yrs 0.325** 0.567** 0.259*** 0.432*** - 61 + yrs. 0.078*** 0.121*** 0.058*** 0.122*** Gender (male) 1.881*** 1.429* 1.06 1.543*** Living as a couple 1.12 0.80 1.27 0.94 Living with children in preschool age 0.64 1.02 1.05 0.74 Living with young children 0.98 1.11 1.28 1.27 Living with adolescents 1.32 1.586* 1.624*** 1.16 Educational attainment - secondary level 2.621*** 2.924*** 2.78*** 2.002*** - tertiary level, degree 4.837*** 10.443*** 7.11*** 4.013*** Household equivalence income - second quartile 1.531* 1.48 1.29 1.20 - third quartile 1.635* 1.654* 2.029*** 1.459* - fourth quartile 2.949*** 3.031*** 3.89*** 2.311*** Size of community 1.355* 1.44** 1.265* 1.07 Social capital: bonding Informal socialising 1.627** 1.35 1.22 1.08 Importance of friends 1.29 1.08 1.06 1.24 Social capital: bridging Nominal membership 1.19 1.451* 1.445** 1.589** Active membership 1.09 1.23 1.20 1.15 Volunteering 1.38 1.19 1.01 1.294* Informal volunteering 0.90 1.09 1.10 0.90 Interpersonal trust 1.601*** 1.33 1.331* 1.04 Trust in institutions 0.94 1.03 1.23 1.321* Migrant status - migrant 2.061** 1.07 0.684* 0.75 Sample size 1,305 1,305 2,208 1,960 Missing cases 952 594 711 404 Nagelkerke's R 0.38 0.43 0.38 0.32 Source: European Social Survey 2002/2003. Table show odds ratios, *p<0.05, **p<0.01, p<0.001 In the more family-oriented Latin social countries the regular use of the Internet only helps to maintain the weak contacts. Here family members are more prone to call another family member than send an email. In the several Southern and Eastern countries, in Spain, Greece, and in Hungary, the strong correlation of bridging capital indicators with regular Internet use will probably be due to a more elite-oriented recruitment of voluntary associations in these countries.
Table 6: Results from logistic regression on regular Internet use in Latin countries, by country Spain France Italy Portugal Slovenia Odds Odds Odds Odds Odds Control variables Ratio Ratio Ratio Ratio Ratio Age group - 30-60 yrs 0.303*** 0.448*** 0.523* 1.22 0.307*** - 61 + yrs. 0.057*** 0.143*** 0.153*** 1.11 0.072*** Gender (male) 1.902*** 2.017*** 2.668*** 0.92 0.99 Living as a couple 1.095** 1.33 0.79 0.80 0.64* Living with children in preschool age 0.82 0.91 2.37* 1.04 1.35 Living with young children 0.71 1.17 0.98 1.00 1.29 Living with adolescents 1.873* 0.99 1.54 1.583* Educational attainment 1.48 - secondary level 2.677*** 2.37*** 4*** 1.45 2.392*** - tertiary level, degree 9.487*** 5.957*** 9.438*** 9.2*** Household equivalence income - second quartile 1.44 1.593* 1.54 0.74 1.28 - third quartile 1.41 2.639*** 1.71 1.12 2.202** - fourth quartile 3.45** 3.097*** 2.498** 0.95 3.67*** Size of community 0.90 1.20 0.84 1.30 1.04 Social capital: bonding Informal socialising 1.43 1.09 0.99 1.69 0.80 Importance of friends 0.71 0.96 0.92 1.294** 0.84 Social capital: bridging Nominal membership 2.438*** 1.41* 1.634* 1.22 1.733** Active membership 0.99 1.21 1.46 3.04 1.506* Volunteering 0.65 1.01 0.94 1.166** 0.74 Informal volunteering 1.18 0.95 1.802* 0.48 1.01 Interpersonal trust 1.01 1.661** 1.09 0.815** 1.748** Trust in institutions 1.53 0.98 1.26 0.96 1.412* Migrant status - migrant 0.57 1.27 0.18 0.18 0.84 Sample size 861 1,209 590 893 1,116 Missing cases 868 294 617 618 404 Nagelkerke's R 0.47 0.40 0.41 0.12 0.45 Source: European Social Survey 2002/2003. Table show odds ratios, *p<0.05, **p<0.01, p<0.001 With a Nagelkerke’s R² of at least 0.32 and in most cases of more than 0.40 the country models explain ICT access of migrants remarkably well. At the same time the considerable loss of information due to missing data should incite to caution when interpreting the results, as do the small cell frequencies for some variables in the case of Portugal and in the transformation countries that lead to inflated odds ratios. A second major result is that with an increasing cultural and social integration into the host society migrants are also more inclined to get internet access. Today (i.e. in the year of the survey, 2003) the new communication technologies – including mobile communication – can help to overcome integration difficulties for migrants.
Table 7. Results from logistic regression on regular Internet use in transformation countries, by country Greece Hungary Poland Control variables Odds ratio Odds ratio Odds ratio Age group - 30-60 yrs 0.554* 0.273*** 0.169*** - 61 + yrs. 0.096*** 0.062*** 0.043*** Gender (male) 1.876** 2.241*** 1.22 Living as a couple 0.568* 0.276*** 0.77 Living with children in preschool age 0.93 1.13 0.453** Living with young children 1.15 1.06 1.811** Living with adolescents 1.48 1.669*
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