CLUSTERING THE MIGRATION-RELATED-NGOS AND IMMIGRANT ASSOCIATIONS IN GREECE. A QUANTITATIVE APPROACH Apostolos G. PAPADOPOULOS1,*, Christos CHALKIAS2, Loukia-Maria FRATSEA3 1
Associate Professor, Department of Geography, Harokopio University of Athens, El. Venizelou 70, Athens, 17671, Greece. Tel. +30 210 9549318, Email:
[email protected] 2 Assistant Professor, Department of Geography, Harokopio University of Athens, El. Venizelou 70, Athens, 17671, Greece. Tel. +30 210 9549347, Email:
[email protected] 3 M.Sc Agronomist - Researcher, Department of Geography, Harokopio University of Athens, El. Venizelou 70, Athens, 17671, Greece. Tel. +30 210 9549318, Email:
[email protected]
ABSTRACT The paper provides an elaborated analysis of the main characteristics of the migration-related-NGOs and immigrant associations (ΙΜΑs) in Greece. The analysis is based on a quantitative research which was carried out in the period October 2009-February 2010. A total number of 375 representatives of migration-related social actors were interviewed, while a great deal of information regarding the objectives, the organizational structure and the activities of those actors was collected. At the end, the quantitative research can be considered as a census-like research which recorded nearly all migration related NGOs and IMAs operating in Greece. Through the utilization of various quantitative techniques the paper aims at constructing classifications of migration-related-NGOs and IMAs. Various data such as, for example, the type of social actor, the level of actions (local, regional, national), the number of salaried (and voluntary) staff, the number of members, the budget size and the objectives were used to classify and categorize the organizations under research. Finally, a Hot Spot Analysis is implemented in order to illustrate the spatial clustering of NGOs and IMAs. KEYWORDS NGOs, Immigrant Associations (IMAs), Concentration patterns, Clusters, Hot Spot Analysis, Greece. 1. INTRODUCTION Migration is a phenomenon that links together places, people and cultures. Migrants are participants in movements necessitating not only a reworking of identities but also a corresponding reshaping of the socioeconomic contexts in which they find themselves and the places through which they are moving. It is through processes of mobility that migrants modify their identities, simultaneously incorporating experiences of multiple locations and a variety of socioeconomic contexts. Much migration research has approached migrants as a labour force that moves in accordance with economic rationales, with migrant employment shaped by structural forces and the migrants themselves having only a limited impact (Castles and Miller 2009). Migration, diasporas and transnational citizenship studies have formulated trenchant critiques of the bounded and static categories of nation, ethnicity, community, place and state (Hannam et al. 2006). This has become possible through analysis of different types of migrant mobility, of the relationships between dwelling and mobility, and of the way transnational and diaspora networks and other connections are mobilized (Blunt 2007: 685). Immigrant participation in civil society is normally mediated by NGOs which are active on immigrant issues and/or through their own organizations which serve their short-term interests for helping their compatriots while they are gradually transformed to immigrant pressure groups. The relevant literature considers NGOs pivotal for the strategic orientation and restructuring of immigration policies in the developed countries (Sharry 2000; de Montclos 2007). On the other hand, IMAs are predominantly considered as a means for strengthening immigrants' integration through their civil and social participation as well as their political engagement (Danese 2001; Caponio 2005; Pero 2007; Caselli 2009; Pilati 2010). In the Greek case, IMAs have been depicted as weak organizations, while their limited participation in civil society is stressed (Gropas and Triantafyllidou 2005). Since the late 1980s Greece was rapidly transformed to a new immigration country, at a time when central and eastern European regimes collapsed. Many factors explain the transformation of Greece 414
into a recipient country. They include Greece’s geographic location as eastern gateway to the EU, with extensive coastlines and easily crossed borders. Though the situation at the country’s northern borders has greatly improved since the formation of a special border patrol unit in 1998, geographic accessibility remains a central factor in patterns of migration to Greece, a condition which among other phenomena facilitates circular migration from the Balkans. Another important factor has been the rapid economic change that since Greece’s accession to the EU in 1981 has narrowed the country’s economic and social distance from the northern European countries. The main bulk of the immigrants – mainly Albanians- arrived in the first wave of immigration to Greece (1990-1995), but many also came in the wake of the collapse of the enormous “pyramid schemes” in Albania’s banking sector in 1996. The second wave of immigration (1996-2001) involved much greater numbers of migrants from other Balkan states, the former Soviet Union, Pakistan and India. The recent waves (2002-2010) consist of undocumented immigrants from Africa and Asia who are mainly employed as seasonal labour or on precarious jobs. A recent estimate for Greece raises the number of immigrants to 1-1.2 million or 10 per cent of the country’s population and 12-14 per cent of the total labour force (Triantafyllidou 2010: 122). Although the consecutive regularization laws (1997-1998, 2001 and 2005) have resulted in legalization of a significant number of immigrants, there were nevertheless estimated to be 280,000 irregular migrants in Greece in 2007 (Maroukis 2009: 5). Much attention has been paid in recent years to immigration flows, mainly from Africa and Asia, because of the large numbers of undocumented immigrants being arrested in border areas and/or elsewhere in Greece. This paper is based on an empirical research carried out in the period of October 2009-February 2010 in order to provide a data base of all migration-related NGOs and Immigrant Associations (IMAs) operating in Greece. At a general level, the paper aims at depicting the mosaic of immigrant population groups and the patterns of their organizational behaviour. However, through the utilization of various quantitative techniques the paper aims at constructing classifications of migration-relatedNGOs and IMAs. 2. METHODOLOGY AND DATA The empirical analysis draws on the project “Data Collection for Non-Governmental Organisations (NGOs) and Immigrant Associations which are active in Greece”, which was co-funded by the European Integration Fund for Third Country Nationals (75 percent) and national resources (25 percent). The aim of the study was to collect and to organize data concerning the characteristics of NGOs which are active on issues of immigration in Greece and IMAs, in order to design relevant immigration policies. The research design was based on previous registrations mainly implemented within the framework of European programs or Community initiatives (i.e. EQUAL I and II), as well as databases of NGOs or IMAs held by several NGOs and/or by embassies of third country nationals (TCNs) in Greece. In addition, in order to locate and register all the organizations and to access the organisations that were created in the last years, the "snowballing" technique was followed. The data were collected through a semi-structured questionnaire which was addressed to the representative of NGO or Immigrant association and aimed at collecting information regarding the profile, the characteristics and their activities related with various aspects of immigration. More specifically, the method of face-to-face interview was followed, while when this was not possible (i.e. due to distance) the telephone interview was used. The empirical research was carried out in the period of October 2009-February 2010 and in total 375 questionnaires were collected. The material of those questionnaires offers a basis for a satisfactory description of the characteristics of social actors which are active on issues of migration and social integration of migrants. Initially the data of NGOs and IMAs were analysed statistically through the use of SPSS 16.0. A number of crosstabulations were carried out and Chi-square tests of independence were used. Moreover, the Spearman’s rho correlation coefficient was calculated in order to examine the association between ordinal variables. In order to visualize and analyse spatial patterns of migration-related NGO’s and IMAs, GIS technology was adopted. GIS-based spatial clustering has been adopted recently in various studies (Ceccato and Persson 2002; Sokal and Thomson 2006; Gavalas and Simpson 2007; Borruso 2008). The following GIS-supported procedures were implemented: a) Spatial Database creation, b) Geocoding – Aggregation of data, c) Visualization in the form of various thematic maps, and d) Assessment of spatial clustering. The spatial database was created in GIS context with the use of ArcGIS software package (Arctur and Zeiler 2004). This geodatabase consists of thematic layers 415
representing the administrative districts (area topology) according to the most recent Greek administration. Especially for the analysis of spatial clustering in Athens area we adopt a more detail sectorisation according to the more detailed post districts. Next, we precede to the geocoding and the aggregation of NGOs and IMAs data. For this task the address of NGO and IMA as well as the thematic layer of the reference polygons (post districts) were used. With this procedure the allocation of each NGO and IMA in the spatial background of the study area was implemented. Another reason for the selection of the post districts as the spatial unit for the spatial clustering analysis is the fact that they are designed to have more or less the same population. Thus, we ensure a homogeneous population distribution for all the spatial units of the study area. The visualisation and mapping of spatial properties of NGOs and IMAs dataset is the primary stage almost in every spatial immigrant analysis. Thus, the first stage of our analysis was the creation of various thematic maps of NGOs and IMAs rates. In order to implement hot spot analysis the Getis-Ord Gi* statistic for each polygon features was calculated (Getis and Ord 1992; Ord and Getis 1995). The resultant Z score indicates where features with either high or low values cluster spatially. A statistically significant hot spot is a feature with a high value surrounded by other features with high values as well. The local sum for a feature and its neighbors is compared proportionally to the sum of all features; when the local sum is much different than the expected local sum, and that difference is too large to be the result of random chance, a statistically significant Z score results. The Getis-Ord local statistic is given from the following formula:
Gi *
n
n
j 1
j 1
wi, j x j X wi n 2 n n w i , j wi , j j 1 j 1 S n 1
Where xj is the value of feature j, wi,j is the spatial weight between feature i and j, n is the total number of features, X is the mean value of xj, and S is given from the following formula: n
S
x j 1
n
2 j
X
2
The Gi* statistic for each feature in the dataset is a Z score. Figures 2(a,b) visualize the statistically significant hot spots (p-value < 0.05) for NGOs and IMAs. The calculations of Getis-Ord Gi* statistic, and the creation of all thematic and hotspot maps were implemented with the use of ArcGIS 9.3 software package. 3. RESULTS In this paper we will analyze the total number social actors related to migration. Taking into consideration the self-definition, but also the distinct roles that they possess as active social actors in the civil society, we have distinguished the recorded organizations in two general types: a) the NGOs which are founded mainly by natives, are involved in the implementation of EU programmes and offer their services to immigrants in general; and b) the IMAs, which are founded by immigrants and, in their majority, offer their services to specific foreign nationalities or immigrant groups. An important difference between the two basic types of social actors is that the majority of the NGOs have been founded in the past with only limited number of them to be newly founded, while IMAs, as immigrant groups, represent a relatively recent phenomenon (Table 1). More specifically, the number of NGOs which were founded before year 2000 represents the 61.2 per cent of total. Respectively, the three quarters (73.5 per cent) of the total of immigrant associations were founded in the post-2000 period, a fact which is connected to some extent with the increase of the immigrant population in general, but more importantly to the rapid expansion of legal immigrants in the country. According to the latest Population Census (2001) the majority of the foreign population in the country is concentrated in Attica region, while an important percentage resides in Central Macedonia, 416
in Peloponnese and in Central Greece (Table 2). This geographic distribution is confirmed with minimal exceptions with the regional distribution of residence permits of TCNs. At the same time, the majority of NGOs and IMAs are concentrated in the major urban centers of the country and particularly in Athens. Hence, the 93.3 per cent of NGOs and IMAs are concentrated in five regions. Attica includes the overwhelming majority (77.3 per cent), while an important number of social actors were recorded in Central Macedonia (5.6 per cent), in Crete (4.8 per cent), Western Greece (3.2 per cent) and Thessaly (2.4 per cent). Table 1: Distribution of NGOs and IMAs according to their year of foundation NGOs Before 1990
IMAs
Total
36
20
56
23.2%
9.1%
14.9%
19
14
33
12.3%
6.4%
8.8%
32
30
62
20.6%
13.6%
16.5%
31
59
90
20.0%
26.8%
24.0%
37
97
134
23.9%
44.1%
35.7%
155
220
375
% 100.0% Source: Field research data 2009-2010.
100.0%
100.0%
% 1990 to 1994 % 1995 to 1999 % 2000 to 2004 % 2005 to 2009 % Total
Table 2: Geographical distribution of immigrant population and organizations (NUTS II) Region
Population Census 2001
Residence permits 2010
NGOs and IMAs 2009/2010 number %
number
%
number
%
Attica
370,218
48.6
210,200
40.5
290
77.3
Central Macedonia
100,178
13.1
78,123
15.1
21
5.6
Crete
40,424
5.3
34,005
6.6
18
4.8
Western Greece
35,144
4.6
25,800
5.0
12
3.2
Thessaly
31,957
4.2
35,403
6.8
9
2.4
North Aegean
9,711
1.3
7,945
1.5
6
1.6
Peloponnese
47,882
6.3
30,580
5.9
5
1.3
E.Macedonia & Thrace
15,146
2.0
12,872
2.5
4
1.1
Central Greece
39,397
5.2
29,787
5.7
4
1.1
South Aegean
28,112
3.7
19,377
3.7
3
0.8
West Macedonia
8,870
1.2
12,514
2.4
1
0.3
Epirus
15,692
2.1
12,524
2.4
1
0.3
Ionian Islands
19,460
2.6
9,545
1.8
1
0.3
Total 762,191 100.0 518,675 100.0 375 100.0 Source: NSSG, Population Census 2001. Ministry of the Interior, Decentralisation and E-Government, Residence permits of TCNs March 2010. Field research data, 2009-2010.
Figures 1a and 1b depict on the basis of their official addresses (including both the headquarters and branches) a more detailed geographical distribution of NGOs and IMAs respectively in the whole of the country. The overconcentration of NGOs and IMAs in Athens reflects the organizational and administrative culture in Greece. Athens is the administrative centre of the country and also a place of transit not only for the indigenous population but more importantly for the immigrant populations. It is worth saying that the activities range of NGOs and IMAs is significantly wider than their actual 417
headquarters. For example, in cases of emergency as in the recent case of the Evros river where most of the irregular immigrants use as a entry point into the country, a number of NGOs and IMAs are involved in actions related to the monitoring, the medical care and the support of the vulnerable immigrants groups.
Figure 1a: Geographical distribution of NGOs in Greece, Athens(a) and Thessaloniki (b)
Figure 1b: Geographical distribution of IMAs in Greece, Athens(a) and Thessaloniki (b)
This geographical distribution does not imply that there exists a linear relationship between the number of immigrants and the number of NGOs and IMAs at the regional level. Moreover, there are significant differences between the two types of social actors when considering their activities at different geographical levels. More specifically, virtually all IMAs are active at the local level (99 per cent), while an important percentage carries out actions at a regional (26 per cent) and national level (27 per cent). However, it should be underlined that the level of activity of NGOs is wider as in many cases it expands outside the national boundaries. Hence, the majority of NGOs has actions in local level (86 per cent) and at national level (57 per cent), while a large percentage is activated in transnational level (28 per cent) but only a small one (5 per cent) worldwide. The calculation of statistical correlations among the ordinal variables for the economic operation of NGOs and IMAs (Table 3) has shown that those organizations which have been established in earlier years tend to have more salaried staff (in years 2008 and 2009), and higher expenses in different years (2007 and 2008). The staff tends to increase in the course of the years, while there is a positive correlation among the size of the salaried staff and that of the expenses. Moreover, the size of the voluntary staff tends to remain important for different years. The expenses for the year 2007 have a strong association to the long operation of the organization, and also to the expenses for the year 2008. Finally, the size of expenses for the year 2008 is strongly associated to the size of the salaried staff for different years (2008 and 2009) and the size of voluntary staff for the year 2008. There is, therefore, evidence that the longer the NGOs and IMAs exist the more prone they are to employ a large number of salaried staff and therefore to maintain a sizeable budget for a different years. However, those significant findings do not reflect equally the situation in both types of social actors, i.e. NGOs and IMAs. More particularly, 59 per cent of NGOs but only 15 per cent of IMAs employ permanent personnel. A relatively even proportion of NGOs and IMAs have recorded their revenues and expenses (29 and 25 percent respectively), and a relatively even proportion employ parttime staff (83 and 95 percent respectively). All these remarks imply that the economic aspect is a major issue for both types of social actors, although each type has a different economic capacity. For
418
example, the NGOs tend to have an average of 2.3 million euro as revenue in the year 2008 against a mere 21,000 euro for IMAs.1 Table 3: Statistical correlations
Categories of Years of Operation Categories of salaried staff 2008 Categories of voluntary staff 2008 Categories of salaried staff 2009 Categories of voluntary staff 2009
Correlation coefficient Sig. (2-tailed) N Correlation coefficient Sig. (2-tailed) N Correlation coefficient Sig. (2-tailed) N Correlation coefficient Sig. (2-tailed) N Correlation coefficient Sig. (2-tailed) N Correlation coefficient Categories of Sig. (2-tailed) Part-Time staff N Correlation coefficient Categories of Sig. (2-tailed) Active Members N Correlation coefficient Categories of Sig. (2-tailed) Expenses in 2007 N Correlation coefficient Categories of Sig. (2-tailed) Expenses in 2008 N
Categories Categories Categories Categories Categories Categories Categories Categories Categories of Years of of salaried of voluntary of salaried of voluntary of Partof Active of Expenses of Expenses Operation staff 2008 staff 2008 staff 2009 staff 2009 Time staff Members in 2007 in 2008 1 -,329** -0,01 -,347** 0,054 0 -0,101 -,374** -,479** . 0 0,909 0 0,547 0,995 0,058 0 0 375 123 124 127 127 338 353 91 102 -,329** 1 0,108 ,832** -0,03 -0,089 0,116 0,183 ,712** 0 . 0,234 0 0,745 0,376 0,219 0,209 0 123 123 123 123 123 102 113 49 51 -0,01 0,108 1 0,034 ,839** 0,008 0,111 0,11 ,348* 0,909 0,234 . 0,708 0 0,936 0,241 0,451 0,012 124 123 124 124 124 103 114 49 51 -,347** ,832** 0,034 1 0,03 -0,04 0,152 0,093 ,556** 0 0 0,708 . 0,736 0,684 0,101 0,525 0 127 123 124 127 127 105 117 49 52 0,054 -0,03 ,839** 0,03 1 -0,046 0,082 -0,011 0,201 0,547 0,745 0 0,736 . 0,64 0,381 0,939 0,153 127 123 124 127 127 105 117 49 52 0 -0,089 0,008 -0,04 -0,046 1 0,082 -0,144 0,052 0,995 0,376 0,936 0,684 0,64 . 0,145 0,198 0,625 338 102 103 105 105 338 319 82 92 -0,101 0,116 0,111 0,152 0,082 0,082 1 0,008 0,075 0,058 0,219 0,241 0,101 0,381 0,145 . 0,941 0,46 353 113 114 117 117 319 353 89 99 -,374** 0,183 0,11 0,093 -0,011 -0,144 0,008 1 ,618** 0 0,209 0,451 0,525 0,939 0,198 0,941 . 0 91 49 49 49 49 82 89 91 90 -,479** ,712** ,348* ,556** 0,201 0,052 0,075 ,618** 1 0 0 0,012 0 0,153 0,625 0,46 0 . 102 51 51 52 52 92 99 90 102
Note:
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). Source: Field research data 2009-2010.
Focusing on the aims and objectives of the two types of social actors one may find significant differentiations between them. One basic difference between the two categories of social actors is that IMAs almost exclusively adhere to migration-related issues, while NGOs in many cases pursue mixture of objectives, along with the migratory issues. Moreover, the same social actor may simultaneously aim at different aspects of the migratory phenomenon. On this basis, the majority of the NGOs aim at defending the human rights (69.7 per cent) and the social integration of immigrants (67.7 per cent), while a significant proportion promote intercultural dialogue/multiculturalism (42.6 per cent) and the education/training of immigrants (41.9 per cent). On the other hand, IMAs aim mainly at the safeguarding of their culture (87.7 per cent) and at the support of their immigration community (83.6 per cent), while a significant proportion aim at the social integration (50 per cent) and education/training of immigrants (43.6 per cent). In brief, for IMAs the objectives of social integration signifies the social integration of the specific nationalities to which they address their services, while for NGOs social integration represents only a vague objective since it is considered in a horizontal manner and concerns the immigrant population in general. Furthermore, we proceeded with the visualisation and hot spot analysis of NGOs and IMAs data at the local level (Athens Municipality area). Figures 2a and 2b demonstrate the most important of these maps. In order to identify spatial patterns of NGOs and IMAs in the municipality of Athens we performed the spatial clustering analysis according to Getis-Ord Gi* statistic. This analysis evaluates the contribution of each location to the Global Getis- Ord statistic for the whole area. Figure 2 shows the cluster maps after 5% significance filtering, and 9999 permutations of randomization (Monte Carlo technique). These maps visualise the significant patterns by type of spatial association; here hot spot clustering (districts of high rates surrounded by districs with high rates). This analysis shows that hot spot clustering is much more solid for IMAs than NGOs. In Figure 2a we see scattered hot spots around the centre of the municipality, without any connecting pattern. Moreover, a significant surface 1
The standard deviation for NGOs is 6.3 million euro, whereas for IMAs is just 69,000 euro. 419
of the hot spot analysis is found in the centre and southern to the city centre. In Figure 2b we can identify a solid hot spot cluster in the central and northern part of the municipality (along the road axes of Patision and Acharnon streets).
Figure 2a: Hot Spots of NGOs in Athens
Figure 2b: Hot Spots of IMAs in Athens
Figures 2a and 2b of the two different types of social actors depict a situation which may be expected by migration researchers. Figure 2a illustrates that NGOs are scattered in the city centre due to the fact that they need to be connected to the immigrant populations, but also be in proximity to public services (e.g. ministries, municipal offices, etc.). Some of the NGOs are located to higher class neighbourhoods although they address their services to poorer immigrant groups. Figure 2b, on the other hand, depicts a more predictable situation concerning the IMAs and, to a significant extent, the immigrant populations. The pattern illustrated from the hot spot analysis of IMAs may be better explained when taking into account where immigrant groups reside and/or frequent. The centre and the northern axis of Kypseli, Patision and Acharnon and a northeastern axis to Ambelokipoi are the main residential areas of numerous immigrant groups. It is exactly in those areas that the IMAs are located indicating where immigrants live and/or gravitate.
Figure 3a: Distribution of African IMAs in Athens
Figure 3b: Distribution of Asian IMAs in Athens
Figure 3c: Distribution of European IMAs in Athens
The thematic maps in Figures 3a, 3b and 3c illustrate the spatial distribution of IMAs offering services to the main immigrant groups. Figure 3a depicts a distribution pattern of African IMAs nearly identical to the hot spot analysis map (Figure 2b). The African IMAs are located along the northern Patision and Acharnon axis, which has transformed into a major immigrant residential area. Figure 3b identifies a somewhat different spatial pattern for Asian IMAs which tend to concentrate around Omonoia Square. There are also concentrations of Asian IMAs in the eastern part of Athens municipality and even outside the borders of the municipality in the southeastern part towards Pireaus. Finally, Figure 3c depicts the concentration of European IMAs - containing eastern European and Albanians – which are more limited in number but also significantly scattered in Athens municipality and in the wider area. 420
4. CONCLUSION Greek migration research has focused on the study of the characteristics and integration issues that different immigrant populations face in Greek receiving society. On this basis, the study of migrationrelated NGOs and IMAs as intermediaries for immigrants’ integration, has significantly delayed. This paper is based on empirical material which is for the first time available in Greece and includes a wide range of information regarding the objectives, the operation, the organizational structure and the activities of NGOs and IMAs. The main finding of this paper is that despite the common characteristics between NGOs and IMAs, there are significant differences among the two types of social actors. Those differences become apparent not only by studying the objectives, the target groups that they aim at and the economic aspects of their operation, but more importantly when analyzing the socioeconomic and financial capacity of those organisations. The analysis of the spatial clustering of the two types of social actors has illustrated that each of them fulfils diverse operations within civil society and that IMAs, in particular, include important differentiations according to the different immigrant groups to which they provide services. Those findings may have important repercussions on the design and implementation of migration-related policies. Finally, possible expansion of our work could involve two major aspects: investigating spatial clustering by using alternative quantitative techniques (e.g. LISA method or spatial scan statistic) and exploring association between the spatial distribution of NGOs/ IMAs and various socioeconomic variables (e.g. regression analysis). 7. REFERENCES Arctur, D., and Zeiler, M., (2004), Designing Geodatabases: Case Studies in GIS Data Modeling, ESRI Press. Blunt, A. (2007), Cultural Geographies of Migration: Mobility, Transnationality and Diaspora, Progress in Human Geography, Vol. 31, No 5, pp 684-694. Borruso, G. (2008), Geographical Analysis of Foreign Immigration and Spatial Patterns in Urban Areas: Density Estimation and Spatial Segregation, Lecture Notes in Computer Science, Vol. 5072, pp. 415-427. Caponio, T. (2005), Policy Networks and Immigrants' Associations in Italy: The Case of Milan, Bologna and Naples, Journal of Ethnic and Migration Studies, Vol. 31, No 5, pp. 931-950. Caselli, M. (2009), Integration, Participation, Identity: Immigrant Associations in the Province of Milan, International Migration, Vol. 48, No 2, pp. 58-78. Castles, S. and Miller, M.J. (2009), The Age of Migration. International Population Movements in the Modern World, 4th Edition, London, Palgrave Macmillan. Ceccato, V. and Persson, L.O. (2002), Dynamics of rural areas: An assessment of clusters of employment in Sweden, Journal of Rural Studies, Vol. 18, No 1, pp. 49-63. Danese, G. (2001), Participation beyond Citizenship: Migrants' Associations in Italy and Spain, Patterns of Prejudice, Vol. 35, No 1, pp. 69-89. de Montclos, M-A. P. (2007), Humanitarian NGOs and the Migration Policies of States: A Financial and Strategic Analysis, in M. Korinman and J. Laughland (eds), The Long Marsh to the West, London, Vallentine Mitchell Academic, pp. 56-65. Gavalas, V.S. and Simpson, L. (2007), Segregation of ethnic minorities in two Districts of Greater Manchester, Genus, Vol. 63, No 1/2, pp. 119-148. Getis, A. and Ord, J.K. (1992), The analysis of spatial association by use of distance statistics, Geographical Analysis, Vol. 4, pp. 189-206. Gropas, R. and Triantafyllidou, A. (2005), Active Civic Participation of Immigrants in Greece, Country Report prepared for the EU research project POLITIS (available from http://www.unioldenburg.de/politis-europe). Hannam, K., Sheller, M. and Urry, J. (2006), Mobilities, Immobilities and Moorings, Mobilities Vol. 1, No 1, pp. 1-22. Maroukis, T. (2009), Undocumented Migration: Counting the Uncountable, Clandestino Country Report for Greece., Athens, ELIAMEP. Ord, J.K. and Getis, A. (1995), Local Spatial Autocorrelation Statistics: Distributional Issues and an Application, Geographical Analysis, Vol. 27, pp. 286-306. 421
Pero, D. (2007), Migrants and the Politics of Governance. The Case of Barcelona, Social Anthropology, Vol. 15, No 3, pp. 271-286. Pilati, K. (2010), Civic and Political Participation by Immigrant Associations in Italy. The Case Study of Milan, Revista Migracoes, No 6, pp. 145-159. Sharry, F. (2000), NGOs and the Future of the Migration Debate, Journal of International Migration and Integration, Vol. 1, No 1, pp. 121-130. Sokal, R.R. and Thomson, B.A. (2006), Population structure inferred by local spatial autocorrelation: An example from an Amerindian tribal population, American Journal of Physical Anthropology, Vol. 129 No 1, pp. 121-131. Triantafyllidou, A. (2010), Twenty years of Greek immigration policy, in A. Triantafyllidou and T. Maroukis (eds), Immigration in Greece of the 21st century, Athens, Kritiki (in Greek).
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