Europe and North America Regional GCED Network

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Graph 3 : Meeting network These three networks show some clear patterns. First, the division of two geographical areas is clearly visible in the network graphs; nodes of the same colors are closely located. Second, the organizations that did not respond, represented as squared nodes, are mostly located at the periphery of the network. This is the case for two reasons. First, they did not name ties as they were not being interviewed; therefore, their out-degree (number of outgoing neighbours) is 0. Second, few of the respondents named them as their ties, so their in-degree is very small (number of incoming neighbours). Third, there is no clear pattern between the dimension of the node (resources devoted to GCED) and its position in the networks. This suggests that the centrality in the network is not a function of the resources devoted to GCED. Chart 7 : Organization centrality and resources to GCED GCED resources and network centrality 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 between less than 20% 20% and 50% more than 50% Q1 centrality Q2 centrality Q3 centrality Q4 centrality 044ㆍ045
Chart 7 shows the distribution of institutions according to their beta centrality (Bonacich power), calculated on cooperation network, by resources devoted to GCED. We have organized the institutions in 4 quartiles as it allows us to understand the distribution of centrality better as it relates to resources. In the first quartile (Q1) are institutions that have the lowest level of beta centrality as they are below the median. The second quartile (Q2) contains those with a median value. The third quartile (Q3) is the middle value between the median and the highest value. The fourth quartile (Q4) is composed of institutions that have the highest value of beta centrality. The main attribute that emerges as relevant in observing network characteristics is the geographical location of the organizations. In particular, organizations tend to create ties with others with the same geographical location. We systematically assess whether organizations tend to create more ties within the same geographical area by focusing on homophily. Homophily is a property commonly acknowledged in social network analysis literature. It refers to the fact that ties tend to be created with others that share similar characteristics (McPherson et al., 2001, Krackhardt, 1988). We measure homophily with the EI index: a measure of in-and-out-group preference. It subtracts the number of out-group ties from the number of the in-group ties, divided by the total number of ties (Everett & Borgatti, 2012). An EI score of -1 signifies complete homophily, i.e., the node has relationships only with in-group actors. A score of 1 signifies complete heterophily, i.e., the node is connected only with out-group actors. A score of 0 signifies a balanced number of connections inside and outside the group. In Tables 9, 10, and 11, a node (organization) is defined as homophilous when it has an EI index score ranging from -1 to -0.6, as heterophilous when it ranges from 0.6 to 1 and balanced when it lies between -0.5 and 0.5. The three tables below show how the geographical area EI index varies by typology of the organization across the three networks. Table 9 : Meeting network homophily by typology of organization 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Civil society organization Education institution Governmental body Inter governmental organization Thematic network balanced heterophilous homophilous Europe and North America Regional GCED Network
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Page 7 and 8: Executive Summary Global citizenshi
Page 9 and 10: characteristics. This network struc
Page 11 and 12: Introduction This report presents t
Page 13 and 14: About Studying Networks As mentione
Page 15 and 16: References Bourdieu, P. (1986). The
Page 17 and 18: knowledge development and critical
Page 19 and 20: from within the modern/colonial ima
Page 21 and 22: Monaghan, C., & Spreen, C. A. (2017
Page 23 and 24: informants are required to nominate
Page 25 and 26: Possible examples of typologies of
Page 27 and 28: We adopted a whole network design,
Page 29 and 30: The goals for the SNA are to define
Page 31 and 32: DEAR Multi-Stakeholder Group meetin
Page 33 and 34: We conducted four pilot interviews
Page 35 and 36: possible patterns of proximity. The
Page 37 and 38: McPherson, M., Smith-Lovin, L., & C
Page 39 and 40: Social Network Analysis Results In
Page 41 and 42: Chart 5 : Importance attributed to
Page 43: - Node position is determined by th
Page 47 and 48: We also analyzed whether organizati
Page 49 and 50: interaction. Table 13 illustrates t
Page 51 and 52: Table 16 shows that the vast majori
Page 53 and 54: Graph 5 : Technical/scientific info
Page 55 and 56: 3.2. Summary of main results In thi
Page 57 and 58: 4.1.2 Organization-keyword network
Page 61 and 62: International Policy Pink No Easy A
Page 63 and 64: egression analysis of dyadic data.
Page 65 and 66: 2.1. Methods and data set To unders
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Page 73 and 74: Another set of interconnected organ
Page 75 and 76: 5) Conclusion and Further Questions
Page 77 and 78: https://doi.org/10.1177/20563051156
Page 79 and 80: in this summary, we would like to h
Page 81 and 82: While some qualitative results emer
Page 83 and 84: Appendices Appendix A: List of Orga
Page 85 and 86: UNESCO Chair in Democracy, Global C
Page 87 and 88: Global Citizen 3610 @GlblCtzn Globa
Page 93 and 94: All organizations (as per list in A
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Appendix D: Question 14 Answers Ala
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Enabel; Engagement Global, GENE als
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CONTENTS 100 100 100 101 101 101 10
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2. How do the actors work individua
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Knoke, D. & Yang, S., (2008). Socia
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Name of organization Code (es 01EU,
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• Explain that the interview will
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advisable to skip the formal ethica
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Policy development & decision makin
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B: Sometimes one organization provi
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the study. Findings will be present
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9.3 Invitation letter Dear My name
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Europe and North America Regional G
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Europe and North America Regional GCED Network

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