In order to increase their influence and achieve certain other goals, most organizations tend to collaborate with other organizations that they believe share their perspectives and attitudes (Portes et al., 2008). Ethnic organizations mostly base their activities on perceptions of common “routes” and “roots” and tend to collaborate with similar others, and thus have a quite homophilous collaboration network. However, when a violent armed conflict in the homeland arises, it can be brought closer to the everyday space of diaspora through modern media and globalization processes (Baser, 2015; Brubaker, 2005; Féron, 2017; Féron and Lefort, 2019; Jabri, 2007; Oberschall, 2000). For example, the development of modern media has allowed a lot of war and conflict-related events to be available and witness-able across the geographical spaces simultaneously (Ukrainian Revolution at the end of 2013 – beginning of 2014 has been streamed by multiple channels online; Mosul battle streamed online via Facebook, and others).
A lot of ethnic/diasporic organizations in this context may mobilize their activism in order to show their support for or discontent with the events, especially if they perceive themselves as a group under attack (Oberschall, 2000). For example, Féron (2017; Féron and Lefort, 2019) discusses the case of conflict-generated diasporas that emerge as a direct response to the armed conflict in the home country. In addition, Baser (2005) looks more closely at the realities of Turks and Kurds living in Germany and Sweden and compares their experiences, which lead to different outcomes for the relationships between the two groups in these specific contexts. Other research on the interconnection of war in the homeland and diasporas include multiple case studies such as Palestinian, Irish, Armenian, Tamil, Rwandan Tutsi diasporas as well as studies of intergroup relations in the country of settlement, e.g., Sikh–Muslim relations in Britain (Féron, 2017; Koinova, 2016; Moliner, 2007; and others). However, this type of research is still quite scarce, while most of the diaspora studies focus mostly on the ways in which diasporas can affect the peace-building processes in their home countries, as well as the political unrest that they can be a part of in the country of settlement (Demmers, 2002; Féron, 2017).
Nevertheless, all this research, among others, show that an ongoing armed conflict in the home country can have the potential to affect the collaboration networks, which different ethnic organizations build with each other. Thus, shared ethnicity can lose its importance in how an organization decides to form a connection with another, and shared attitudes about the conflict can become a leading mechanism in forming collaborations. In other words, an ethnically homophilous collaboration network may reorient itself into clustering by attitudes toward the conflict, and thus actively choose to become homophilious based on that perceived value. An organization can, therefore, give a lesser degree of consideration to collaborate with another one solely on the basis of that organization’s claim of ethnic belonging, and choose the collaborations based on the perceived agreement on the politics in the home country. Alternatively, there might be a reconfiguration of the meaning of ethnic belonging, namely the attitudes toward the conflict may become a substantial part of identifying the potential collaborator as a “true” co-ethnic or not, and thus leading to the action of working together or rejection of any association.
In this paper, I focus on the collaboration networks of Ukrainian, Russian, and Russian-speakers’ organizations in Sweden to see the effects that their identified ethnicity and stand toward the conflict may have had on their structure. I account for the Swedish context and trace the evolution of the network, including its growth through the creation of the conflict-generated organizations, i.e., organizations that both through their name and activity description claim the war in Eastern Ukraine to be their main focus, agenda, and reason for existence. I do not claim to see the causal relationship or to distinguish the exact impact of the war on the collaboration networks since I specifically focus on the 2014 through 2016 period that saw the beginning of war in Eastern Ukraine and was the most violent period in terms of casualties. However, I suggest that there are some indications that the reflections of war have at least been present in the studied collaboration networks and thus had a significant enough impact, especially in the Ukrainian organizations’ case. Focusing on this conflict is particularly interesting since it allows us to follow its development from the early stages onwards, as well as follow the changes in the diasporic communities, in the context of the relatively high freedom of organization that Sweden provides.
I suggest that the concept of homophily is useful to understand ethnic organizations’ collaboration before the armed conflict in Eastern Ukraine started, but the model of foci of activity is more applicable for the analysis of collaborations based on their attitudes toward the armed conflict. I suggest that engaging in activities that (do not) support a certain side in the conflict might have become a focus of activity for the organizations and reorganized the organizational field along the conflict lines that later became incorporated into the identification of the other organization’s ethnic belonging. Thus, ethnicity in terms of similar ideas on one’s “roots and routes” may become less steering for the collaboration decisions than identification with a certain side in the conflict.
The context of the study
Short background on the armed conflict in Eastern Ukraine
The current armed conflict in Eastern Ukraine can be traced back to the beginning of the Maidan Revolution in November 2013 when the protests against then President Yanukovych and the Parliament of Ukraine became large scale due to the President’s sudden decision not to sign a trade pact with the European Union. By late February 2014, there were more than a 100 unarmed protesters that were killed, after which then President Yanukovych fled the country and a new Parliament was established (UN Documents for Ukraine). In March 2014, the Russian Federation annexed the Crimean peninsula, an autonomous region within Ukraine, claiming its ethnic belonging as Russian and the “necessity of defending the Russians in Crimea” (address by President of the Russian Federation Vladimir Putin). Soon thereafter, Russian-backed rebels started an insurgency in two eastern regions of Ukraine: Luhansk and Donetsk (The World Bank: Conflict in Ukraine, 2017; OSCE statements). The most violent period of the conflict occurred in 2014 and 2015. July 2014 also saw the downing of the MH17 flight by Russian-backed insurgents in Eastern Ukraine (Crash MH17, 2014).
The World Bank Organization estimates that over 4 million people in Eastern Ukraine, specifically the Donbas region, have been directly affected by the continuing conflict (The World Bank: Conflict in Ukraine, 2017). According to a 2015 OCHA report, the number of casualties due to the conflict was 30,729, with 21,396 wounded and 9,333 killed (OCHA, 2015). By 2016, the number of those killed reached more than 10,000 (The World Bank: Conflict in Ukraine, 2017; UN Documents for Ukraine). In addition to casualties, 2.7 million people have been displaced. At the time of this writing, the official ceasefire has often been violated, and recent developments in the Ukrainian–Russian relations (Russia seizing three naval ships in the Azov sea in late November 2018) point to a new phase of the crisis (UN Emergency Security Council Meeting on Seized Ukrainian Vessels).
Swedish context: response to the conflict in Eastern Ukraine and Ukrainians and Russians in Sweden
Sweden is a country with a high level of participation in civil society, with an astonishing number of 251,000 “civil society” organizations, out of which 156,845 are non-profit (Statistikmyndigheten SCB). It is relatively easy to register an organization if it is non-profit, including even applying for funding through the state. Sweden is quite welcoming to different types of non-violent, non-terrorist, ethnic activism, which creates good grounds for practicing one’s ethnicity and taking part in homeland politics through demonstrations and other similar activities (Baser, 2015).
In the context of the Ukrainian–Russian conflict, Sweden has been very supportive of Ukraine. One example is the multiple visits by the Swedish foreign affairs ex-ministers Carl Bildt (March, 2014) and Margot Wallström in 2017. In addition, Sweden has been offering humanitarian, financial, technical, and even police training aid to Ukraine since the war unraveled, through organizations such as Sida and Riksbanken (The National Bank of Sweden) (Sveriges Riksbank and Sida: Ukraine). Moreover, within its Regional Strategy for Cooperation with Eastern Europe, launched in November 2014, Ukraine is the biggest recipient (European External Action Service – European Commission).
In 2018, there were 21,930 people born in the Russian Federation and 9,924 born in Ukraine living in Sweden (Statistikmyndigheten SCB). According to the Swedish Migration Office, of the people seeking asylum from Ukraine during the years of the conflict, only 32 applicants were approved in 2014 and just 29 in 2015 (Migrationsverket, 2017). Thus, it can be assumed that the Ukrainian population living in Sweden has not been significantly affected by migration due to the armed conflict in Eastern Ukraine. However, the economic and political situation of Ukraine has no doubt influenced the decision-making process of emigration from the country.
The history of Ukrainian and Russian populations’ settlements in Sweden is, to a great extent, speculative and mixed. Throughout the Soviet Union period, most people coming from any republic within the Union would often be counted either as Soviet or Russian. Therefore, it is not easy to describe a clear and distinct history of every population. However, some knowledge has been passed on, both through the official governmental institutions, organizations, and individual people. The information below is based on interviews with the representatives of different Russian, Russian-speaking and Ukrainian organizations, Russian and Ukrainian embassies, and Swedish Statistical Bureau.
When it comes to Ukrainians in Sweden throughout the twentieth century, one of the first bigger waves came as prisoners of the 1939 to 1940 Winter War between Finland and the Soviet Union as well as more coming during the later years of the Second World War. By the mid-1950s, the community had managed to create some organizations (Embassy of Ukraine in Sweden). Another wave of immigration to Sweden came with the collapse of the Soviet Union, and included mostly women. Thus, by 2000, there were 441 men and 1,018 women born in Ukraine living in Sweden (Statistikmyndigheten SCB). This statistics, however, has to be viewed with caution since the registration by country of birth might have been mixed up with accounts of registering Soviet Union and not a particular Soviet republic before the late Soviet Union collapse.
The first big wave of emigration from Russia in the twentieth century came with the First World War and the 1917 Revolution, following thereafter with emigration caused by the Second World War and finally, following the break-up of the Soviet Union. In the early 1990s, the Russian population in Sweden consisted mostly of women (Embassy of the Russian Federation in the Kingdom of Sweden). Thus, by 2000, there were 2,192 men and almost twice as much (4,331) women born in Russia living in Sweden (Statistikmyndigheten SCB).
Ukrainian and Russian organizations in Sweden also have interconnected, yet, distinct histories of existence in Sweden (most of this information is obtained from the interviews with representatives from the Ukrainian and Russian ethnic organizations). Many of these organizations were created before or after the Second World War, and some changed from the so-called Soviet “friendship” to independent nation-state-specific organizations. Most of them claim a very long history of existence even before they were (or formally could be) registered. Practicing activism based on cultural issues is rarely problematic in Sweden, and organizations that mostly focus on maintaining traditions and celebrations from the home country can easily apply for funding from the state to organize such activities. On the other hand, to be a completely politically focused organization or one primarily occupied with humanitarian or other aid can be limiting, in terms of funding from the Swedish state and require stronger argumentation. This is even more complex for openly political organizations (Lagar för ideell förening – Bolagsverket). Therefore, many organizations may find it easier not to register with the state, although they do exist and organize meetings and events for their members. Most of these organizations use online social media platforms, where they can freely converse and diverge from mainstream ideas and thoughts.
All in all, the Swedish context is one with a relatively high freedom of organizational engagement and expression, which makes it quite easy for the diasporic communities to organize and push their agenda, often relating to raising awareness about their homeland or their situation in the country of settlement. Therefore, studying the collaboration networks in this context is not limited by the legal or oppressive regime structures in which similar practices cannot take place.
Here, it is also important to note that diaspora organizations, although often claiming to represent the totality of the group rarely do so (Ragazzi, 2012). Most often, diaspora groups are comprised of people who have a very special connection to the idea of “homeland” and stronger ethnic identification than their average co-ethnic. Thus, this research cannot be generalized to the total populations of either Ukrainians or Russians in Sweden, but only to very specific diasporic organizations with a strong and institutionalized sense of ethnic belonging. In addition, the research opens an important arena for studies on inter-ethnic and diasporic relations in the times of war in the home country.
Homophily
The idea behind the concept of homophily is often summarized by a saying “birds of a feather flock together,” famously applied by McPherson et al. (2001) and relates to the phenomenon that people tend to become friends with people who share some similar characteristics with them. Homophily is an ambivalent process that makes the flow of information faster for similar others, while at the same time implies that this flow of information is localized and not different from whatever the similar others already share (McPherson et al., 2001).
McPherson and Smith-Lovin (1987) distinguished between choice homophily and induced homophily. In their discussions, induced homophily covers the effect of group composition that is homogenous on the individual pairings with similar others. Similarly, Blau (1977) proposed that patterns of relationships including homophily are guided by relative group size and ability to gain contacts for in- and out-group. In other words, the opportunity structure within the homogeneous group/organization that a pair is in dictates that the pair is also homogenous. Thus, in this view, baseline homophily reflects the composition at large and is affected by the relative size and pool of potential contacts. On the other hand, choice homophily is an individual bias or propensity to connect with similar others (Coleman, 1958; McPherson and Smith-Lovin, 1987; Marsden, 1988). In other words, the composition at large has no effect on the homophily patterns in the group.
Multiple studies have pointed to how homophily can be stronger or weaker for different types of ties as well as different socio-demographic or behavioral/attitudinal categories within the given context. When it comes to socio-demographic categories, such as sex, gender, age, or ethnicity, studies have been variable. In the case of gender, homophily is especially interesting since the group sizes at large are almost equal. The fact that gender homophily is strongly present in different societies and groups showcases that there is an individual or structural bias, since the organizational foci are gendered, as are workplaces and other activities (McPherson and Smith-Lovin, 1987; Eder and Hallinan, 1978). Marsden (1987) after controlling for kin showed that network composition of people with whom others discuss important matters is strongly gendered. Further, Ibarra (1992) found that men have stronger sex homophilous ties than women. Moreover, women with homophilous ties received support from other women and instrumental access through network ties to men, in her study of an advertising firm (Ibarra, 1992). When it comes to age, homophily patterns depend on the type of ties studied (McPherson and Smith-Lovin, 1987). In addition, since school classes are grouped by age, a strong baseline age homophily is induced (McPherson et al., 2001). Age homophily has also been shown to persist longer, most probably due to friendships formed at a younger age (McPherson et al., 2001; Marsden, 1987, 1988).
Homophily and ethnicity
Homophily based on ethnicity is a special case and has been explained by both contact opportunities (group size) and biases. Studies have shown that smaller ethnicized and racialized groups share more networks with majority groups (Blau, 1977; Marsden, 1988; McPherson et al., 2001). On the other hand, other studies (Marsden, 1987, among others) have shown that this pattern may be different for certain groups, where a smaller group shows a tendency for homophily despite the baseline expectation that smaller ethnic groups’ networks should include more majority group members. One explanation that these studies give for this anti-intuitive pattern is that some organizational foci are segregated by ethnicity and thus limit opportunities and create bias. Often, these overlap with social class and status. In the case of ethnic organizations, the process of defining ethnic belonging and cultural heritage becomes central and practical. These organizations are voluntary, and historically people have joined them in order to gain access to information networks and for work opportunities, among other things (Portes et al., 2008). Portes et al. (2008) write that in order to play a role in the nation-state politics on minorities, people often organize in a formal, stronger, way to exercise more power. Similarly, Ooka and Wellman (2006) in their study on ethnic groups in Toronto showed that newly arrived migrants tend to have more homophilous networks that can be explained by both ethnic segregation (of neighborhoods, voluntary organizations, language, schools, etc.) and hidden value homophily, like tastes and information. In the context of ethnic organizations, ethnicity is constantly made and maintained through various organized events and similar activities.
Scott Feld’s (1981) foci of activity model is both complementary and explanatory for the analysis. Feld suggests a theory of focused social ties based on the idea that social networks are organized through shared focus and joint activity. He states that individuals often have little choice in their association with certain foci. While some activities can be chosen by individuals who then create social networks around them (e.g., playing tennis), social foci can be better understood as social structures that systematically constrain the choices of relationship formations (e.g., only certain people play or want to play tennis). Thus, people who are tied to each other through their relations to these focal activities also tend to be homogenous in other characteristics. Feld derives three propositions from his model. First, since we meet to associate, most relationships originate in focused activities. Second, these foci are usually homogeneous. Third, if foci are homogeneous, the ties that are created there also tend to be homogeneous (McPherson and Smith-Lovin, 1987; McPherson et al., 2001).
The main basis of identification in ethnic organizations is (obviously) ethnicity, and since almost every organization’s activities evolve around the cultural heritage of the group they represent, it makes little sense for them to be heterogeneous in terms of collaborations with other ethnic organizations. Thus, unless two organizations share some similarities in their views on their “roots,” culture, or heritage, theoretically they should not have many reasons to collaborate. These similarities mostly relate to views on ethnicity and, in the case of Russian, Ukrainian, and Russian-speaking organizations, showcase a complex and specific ethnic boundary-making process. One example is Russian-speaking organizations, which can include people from almost every ex-Soviet country. Inclusion of different cultural and religious holidays in such organizations forms a pan- (often Slavic)-ethnicity that connects all the specificities. In the case of Ukrainian and Russian organizations, the question of “similarity” of traditions and culture in general has been a loaded political topic, especially during the last several years when the war unraveled. The boundary between Ukrainian and Russian identifications has shifted continuously and is usually drawn on language spoken and/or country of origin. In the case of ethnic organizations, where each represents a group of people that are homogenous, at least in terms of how they self-identify through ethnicity (as someone representing a certain culture through membership in an organization), the focus of activity is usually traditions from the “homeland,” such as dancing or celebrating religious holidays, and relates to an already established sense of ethnic belonging (see discussion of homophily). However, when the war in the homeland starts abruptly, mobilization of the sense of ethnic belonging may lead to reinventing different activities and renegotiating collaborations on the basis of the attitude toward the ongoing war. Ethnic organizations – due to their already strong connection to the idea of homeland (Jabri, 2007; Demmers, 2002; Vertovec, 1999) – may regard taking a stand as a necessary point of activity in relation to their identification with certain ethnicity. However, if it is relatively easy to assign ethnicity to an organization through the already existing name, for example, the attitude toward the war could become a more complex process that is also related to maintaining the established ethnic identification. This may require more work, and organizations might feel the pressure to become active in support of or discontent with the ongoing situation at home. Thus, the focus of their activities may shift, from primarily ethnicity-maintaining cultural events like celebrating shared perspectives on the history and traditions to relating primarily to the developments of the political situation currently ongoing at home.
Reorganizing the meanings of ethnicity through the focus of activity
Studies of ethnicity and inter-ethnic relationships usually tend to understand ethnicity as a characteristic at the core identity (Chow and Bowman, 2010). I believe taking the model of focused social ties (Feld, 1981) discussed above grants the possibility of studying ethnicity without these essentialist assumptions. It creates a theoretical possibility for understanding ethnicity and diasporic communities through action as constructed through maintenance of ethnic boundaries (Wimmer, 2008).
In the current study, I suggest that collaboration of ethnic organizations is often based on the perceptions of shared “routes” and heritage. However, in times of war in the homeland, a reorientation might take place, usually through activities such as demonstrations and different campaigns connected to the developments “back home.” In this way, the war in the homeland can become symbolically transported into the everyday of the diasporic organizations and thus become a focus of activity too. Often, in order to raise an awareness about the developments in the homeland, the best way for these organizations would be to gather as many people as they can. Hence, organize the similar others around them through activities related to the conflict that is happening thousands of miles away. At the same time, those who previously were non-political or even active at all might become mobilized to action as well. Therefore, the restructuring of the organizational field by the conflict attitudes might take place.
Put in other words, if the war in the homeland has no implication for the collaboration networks, they would probably be characterized either by same ethnicity pairs, or not dominated by ethnic identification at all (only structural network characteristics would matter for the collaborations in this specific case, such as, e.g., large and famous organizations would be more likely to receive invitations to collaborate). On the other hand, if collaborations tend to be dominated by pairs that share a similar attitude toward the conflict, this could be a potential indicator that the war in the homeland has had a shaping role in the evolution of the collaboration networks.
Hypotheses
H1 In this section, I aim to clarify three main hypotheses that follow from the theoretical discussion above:
H1 There is some collaboration between Ukrainian, Russian, and Russian-speakers’ organizations during the period studied. The collaborations are not dominated by organization pairs with the same ethnicity.
This hypothesis suggests that there is some collaboration between Ukrainian, Russian, and Russian-speakers’ organizations due to shared religion or traditions as well as, in some cases, a common spoken language.
H2 During the 2014 to 2016 period, Ukrainian organizations tended to collaborate with other Ukrainian organizations, and Russian organizations with other Russian organizations.
H3 Organizations might have collaborated with each other along the homogenous narrative of a shared past and/ or language, similar ideas on common “roots,” etc., only within clear ethnic boundaries. This hypothesis refers to the possibility that during the Revolution and subsequent war, this line of organizational collaboration remained the same. This scenario would showcase that while ethnicity is the main focus of the organizations, the developments in Ukraine were not reflected in the processes of network clustering.
Organizations that share attitudes relating to the conflict tend to collaborate more with each other than with organizations with other attitudes during the period studied.
In this scenario, organizational field of collaboration networks have reoriented from primarily subjectively identified ethnicity to standpoints on the armed conflict in Eastern Ukraine. Thus, the third hypothesis suggests that the armed conflict in Eastern Ukraine can be regarded as a focus of activity for Russian and Ukrainian organizations in Sweden (see Fig. 1).
Figure 1:
Focus of the conflict for diasporic organizations in another country, a model.
Data collection
The organizations researched in this study do not officially help with accommodation, work, or legal issues for the newly arrived migrants. The organizations that were created in the earliest period of critical developments in Ukraine (late 2013–2014) were concerned with the protests, assessing them either positively and showing support or negatively and treating the revolution as a coup – in the latter case often connecting it to Western political power struggles and conspiracies, or nationalist organizations active in Ukraine. Later, with the beginning of the armed conflict in Eastern Ukraine, a few organizations were created to send humanitarian help, among other activities, and some were created to spread information about the political developments in Ukraine.
Organizational network data collection started in early 2017. The network data were collected retrospectively through interviews and from official Facebook pages and websites of different Russian, Russian-speaking, and Ukrainian organizations. The main sampling method was to trace each organization from the connections of the previous one until the referrals led to the same organizations that were already in the database. The criteria for actors to appear in the network were: (i) the organization is Russian, Ukrainian, Russian/Ukrainian-speaking or active in connection with the conflict in Eastern Ukraine and (ii) the organization is based in Sweden. Actors could not be a political party or a governmental agency. Some organizations based outside of Sweden were included in the data collection but are not included in the data set for this analysis. The edges in the studied networks are all positive referrals and no negative (e.g. if organization A states that they will never collaborate with organization B, they have been excluded). Since the referral tracing data collection method was employed, some specific issues about the network boundaries should be mentioned. The first criteria for appearing in the network included organizations that are somehow active in connection with the conflict in Eastern Ukraine. Some of such organizations were generated by the conflict in Eastern Ukraine, while others have a broader set of activities and included in their agenda only a few events and collaborations that had to do with the conflict in Eastern Ukraine. In the first case, the conflict-generated organizations have been included as an edge sender and receiver node. In the latter case, the organization was coded only as an edge receiver. This was done to limit the network to only those organizations that are primarily focused on the conflict or identify themselves as Russian, Russian-speaking, or Ukrainian, while including potential collaborations with organizations that have a broader set of activities and agenda overall. The main motivation for including those organizations only as edge receivers was also to account for the theoretical possibility that the antagonist organizations could be connected through these broader organizations. Therefore, if not included at all, the network structure could be seriously implicated. The cumulative data for the period from 2013 to 2016 included 352 edges between 86 different organizations. However, for this analysis, the final data set consisted of 59 organizations located in Sweden (including international ones with a chapter in Sweden) during the period 2014 to 2016.
Table 1 shows that there are 14 Ukrainian organizations and 6 Russian organizations that clearly identify as such. The category “mixed” includes organizations that have members that identify themselves as Russian, Ukrainian, or other countries that used to be part of the Soviet Union or are Russian-speaking. Some of these organizations also identify themselves as Slavic. The fact that there are more specifically Ukrainian organizations reflects the phenomenon described elsewhere (author’s other unpublished article), qualitatively, namely that the people who were not happy with the claims of neutrality of the pan-Slavic organizations could demand a clear standpoint and even leave the organization if that demand was not satisfied. Some of these people could also start their own organization. On the other hand, if an organization became more political during the war, some members might not have felt completely happy with such course of events, and leave the organization as well. Furthermore, many organizations in the data set have been created as a direct response to the conflict, while claiming no identification with a specific ethnicity.
Table 1.
Data frequencies.
| Conflict side | ||||||||
|---|---|---|---|---|---|---|---|---|
| Ethnicity | Neutral | Pro-Russian | Pro-Ukrainian | Total | ||||
| Mixed (Russian-speaking) | 8 | 1 | 0 | 9 | ||||
| Not national | 12 | 6 | 1 | 19 | ||||
| Other national organizations | 11 | 0 | 0 | 11 | ||||
| Russian | 5 | 1 | 0 | 6 | ||||
| Ukrainian | 4 | 0 | 10 | 14 | ||||
| Total | 40 | 8 | 11 | 59 | ||||
| Network size | Density | Edges (total) | Reciprocity | Transitivity | ||||
|---|---|---|---|---|---|---|---|---|
| 2013 | 15 | 0.06 | 12 | 0.88 | 0 | |||
| 2014 | 15 | 0.10 | 22 | 0.88 | 0 | |||
| 2015 | 27 | 0.12 | 88 | 0.90 | 0.43 | |||
| 2016 | 40 | 0.08 | 139 | 0.94 | 0.19 | |||
| Baseline model | Step 2 | Step 3 | ||||||
|---|---|---|---|---|---|---|---|---|
| Covariates | Estimate | SE | Estimate | SE | Estimate | SE | ||
| Edges/intercept | −4.92 | 3.38 | −2.34 | 3.23 | −2.48 | 3.15 | ||
| Reciprocity | 0.58 | 1.26 | 0.88 | 1.21 | 0.91 | 1.20 | ||
| Intransitive | −0.41 | 0.41 | −0.26 | 0.37 | −0.25 | 0.37 | ||
| gw out-degree | −0.93 | 2.52 | −1.72 | 2.92 | −1.68 | 2.81 | ||
| gw in-degree (fixed 0.5) | 2.66. | 1.57 | 2.22 | 1.47 | 2.21 | 1.47 | ||
| org. type | umbrella organization | −0.06 | 0.57 | −0.12 | 0.46 | −0.10 | 0.46 | |
| global | ||||||||
| independent organization – reference category | . | . | . | . | . | |||
| ethnic ident. | Ukrainian | 1.37 | 1.00 | |||||
| Russian | 0.01 | 1.21 | ||||||
| mixed (Ukrainian and Russian) – reference category | . | |||||||
| other | – | – | ||||||
| no ethnic ident | 0.87 | 0.99 | ||||||
| conflict side | pro-Russian | |||||||
| pro-Ukrainian | ||||||||
| neutral – reference category | ||||||||
| homophily | on conflict side | –0.51 | 0.64 | |||||
| on ethnic identification | –0.25 | 0.66 | ||||||
| AIC | 113 | 112.2 | 112.9 | |||||
| Baseline Model | Step 2 | Step 3 | ||||||
|---|---|---|---|---|---|---|---|---|
| Covariates | Estimate | SE | Estimate | SE | Estimate | SE | ||
| Edges/intercept | −1.68*** | 0.44 | −1.77*** | 0.45 | −1.74*** | 0.44 | ||
| reciprocity | 2.14** | 0.81 | 2.07* | 0.82 | 2.08** | 0.82 | ||
| intransitive | −0.22. | 0.12 | −0.24. | 0.13 | −0.23. | 0.13 | ||
| gw in-degree (fixed 0.5) | 0.97 | 0.75 | 1.04 | 0.81 | 1.00 | 0.77 | ||
| gw out-degree (fixed 0.7) | −3.22*** | 0.51 | −3.17*** | 0.53 | −3.18*** | 0.53 | ||
| org. type | umbrella organization | 0.11 | 0.17 | 0.12 | 0.19 | 0.07 | 0.19 | |
| global | ||||||||
| independent organization – reference category | . | . | . | . | . | . | ||
| ethnic ident. | Ukrainian | |||||||
| Russian | ||||||||
| mixed (Ukrainian and Russian) – reference category | . | . | . | . | ||||
| other | ||||||||
| no ethnic ident. | ||||||||
| conflict side | pro-Russian | −0.001 | 0.18 | |||||
| pro-Ukrainian | −0.009 | 0.19 | ||||||
| neutral – reference category | ||||||||
| homophily | conflict side | pro-Russian | 0.08 | 0.51 | ||||
| pro-Ukrainian | 0.90. | 0.53 | ||||||
| ethnic ident. | mixed | 1.03 | 0.57 | |||||
| Ukrainian | 0.28 | 0.42 | ||||||
| AIC | 269.7 | 267.2 | 268.1 | |||||
| Baseline model | |||
|---|---|---|---|
| Covariates | Estimate | SE | |
| Edges/intercept | −1.14* | 0.50 | |
| reciprocity | 1.99** | 0.65 | |
| intransitive | −0.01 | 0.05 | |
| gw in-degree | 0.81. | 0.46 | |
| gw out-degree | −3.72*** | 0.40 | |
| org. type | umbrella organization | −0.16 | 0.19 |
| independent organization – reference category | . | . | |
| global | 0.17 | 0.19 | |
| ethnic ident. | Ukrainian | ||
| Russian | |||
| mixed (Ukrainian and Russian) – reference category | |||
| other | |||
| no ethnic id. | |||
| conflict side | pro-Russian | 0.29* | 0.13 |
| pro-Ukrainian | −0.20 | 0.26 | |
| neutral – reference category | . | . | |
| homophily | on conflict side | ||
| on ethnic ident. | |||
| AIC | 416.7 | ||
