metadata: authors: 0: author: World Bank
1: author: Pham,Phuong
2: author: O’Mealia,Thomas
3: author: Wei,Carol
4: author: Bindu,Kennedy Kihangi
5: author: Makoond,Anupah
6: author: Vinck,Patrick Thierry
count: Congo, Democratic Republic of
docna: 0: docna: Hosting New Neighbors : Perspectives of Host
            Communities on Social Cohesion in Eastern DRC
docty: Policy Research Working Paper
bdmdt: 2022-06-22T00:00:00Z
abstracts: cdata!: Situations of forced displacement create
            unique challenges for social cohesion because of the major
            disruption of social dynamics among both displaced persons
            and host communities. This paper uses a sequential mixed
            method approach to analyze the relationship between hosting
            displaced persons and perceptions of social cohesion in
            eastern Democratic Republic of Congo. First, participatory
            research methods in focus groups empowered participants to
            produce a locally driven definition of social cohesion. The
            results from these exercises inform the quantitative
            assessment by dictating measurement strategies when
            analyzing original surveys. Combining almost 50,000
            responses to 11 cross-sectional surveys between 2017 and
            2021, displacement is negatively associated with perceptions
            of social cohesion in aggregate. But at the individual
            level, those who report hosting displaced populations in
            their communities often have higher perceptions of social
            cohesion. These results are strongest among respondents who
            self-report hosting IDPs as opposed to refugees, but
            important heterogeneity across indicators, local context,
            and gender should guide policy meant to promote social
            cohesion in forced displacement.
display_title: Hosting New Neighbors : Perspectives
            of Host Communities on Social Cohesion in Eastern DRC
closedt: 2022-06-22T00:00:00Z
listing_relative_url: /research/2022/06/33849424/hosting-new-neighbors-perspectives-host-communities-social-cohesion-eastern-drc
topicv3: Forced Displacement m1326032 740,Social Cohesion m1327189 738,Conflict and Violence m1327549 2433,Internally Displaced Persons m1939428 4819
publishtoextweb_dt: 2022-06-23T00:00:00Z
dois: 10.1596/1813-9450-10099
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model_extractions: Policy Research Working Paper 10099

# Hosting New Neighbors

Perspectives of Host Communities on Social Cohesion in Eastern DRC _Phuong Pham Thomas O’Mealia Carol Wei Kennedy Kihangi Bindu Anupah Makoond Patrick Vinck_ Social Sustainability and Inclusion Global Practice June 2022
Policy Research Working Paper 10099

# **Abstract**

Situations of forced displacement create unique challenges for social cohesion because of the major disruption of social dynamics among both displaced persons and host communities. This paper uses a sequential mixed method approach to analyze the relationship between hosting displaced persons and perceptions of social cohesion in eastern Democratic Republic of Congo. First, participatory research methods in focus groups empowered participants to pro-duce a locally driven definition of social cohesion. The results from these exercises inform the quantitative assessment by dictating measurement strategies when analyzing original surveys.

Combining almost 50,000 responses to 11 cross-sectional surveys between 2017 and 2021, displacement is negatively associated with perceptions of social cohesion in aggregate. But at the individual level, those who report hosting displaced populations in their communities often have higher perceptions of social cohesion. These results are strongest among respondents who self-report hosting IDPs as opposed to refugees, but important heterogeneity across indicators, local context, and gender should guide policy meant to promote social cohesion in forced displacement.

This paper is a product of the Social Sustainability and Inclusion Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at ppham@hsph.harvard.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Hosting new neighbors: Perspectives of host communities on social cohesion in eastern DRC<sup>*</sup>

Phuong Pham,<sup>†</sup> Thomas O’Mealia,<sup>‡</sup> Carol Wei,<sup>§</sup> Kennedy Kihangi Bindu,<sup>¶</sup> Anupah Makoond,<sup>||</sup> & Patrick Vinck<sup>**</sup>

**_JEL Codes:_** D74, F22, C83, N47, O15, R23

**_Keywords:_** Displacement, Hosting, Social Cohesion, Surveys, Democratic Republic of Congo

> *Pham and O’Mealia are co-first authors. Acquisition of the data used in this manuscript was supported by the United Nations Development Programme (UNDP). The funder played no role in the analysis, interpretation or writing of the results and decision to submit the manuscript.

This paper was commissioned by the World Bank Social Sustainability and Inclusion Global Practice as part of the activity “Preventing Social Conflict and Promoting Social Cohesion in Forced Displacement Contexts.” The activity is task managed by Audrey Sacks and Susan Wong with assistance from Stephen Winkler. This work is part of the program “Building the Evidence on Protracted Forced Displacement: A Multi-Stakeholder Partnership”. The program is funded by UK aid from the United Kingdom’s Foreign, Commonwealth and Development Office (FCDO), it is managed by the World Bank Group (WBG) and was established in partnership with the United Nations High Commissioner for Refugees (UNHCR). The scope of the program is to expand the global knowledge on forced displacement by funding quality research and disseminating results for the use of practitioners and policy makers. This work does not necessarily reflect the views of FCDO, the WBG or UNHCR.

†Assistant Professor, Harvard TH Chan School of Public Health and Harvard Medical School, USA ‡Postdoctoral Fellow, Harvard TH Chan School of Public Health, USA §Research Consultant, Department of Emergency Medicine, Brigham and Women’s Hospital, USA ¶Professor, Universit ́e Libre des Pays des Grands Lacs, DR Congo

||Research Manager, Harvard Humanitarian Initiative, USA

**Assistant Professor, Harvard TH Chan School of Public Health and Harvard Medical School, USA
# **1 Introduction**

One of the most challenging steps toward building a peaceful and just society after violence is the mending of broken relationships and establishing new ones between people, communities, and institutions. The international community has recognized this challenge, adopting social cohesion as a core objective and tool of peacebuilding (UNDP 2020, UNICEF 2021). Forced displacement creates major disruption to social dynamics among both displaced persons and host communities. The influx of displaced people has the potential to put strain on the host community by creating inequalities in access to services, resources, and income.

At the same time, social cohesion can facilitate collective action for example by allowing populations to preemptively evacuate and escape (Arnon, McAlexander & Rubin 2021). High levels of social cohesion can improve outcomes after traumatic events either providing individual or social assets, such as resilience ( Ozc ̧ ̈ur ̈umez,<sup> ̈</sup> Hoxha &<sup> ̇</sup> Ic ̧duygu 2020) or mental stability (Greene, Paranjothy & Palmer 2015). But understanding what dimensions of social cohesion are especially salient – and how those dimensions are related to changing dynamics such as forced displacement – requires understanding how communities perceive what constitutes social cohesion in their lived experiences.

Despite a growing body of work that analyzes the relationship between forced displacement and social cohesion, there remains a lack of clear definition of social cohesion in the context of forced displacement (De Berry & Roberts 2018). Most research focuses on refugee situations and the resulting relationships with host communities in the global north. But the salience of different elements of social cohesion may be contextually driven and differ across several dimensions, such as the type of forced displacement experienced locally (IDP versus refugee, for example)<sup>1</sup> and local

> 1We employ the following definitions for different types of displacement to ensure analytical consistency: refugees are “someone who has been forced to flee his or her country because of persecution, war or violence.” Internally displaced persons (IDPs) are “someone who has been forced to flee their home but never cross an international border.” Returnees are “someone who was of concern to UNHCR when outside their country of origin and who remains so for a limited period (usually two years) after returning home to their country of origin. It also applies to internally displaced persons who return home to their prior place

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context (urban and rural). It is commonly accepted that displacement negatively affects social cohesion, and that forced displacement occurs in contexts with low levels of social cohesion to begin with.

Protracted displacement can lead to political tensions, as associations are formed along ethnic or political lines and new grievances emerge. In contexts of internal displacement, ethnic and social tensions (which may have been the drivers or consequences of the displacement) are exacerbated by the presence of IDPs. For refugees, deeper social and cultural divides may exist, hindering social cohesion (De Berry & Roberts 2018). Indeed, in some situations, protracted displacement and expectations of retaliation on return create greater politicization of the displaced along ethnic lines (Harild, Vinck, Vedsted & de Berry 2013). More generally, economic competition, poor governance, lack of rule of law, and limited access to scarce resources are features of the living conditions for most IDPs and refugees and oftentimes the host population, further hindering social cohesion (Munoz & Shanks 2019).

This paper analyzes the relationship between displacement and social cohesion in the eastern provinces of the Democratic Republic of Congo (DRC). In 2020 alone, the country recorded 2 million new conflict displacements according to UNHCR, the majority of whom are in the eastern provinces of Ituri, North Kivu, and South Kivu ( _UNHCR Global Focus_ N.d.). Large segments of the civilian population are displaced regularly and temporarily live with hosts in neighboring communities until the local security situation improves. Additionally, political violence and instability in neighboring states (Burundi, South Sudan, Rwanda, and Uganda especially) produce refugee flows into eastern DRC.<sup>2</sup> Eastern DRC is therefore host to large numbers of both IDPs and refugees. The dynamics of hosting displaced persons in eastern DRC thus represent a fundamenof residence.” These categories are in contrast to migrants, “someone who leaves their country purely for economic reasons unrelated to the refugee definition, or in order to seek material improvements in their livelihood.”

> 2The conflicts in eastern DRC also produce refugee flows out of the country and into neighboring states. These flows are beyond the empirical scope of our paper but are connected to regional displacement dynamics.

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tally different set of challenges to social cohesion than the more commonly analyzed camp-based displacement or refugee flows into European countries.

Due to contextual differences, the salient dimensions of social cohesion may not match academic definitions derived mainly within western contexts. To address this challenge, this project employed participatory research methods to identify the elements of social cohesion considered relevant in eastern DRC. By adopting this design, the project iteratively built a set of research questions and methodological tools to ensure locally appropriate decisions to measure contextually appropriate concepts. The insights from the focus groups dictated our measurement strategy of social cohesion when analyzing a series of surveys conducted in eastern DRC between 2017 and 2021.

The findings contribute to a growing research agenda on how hosting forcibly displaced persons impacts perceptions of social cohesion. The results are consistent with findings from Zhou, Grossman & Ge (2021), who find that proximity to refugee settlements can improve goods provision to host communities and that the presence of displaced persons does not necessarily negatively affect host community attitudes towards the displaced persons they host. Similarly, Aksoy & Ginn (2021) also find that the arrival of migrants do not necessarily have negative effects on host community attitudes. Consistent with the results in this paper, Betts, Stierna, Naohiko & Sterck (2021) find that local context – including urban versus rural settings – matters in how host community interactions with displaced populations impact social cohesion.

# **2 Context: Eastern DRCongo**

For the past five decades, eastern DRC has experienced varying levels of conflict. The violence has been fueled by complex and interlinked domestic and foreign competition over access to resources and political power, deepening long-standing inequities and conflicts along ethnic lines.<sup>3</sup> Mobutu’s

> 3For details on the roots of the conflicts in eastern DRC, see Reyntjens (2001), Vlassenroot & Raeymaekers (2004), and Vlassenroot & Raeymaekers (2009).

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thirty years of autocratic rule that followed the Congolese independence from Belgium colonial rule paved the way to a violent transition, culminating in two internationalized wars from 1996 to 1997, in the aftermath of the Rwandan genocide, and from 1998 to 2003. Since the end of the Second Congo War in 2003, eastern Congo has remained unstable and violent, with many domestic and foreign-backed armed groups – including elements of the state military, FARDC – using violence against civilians and each other (Autesserre 2010). The violence and instability have resulted in poor living conditions and regular forced displacement for Congolese civilians.

This project focuses on three provinces of eastern DRC that are especially impacted by forced displacement and political violence: North Kivu, South Kivu, and Ituri.<sup>4</sup> These three provinces account for 4.5 million out of an estimated 5.268 million total (85%) IDPs in DRC 2020 ( _UNHCR Operational Data Portal: Democratic Republic of Congo_ 2021). Other provinces not included in this study but hosting IDPs include southern and central provinces such as Kasai, Kasai-Central, Kasai-Oriental, Lomani, Sankuru, and Tanganyika. The analysis in this paper focuses exclusively on dynamics in eastern Congo where the authors collected data.

The large number of interconnected conflicts in these provinces involving non-state armed groups and state actors create a continuous ebb and flow of displacement in eastern DRC (Jacobs & Kyamusugulwa 2018). In June 2020, UNHCR estimated that over 4.5 million persons were internally displaced in Ituri (1.6M), North Kivu (1.9M) and South Kivu (1M) provinces alone (UNHCR 2020). DRC hosts an additional 536,000 refugees (UNHCR 2020) from neighboring countries with recent experiences of violence, especially Burundi, Uganda, CAR, and South Sudan. Figure 2 plots the trend in the new IDPs in the DRC between 2009 and 2020.<sup>5</sup> Most IDPs in DRC favor staying with host families as opposed to camp displacement (Haver 2008, Rohwerder 2013). In 2017, UNOCHA estimated that around 500,000 IDPs were in camplike settings, whereas 3.3 million sought refuge in host communities (Jacobs & Kyamusugulwa 4The qualitative analysis covers only the Kivu provinces, but the quantitative analysis covers all three. 5Data provided by the Internal Displacement Monitoring Center DRC Page, accessed May 14, 2021.

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7 <!-- Start of picture text --> Ituri<br>North Kivu<br>South Kivu<br>15°E 20°E 25°E 30°E<br>N5°<br>0°<br>S5°<br>S10°<br><!-- End of picture text -->

- (a) DRC, with North Kivu, South Kivu, and Ituri Shaded

<!-- Start of picture text --> G G<br>G<br>G<br>GGG<br>24°E 26°E 28°E 30°E 32°E 34°E<br>N4°<br>N2°<br>0°<br>S2°<br>S4°<br><!-- End of picture text -->

- (b) Kivu Provinces, _Territoires_ , and Focus Group Locations

Figure 1: Area of Interest: Kivu Provinces
<!-- Start of picture text --> New Displacements, DRC<br>2000000<br>1500000<br>1000000<br>500000<br>Year<br>2012 2016 2020<br>Newly Displaced Persons Due to Conflict<br><!-- End of picture text --> Figure 2: Temporal Trends in IDP Flows, Democratic Republic of Congo 2018). Many are displaced multiple times in short bursts as the security situation in their communities fluctuates (Zeender & Rothing 2010). When fleeing violence, IDPs in DRC oftentimes attempt to stay close to their home communities so they can monitor their properties with the intention of returning once the security situation improves (White 2014).

In areas near violence, host communities are frequently and repetitively asked to host IDPs: by one count, host families often host IDPs around three to four times, for around three months on average (Simpson 2010). Alternatively, many IDPs flee to urban areas, increasing slum areas in cities like Goma and Bukavu (Zeender & Rothing 2010). Urban IDPs are less reliant directly on host families and many have found work in urban areas (Jacobs, Lubala Kubiha & Katembera 2020).

In summary, the dynamics of displacement in eastern DRC are fluid, with vulnerable popula8
tions frequently coming and going as conflict dynamics evolve. IDPs primarily rely on informal networks when seeking refuge, leveraging their ethnic, religious, and other social networks to find safety. Communities host displaced persons informally and long-term camp-based displacement is relatively rare. In contrast to most research that focuses on the impacts of tightly concentrated populations, displacement in eastern DRC lacks the sort of static geographic concentration of displaced populations. Such dynamics may have fundamentally different implications for social cohesion and require different policy.

# **3 Defining Social Cohesion in Contexts of Forced Displacement**

Existing definitions of social cohesion motivate the participatory research strategies used define social cohesion in this project. Social cohesion is a conceptual construct for which there is no universally agreed upon measure. In a comprehensive study reviewing whether community driven development positively impacts social cohesion, (King, Samii & Snilstveit 2010) note that both the attitudinal and behavioral measures of social cohesion manifest in highly context specific ways, making it difficult to identify universal and cross-cutting measures of social cohesion. In general terms, social cohesion is defined as a set of societal characteristics or attributes that foster “mutual moral support, which instead of throwing the individual on his own resources, leads him to share in the collective energy and supports his own when exhausted” (Berkman, Kawachi & Glymour 2014).

Scholars and practitioners studying social cohesion in the last two decades generally agree that social cohesion consists of two intertwined features of society: 1) the absence of latent social conflict, including income inequality, racial/ethnic tensions, and disparities in political participation and 2) the presence of strong social bonds such as high levels of trust, norms of reciprocity, presence of associations and the presence of institutions of conflict management (Jenson 2010). Increasingly, and especially in the literature that explores the role of social cohesion in economic 9
growth and development, a third component, sometimes included in the second above-mentioned dimension is made explicit: the presence of effective institutions and governance. These understandings are mainly based on research conducted in Europe or North America, which excludes contextual factors in other societies, “such as focusing on the impact of minority groups on social majorities and the effect of integration (or lack of integration) on social cohesion or theoretical blind spots, such as risks to good governance” (De Berry & Roberts 2018).

The relevant set of relationships and institutions that matter to social cohesion vary according to context. Although some studies use social cohesion and social capital interchangeably, King, Samii & Snilstveit (2010) argue that social cohesion emphasizes the group and the patterns of cooperation rather than the assets that give rise to them. Yet the question remains as to whether there is a set of common thematic concepts that can be operationally measured. De Berry & Roberts (2018) note “initiatives to improve the definition and measurement of social cohesion have involved the development of subjective and objective indicators across the horizontal (inter-group) and vertical axis (person-state). For example, the horizontal could be evident in the levels of trust in other social groups and the vertical evident in the level of trust in the institutions of the state.” Social cohesion thus represents a broader social fabric, not just a particular circumstance, issue, or event. To understand how dynamics such as displacement are related to social cohesion, it is crucial to first what elements of the social fabric are considered most salient by those who live in these communities.

# **3.1 Towards a Locally-Led Definition of Social Cohesion: Focus Group Evidence**

To ensure that the conceptualization of social cohesion used in this paper is appropriately contextualized to local understanding, the project consulted with local communities using a sequential mixed method approach to produce a locally driven definition of social cohesion. First, a qual10
itative exercise empowered focus group participants to guide the research and conceptualization. The results from these exercises then dictating the definition and measurement strategy for social cohesion in the quantitative assessment.

The participatory research strategy was based mainly on structured focus group discussions. The project conducted consultations in seven _territoires_ with the objective to develop localized understandings of what elements were important to social cohesion in eastern DRC. Participants were selected from civil society and the public sector. 96 individuals participated in these exercises (Table 1), 55% of whom were men and 45% of whom were women.<sup>6</sup>

|**Location (Groupement)**|**Date**|**Number Participants**|
|---|---|---|
|Goma City|06 Oct 2017|11|
|Bukavu City|13 Oct 2017|13|
|Nyabibwe (Kalehe)|12 Oct 2017|14|
|Ishungu & Lughendo (Kabare)|12 Oct 2017|15|
|Kamisimbi (Walungu)|16 Oct 2017|18|
|Wassa (Walikale)|20 Oct 2017|12|
|Biiri (Masisi)|03 Nov 2017|13|

Table 1: Descriptive Information on Focus Groups The focus group discussions began with an open discussion on social cohesion designed to ascertain participants familiarity with the concept. The facilitator further asked participants to write down words or concepts participants related to social cohesion. These words were written on individual post-its, which were then posted on a wall. Participants then grouped words, building a concept map to visually represent their common understanding of social cohesion.

Following the development of the concept map, the facilitator broke participants into smaller groups and were asked to conceive of a fictional yet realistic person that exists in their contexts. 6Focus groups were conducted in Swahili and French. Focus groups were transcribed to French for analysis.

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<!-- Start of picture text --> Land Leadership Ethnicity Community Service<br>Public infrastructure Collaborative projects<br>Institutionsituti Distribution of 5f a. Collaboration<br>Corruption resources Gender ssociations Ceremonies (births, deaths,<br>Public Finance Management marriages)<br>Government Electricity . .<br>performance eaithcare hie Solidarity<br>Decision ; Development Credit Helping Each other Distribution of resources<br>making Access to public goods Generosity<br>processes Educationj youth . . Sharing Charity‘<br>Social Cohesion Information Flow Equity<br>Governance<br>Civic Education<br>; Justice Order<br>Inclusion Peace Love<br>PrejudiceMinority— GroupsparticipationStereotypesAcceptancee Conflict ManagementCustomsional EmpathySecurity<br>MarginalisationObedience Authoritiesi Shared Objectives Love<br>Discrimination Mutual understanding Relationships _ Friendship Linguistic Homogeneity<br>Communication Humility- RespectInteraction Religiousi 9 HomogeneityUnityi Ethnic; Homogeneity;<br>Tolerance Cohabitation Collaboration (working<br>Education. Dialogue Intermarriage together)<br><!-- End of picture text -->
# **3.1.1 Relationships**

The predominant understanding of social cohesion was centered around relationships between individuals and between groups. The defining characteristic of group relations was either shared geographic origin, shared ethnicity, or shared religion, with ethnicity and geographic belonging being much more common than religion. Three distinct but interrelated dimensions of relationships further emerged.

Participants associated **cohabitation** with character traits and human values, notably ‘respect’ and ‘tolerance’. According to most participants, these traits are fostered through education, both at home, in the community, and in schools. Some participants spoke about the importance of openness to learning, and to be able to reflect as necessary to cohabitation with others. People also spoke about the importance of communication, whether through media or dialogue spaces, as a factor that can contribute to peaceful cohabitation in so far that the opportunity to exchange with the other enables knowing the other and promotes mutual understanding, the latter of which is considered necessary for cohabitation.

**Harmony** was often discussed alongside peace and at times used interchangeably to describe a desirable overall quality of a community. Peace and harmony were also associated with the management of conflicts, with some participants emphasizing land conflicts. In some consultations, participants spoke more specifically to the importance of norms, and knowledge of laws and social conventions as necessary elements leading to harmony.

**Unity** was the most frequently cited dimension of relationship, with one participant for example suggesting that “there is social cohesion when there is a love among people, and when a community is united.” In areas marked by ethnic diversity, participants pointed to the ability to “love each other despite differences” and to the capacity to compromise. Regardless of the degree of ethnic heterogeneity, unity was frequently described in terms of community members having shared objectives. In some consultations, participants noted that socialization and intermarriages across ethnic, linguistic, and religious divides constitute a demonstration of unity. Unity is visi-

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ble when there is friendship between people, there is affection between people, people get along ( _“bonne entente”_ ), people work together, people think as one. More formal concepts of “reconciliation” and “integration” were not frequently evoked. Other factors that were cited, albeit less frequently, as contributing to unity include shared (ethnic) origins and religion, suggesting that many people believe that a certain degree of homogeneity in cultural and religious background may contribute to “organic” unity.

# **3.1.2 Solidarity**

A second theme that was echoed across all seven consultations was solidarity. While closely related to relationships, solidarity was emphasized as a separate domain. In some focus groups, participants noted that solidarity was the very _raison-d’etre_ of social cohesion and its most valuable benefit. Solidarity was divided into three dimensions: collaboration, sharing, and support.

In some rural areas, participants cited examples of community infrastructure which had been built by the entire community, or of jointly managed public goods (e.g. water) as strong examples of **collaboration** . Such collaborative efforts represent the cornerstone of solidarity for some participants. Collaboration emanates from having common objectives and working towards them together. Community associations or organizations aimed at achieving common objectives were given as examples of collaboration. Participants also discussed the organization of ceremonies celebrating births, marriages, or deaths as examples of collaborations. In urban consultations, many participants suggested that there is less cohesion in the city compared to rural areas because people do not work together as one when a neighbor dies or a relative is getting married. In contrast, some participants suggested that in rural areas, an entire village would be mobilized if there is a need to organize a wedding or a funeral. A third instance of collaboration cited across the consultations was that of community service (e.g. _salongo_ ) or community participation. This is also tied to civic duty, and while acknowledged as an example of collaboration, participants noted that authorities – both customary and formal – sometimes co-opt community service in a predatory manner.

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**Sharing** ( _partage_ ) was a strong component of social cohesion across all consultations. Sharing was expressed in different contexts and at different levels. On one hand, participants cited religious values and charity, while on the other hand, it was conceptualized in a more structural manner and associated with notions of equality. One participant in Kalehe noted that “if my neighbor has less than me, and is in need, he might steal from me, and I might not trust him.” Inequalities with regards to the distribution of resources were cited as an impediment to social cohesion and evoked that “sharing resources” was thus a necessary remedy. This discussion also touched on issues of governance as many participants felt that the root cause of the unequal distribution of resources was favoritism by leaders for members of their own group or otherwise a truncated economic system that favored some groups over others (see domain 3 on governance). People also specified the importance of sharing information and exchanges as a factor contributing to social cohesion. Additionally, the flow of information between leaders or authorities and members of the community was also cited as necessary to social cohesion.

In addition to the formal forms of collaboration and to the importance of equity between individuals and groups, persons consulted also evoked the importance of basic, quotidian solidarity, which we label as **support** . Examples included the willingness to help a neighbor who is sick or to assist someone in need of credit. Support did not give rise to many sub dimensions during the consultations, but scales can be developed to measure the attitudes and behavior of individuals in relation to quotidian solidarity.

# **3.1.3 Governance**

Finally, some participants (in Goma especially) noted the accountability of leaders to the population as a factor contributing to social cohesion. Elsewhere, participants discussed governance but in an indirect, and often negative, manner. The governance factor can be broken down into three dimensions.

In almost all consultations, participants expressed that access to basic needs and services is key 15
to social cohesion, broadly encapsulating the concept of **development** . The fact that people are in need or suffering makes them desperate and may force them to give in to behavior that destabilizes the community, with the example of armed group recruitment cited on several occasions. In most consultations, people talked of the importance of job opportunities as key. While in some instances, the government’s responsibility to ensure access to basic public goods was cited, this point was not heavily emphasized. In some cases, however, participants did note that development was the shared responsibility of the community and that ensuring the education of youth would endow individuals with the tools necessary to foster development.

A second recurring theme describe how the inequitable **distribution of resources** (of land in particular) encroaches upon social cohesion and harmony within a community. While rarely pointing fingers directly at authorities, participants did implicitly evoke corruption and nepotism as factors that can create inequities. The distribution of land was cited in almost all consultations. Some participants pointed to laws and customs that favored some groups over others, and in particular men over women. Although participants generally refrained from citing the responsibility of authority figures and leaders for development, they were more emphatic in attributing inequities to their behavior. In some consultations, participants openly spoke of political manipulation. Especially in urban areas, participants cited the institutionalized disparity between socio-economic classes as problematic. Participants felt that inequalities existed along ethnic and gender lines, but also along socio-economic and geographic lines. Geographically, the issue of inequality was especially prominent in the city of Goma, where participants noted the striking disparity between the commune of Goma and that of Karisimbi, with the latter under-served for amenities and services.

The third dimension involved **participation** . Most participants felt that a community in which groups are excluded or marginalized does not have social cohesion. Nonetheless, they often recognized that the primacy/dominance of some groups was rooted in tradition and that trying to change an established social order can also destabilize the social cohesion of a community. This was raised in relation to the question of gender equality. In some cases, some participants cited ‘acceptance’, 16
‘patience’ and obedience as qualities that a person should have to live in harmony/cohesion with others because some things cannot change. In other instances, however, participants were more critical of opaque decision-making mechanisms. The question of participation was not limited to decision making processes but also raised in more general terms of participation in the community. In almost all focus groups, care was taken to also include groups that are traditionally marginalized such as pygmies. They were usually the most critical of discriminatory practices by both authorities and other members of the community. Stereotypes and prejudice against some groups, whether women or pygmies also emerged as a factor hindering their participation in social and decision making. On one occasion, a participant challenged the view that the exclusion of certain groups was solely the fault of dominant/majority groups but also partly the fault of the minorities themselves, who resorted to attitudes of auto-victimization.

# **3.2 Hosting Displaced Populations and Perceptions of Social Cohesion**

Social cohesion, consistent with the locally led definition presented above, is not a static state. Evolving political and social dynamics continually challenge or reshape the social cohesion locally. Forced displacement poses unique challenges to social cohesion by stressing local economies and demographics; on the other hand, hosting forcibly displaced populations can attract NGO resources and government service provision (De Berry & Roberts 2018), potentially improving social cohesion.

Despite the common perception that hosting displaced populations increases tension and results in nativist political agendas,<sup>7</sup> several studies find that hosting does not necessarily have detrimental impacts on local social cohesion. Communities have a higher willingness to host refugees than we might assume (Zorlu 2017). In Rwanda, Fajth, Bilgili, Loschmann & Siegel (2019) finds host

> 7Several studies that examine the consequences of hosting refugees in Europe find that large refugee inflows produced resentment and caused the rise of nativists political sentiments (Dinas, Matakos, Xefteris & Hangartner 2019, Hangartner, Dinas, Marbach, Matakos & Xefteris 2019). Refugees can become the target of violence from host populations as well (Fisk 2018, Savun & Gineste 2019).

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populations and refugees overwhelmingly co-exist peacefully. Contact theory is often posited as an important mechanism for promoting social cohesion between displaced populations and host communities (Finseraas & Kotsadam 2017, Ghosn, Braithwaite & Chu 2019): those who are exposed to displaced populations are more likely to be sympathetic to them and support policies that support displaced persons.

These perceptions are influenced by the impact that hosting displaced populations has on the local economy. Low labor market integration of refugees can make it more difficult for exposure and integration to occur (Bauer, Braun & Kvasnicka 2013, Del Carpio, Seker & Yener 2018). Increases in displaced populations have been shown to increase the price of non-aid food items and are associated with more modest price effects for aid-related food items (Alix-Garcia & Saah 2010). In these ways, hosting displaced populations can strain economic conditions, potentially straining social cohesion locally.

Other research finds more mixed implications. The probability of having a negative outcome for host communities in the consumer and labor markets is relatively low (Verme & Schuettler 2021). Jordanians living in areas with a high concentration of refugees have had no worse labor market outcomes than Jordanians with less exposure to the refugee influx (Fallah, Krafft & Wahba 2019). Some even found economic benefits: In Kenya, refugee camps improve the health and nutrient intake of local communities directly surrounding camps (Gengo, Oka, Vemuru, Golitko & Gettler 2018). Ugandans living near refugee settlements benefit both in consumption and public service provision (Kreibaum 2016).

Importantly, these economic implications may not match perceptions of economic benefits. Where assistance to refugees is perceived as above average living conditions in the host communities, resentment may build (Agblorti 2011). The influx of money that can come with the influx of displaced persons can have uneven impact and reinforce the position of privilege or marginalization that individuals have in a community (Whitaker 2002). Economic interventions that displacement attracts can create uneven distributional effects (Paler, Strauss-Kahn & Kocak 2020), as the target 18
group will benefit more in communities where elites and the excluded groups seek to compete to capture aid.

As such, the evidence on the consequences of forced displacement for perceptions of local social cohesion is mixed. Existing findings are based on research conducted mainly in western Europe, particularly those that analyze large refugee flows from the Middle East and show that hosting refugees can negatively impact social cohesion. But other research demonstrates that, especially among those who are most directly exposed to displaced populations, hosting does not necessarily result in a backlash effect and may even be associated with limited economic benefits.

# **3.2.1 Fluid Displacement Flows and Perceptions of Social Cohesion**

In scenarios where displacement is more fluid, frequent, and informal amidst ongoing conflicts, host communities may have incentives and experiences that may differ in fundamental ways than in refugee contexts or more permanent displacement. These differences may result in unexpected relationships between hosting displaced populations and perceptions of social cohesion.

Aggregate relationships between levels of displacement and social cohesion are likely influenced by the fact that areas that experience higher levels of forced displacement are precisely the areas that experience the most violence. As a result, aggregate displacement levels and perceptions of social cohesion are likely negatively related, but this is not necessarily a function of hosting displaced persons. Instead, displacement is a manifestation of a broader erosion of social cohesion at the vertical level. Hosting IDPs may still impact host community perceptions in several ways, but more dis-aggregated analysis is required to unpack the relationship between hosting and perceptions of social cohesion.

At the individual level, the relationship between hosts and IDPs may be more positive than other host-displaced community relationships. First, hosting IDPs populations can improve perceptions of relationships both with in-groups and out-groups by increasing contact and reliance. Hosting displaced populations can force people to rely on their own communities to respond to the 19
difficulties that come with hosting. Civil society groups, such as religious organizations, can help fill the gap when and where needed. Moreover, broader conflict dynamics can make in-group relationships more important (Fearon & Laitin 2000). Such experiences may increase the importance and perceptions of intra-ethnic or intra-religious relationships.

Second, hosting displaced persons is itself an expression of solidarity and may increase opportunities for acts of solidarity as well. Many host communities may have themselves been displaced at other stages of the conflict (Beytrison & Kalis 2013). This set of experiences can change perceptions of hosting displaced populations through empathy - by increasing appreciation for the difficulty that comes with hosting and by understanding the hardship that displaced persons are experiencing. One study in eastern DRC found that 80 percent of hosts said they would do it again and 60 percent reported a positive bond with their displaced guests (Rohwerder 2013).

Many communities host displaced out-groups, not just co-ethnics. Contact can break down stereotypes and create bonds between members of out-groups. Mixing with members of other groups tends to make individuals more empathetic towards those groups (Boisjoly, Duncan, Kremer, Levy & Eccles 2006), and displacement can incentivize or force such mixing. It can also create opportunities for them to reach and learn other parts of society other than their own- cultivating human intrinsic curiosity (Kashdan & Silvia 2009).

Finally, hosting displaced persons can change perceptions of governance. IDPs in communities may receive preferential treatment from the government or from international humanitarian actors (Paler, Strauss-Kahn & Kocak 2020). This can have cross-cutting implications, as host communities may resent the attention/resources paid to the IDPs, but host communities may also benefit from the increased attention paid to local problems. In contexts of informal displacement, host communities can share more equally in resources that arrive to support displaced populations, mitigating the negative perceptions that may grow based on these distributional challenges.

Based on these dynamics, we expect to observe a different set of associations between aggregate trends in displacement locally and individual experiences with hosting displaced communities.

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In aggregate, we expect to observe a negative relationship between the percentage of the population that reports displacement, but at the individual level we expect that experience with hosting may, in certain circumstances, be positively associated with perceptions of social cohesion, regarding perceptions of relationships and solidarity.

# **4 Displacement and Social Cohesion: Survey Evidence**

To empirically evaluate the relationships between hosting displaced populations and social cohesion, this paper analyzes a series of surveys of civilian adults conducted in eastern DRC.<sup>8</sup> Each survey uses a multi-stage cluster sampling strategy capturing all _territoires_<sup>9</sup> in North Kivu, South Kivu and Ituri provinces. The final sampling units are randomly selected adults above the age of 18 to avoid bias toward men and/or heads of households. Multiple attempts are made over the course of one day to contact selected respondents and if necessary, appointments are made for interview. Surveys are enumerated by Congolese college students or professionals and interviews are conducted by members of the same gender and ethnicity as respondents to minimize enumeratorinduced response bias. Further methodological details have been published (Vinck, Pham, Bindu, Bedford & Nilles 2019) elsewhere and additional details and sample size calculation are detailed in Appendix.

These surveys are part of a long-term data collection effort by the research team (Vinck & Pham 2014) and were collected separately from the focus group discussions. The focus group discussions thus did not directly influence the design of the surveys, but rather directed the analysis strategy of the surveys that our team has collected at regular intervals in eastern DRC.

The survey data are analyzed in two ways. First, 11 surveys collected between 2017 and 2021

> 8Eastern DRC is a site of ongoing violence, raising a number of ethical, methodological, and practical concerns about collecting data. We discuss the ethical protections we implemented when collecting this survey data in the Appendix, Section B.

> 9 _Territoires_ are sub-provincial administrative units. Additional details on the structure of administrative units are available in the Appendix, Section A.1.

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are combined. The surveys follow a repeated cross-sectional design and are not panels (i.e. the same administrative units, not the same people, are re-sampled), so responses are aggregated to the _groupement_ level, the lowest level at which the project consistently collect representative data. Table 2 provides a summary of the dates, sizes, and percent of respondents who report being displaced within each survey wave. This aggregated temporal analysis can show, associations between fluctuations in displacement and perceptions of social cohesion over space and time at the _groupement_ level. Question coverage varies across survey waves, but a battery of core questions enables consistent observation of how many individual respondents self-report being displaced at the time of the survey and being involuntarily moved within the past year.

|**Poll**|**Date**|**N**|**% Current**<br>**Displaced**|**ly**<br>**% Displa**<br>**Last Yr**|**ced**<br>**% Hosting**<br>**Displacees**|
|---|---|---|---|---|---|
|#11|July 2017|5834|4.35|7.42|–|
|#12|September-October 2017|4013|1.62|2.62|–|
|#13|December 2017|4883|3.50|7.97|–|
|#14|March-April 2018|1933|4.97|8.85|31.35|
|#15|June-July 2018|5951|3.70|8.35|30.33|
|#16|October 2018|1112|6.47|4.68|–|
|#17|December 2018|5918|5.86|11.20|–|
|#19|July-August 2019|5961|5.12|10.45|–|
|#20|December 2019|5752|4.71|8.14|–|
|#21|November 2020|2627|4.19|5.14|–|
|#22|February-March 2021|5847|6.86|9.30|–|
|**Overall**|**July 2017-March 2021**|**49831**|**4.64**|**8.19**|**30.58**|

Table 2: Details on Surveys and Displacement Trends Second, the paper conducts an individual-level analysis of two cross-sectional surveys of 1,933 and 5,951 individuals conducted in March-April 2018 and June - July 2018, respectively, to probe the relationship between hosting displacees and social cohesion in more detail. This survey wave 22
included a specific battery of questions that provided respondents the opportunity to report their perceptions of whether IDPs or refugees were present in their communities and, if so, what impact hosting displaced persons had on social cohesion their communities. Additionally, respondents reported whether their communities hosted IDPs (displaced persons from within DRC) or refugees (displaced persons from Burundi, Rwanda, Uganda, South Sudan, or other countries).

Given the lack of reliable census data and frequent population movements in eastern DRCongo, sampling and weighting procedures are necessarily conservative. All of the surveys randomly select _groupements_ (or _quartiers_ in cities) in each _territoire_ . Within selected _groupements_ , select villages are drawn (or _avenues_ in cities), which are clusters per _territoire_ . Enumerators carry out 8 interviews per cluster using a random walk procedure. Responses are weighted to adjust for differences in probability of selection at the _territoire_ level and all samples are gender-balanced. Additional details on the survey design are provided in the Appendix, Section D.

# **4.1 Measuring Displacement Context**

Because this paper is interested in a context of frequent, unregistered, and informal displacement, it relies on self-reported measures for all variables included in the analysis.

The aggregate analysis calculates the percentage of respondents in each _groupement_ that report being displaced in response to either of the following two questions: “Are you currently displaced?” and “In the past 12 months, have you been involuntarily moved?” The aggregate analysis is thus a representation of the proportion of respondents within each _groupement_ that self-reports being displaced currently or having recently been displaced (but not necessarily displaced any longer).

In the individual level analysis, the independent variable measures whether respondents’ communities host displaced persons. The 2018 survey asks “Are there any displaced persons or refugees here in the city or the territory?” At the individual level, respondents who respond yes are coded as hosting displaced persons. Additionally, if respondents reported that they did host 23
displacees in their communities, the survey asked an additional question in which respondents reported whether their communities hosted IDPs (displaced persons from within DRC) or refugees (displaced persons from Burundi, Rwanda, Uganda, South Sudan, or other countries). These responses are used to create a categorical variable that measures whether respondents report hosting IDPs, hosting refugees, or not hosting displaced persons in their communities. Table 3 summarizes the measurement strategies for hosting status.

It is possible that respondents may misreport whether they are displaced or whether displaced people are present for a number of reasons. First, they might not know that displaced persons are present, a risk that is especially acute for IDPs. Because the paper is primarily interested in how knowledge of hosting impacts perceptions of social cohesion, this measurement challenge is not as acute a problem as it may at first seem. Respondents must know that IDPs or refugees are present in their community for hosting to impact their perceptions of social cohesion. If they are not aware of the presence of IDPs or refugees, their presence is unlikely to systematically impact their perceptions. Second, there might be incentives to either hide or, alternatively, to over-claim the presence of IDPs or refugees. Enumerators reminded respondents that the survey was part of an academic study and not connected to service provision decisions, which we hope alleviate some of these incentives. That said, it is important to note that this project analyzes _selfreported perceptions of the presence of IDPs or refugees_ , not the confirmed presence of displaced populations.

# **Hosting Status**

|**Aggregate**|**Individual**|
|---|---|
|% Respondents Displaced Currently|Self-Reported Hosting|
|% Respondents Recently Displaced|Self Reported Hosting IDPs|
||Self Reported Hosting Refugees|

Table 3: Operationalizing Hosting Status 24
# **4.2 Perceptions of Social Cohesion**

The outcome of interest is how respondents perceive various dimensions of social cohesion in their communities. The surveys capture each of the locally directed dimensions of social cohesion described above. Table 4 groups these measurement strategies by the dimensions of social cohesion from the qualitative exercise.

**Social Cohesion Dimension**

|**Relationships**|**Solidarity**|**Governance**|
|---|---|---|
|Perception of In-Group Relationships|Participation in socio-cultural activi|ties<br>Access to Basic Needs|
||with Other Ethnic Groups||
|Perception of Out-Group Relationships|Contact with Other Ethnic Groups|Access to Services|

Table 4: Operationalizing the Locally-Led Definition of Social Cohesion with Survey Responses First, to measure how respondents perceive the quality of their relationships, the survey asked respondents to report their perceptions of the quality of their relationships with their own ethnic group and with other ethnic groups. Two binary variables based on each respondents’ answers to these questions are used to measure relationships, with respondents answering either “Good” or “Very Good” coded as perceiving high-quality relationships.

Second, respondents report their willingness to participate in socio-cultural activities/ceremonies, attend the same place of worship, work together, marry members of other ethnic groups, and how often they have contact with members of other ethnic groups to measure solidarity. These questions are used to create measures of whether respondents participate in activities with other ethnic groups and whether they have contact with other ethnic groups.

Third, respondents answer questions about their perceptions of their access to basic services including accommodation, water, finding work, land, primary school for children and health care to measure governance. Additionally, a battery of questions enables respondents to report their access to civil status services (such as for registration of marriages, births, etc.) and access to state services for obtaining title deeds and other documents relating to land.

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These concepts are treated as separate dependent variables. Each variable is meant to capture a component identified by the focus group respondents as important for social cohesion in eastern DRC. Because the survey was carried out separately from the focus groups, however, the surveys cannot measure each of the presented in the concept map, but many of the relevant concepts overlap.

# **5 Survey Results**

## **5.1 Aggregate Relationships**

A series of linear regressions examine the correlation between levels of displacement and perceptions of social cohesion at the _groupement_ level, alternating independent variables between the percentage of respondents who self-report being currently displaced within a _groupement_ in a given survey wave and the percentage of respondents who self-report moving involuntarily within the past year. Each point estimate and confidence interval represent results from a separate regression, with the Y-axis noting the dependent variable.<sup>10</sup> Figure 4 shows that there is no significant relationship between current levels of displacement at the _groupement_ level at the time of enumeration and any dimension of social cohesion. In contrast, _groupements_ with a higher proportion of respondents who report involuntary movements are associated with significantly lower perceptions of solidarity and governance. Self-reported instances of involuntary movements in the community are negatively associated with perceptions

> 10The results of the analysis are plotted in coefficient plots. All results in the main text are presented as odds ratio plots with 95% confidence intervals (CIs). On each of the plots, the X-axis is the Odds Ratio (log scale), the dashed vertical line is the “line of null effect,” and the colored point is the estimate from each regression, with 95% confidence intervals. Estimates to the right of the dotted line signify positive and statistically significant relationships, estimates that intersect with the dotted line indicate results that do not reach statistical significance (defined as p= _._ 05), and estimates to the left of the dotted line indicate negative and statistically significant relationships. Each regression includes relevant controls, but the graphs only plot the displacement or hosting status variables to ease interpretation. Full regression tables are available in the Appendix, Section F.

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<!-- Start of picture text --> Perception of In−Group Relationships Perception of In−Group Relationships<br>Perception of Out−Group Relationships Perception of Out−Group Relationships<br>−1.0 −0.5 0.0 0.5 1.0 −1.0 −0.5 0.0 0.5 1.0<br>Participation with Other Ethnic Groups Participation with Other Ethnic Groups<br>Displacement Displacement<br>Currently Displaced Involuntarily Moved<br>Contact with Other Ethnic Groups Contact with Other Ethnic Groups<br>−1.0 −0.5 0.0 0.5 1.0 −1.0 −0.5 0.0 0.5 1.0<br>Access to Basic Needs Access to Basic Needs<br>Access to Services Access to Services<br>−1.0 −0.5 0.0 0.5 1.0 −1.0 −0.5 0.0 0.5 1.0<br>Regression Coefficient Regression Coefficient<br>(a) % Displaced (b) % Involuntarily Moved in the Past Year<br>Relationships Relationships<br>Variable Solidarity Variable Solidarity<br>Governance Governance<br><!-- End of picture text --> Figure 4: _Groupement_ Aggregated Correlations Between Displacement and Perceptions of Social Cohesion of out-group relationships (OR: -0.22; CI: -0.37 – -0.08), participation with other ethnic groups (OR: -0.37; CI: -0.55 – -0.20), contact with other ethnic groups (OR: -0.36; CI: -0.63 – -0.09), access to basic needs (-0.25; CI: -0.46 – - 0.03) and access to services (-0.23; CI -0.40 – -0.06). _Groupements_ with higher proportions of respondents who report being involuntarily moved in the past year are also negatively associated with perceptions of out-groups but are not significantly correlated with in-group relationships The discrepancy between the aggregate results for _groupements_ experiencing higher levels of current displacement versus those with higher levels of respondents who were displaced in the last year begs several questions. Of course, the negative relationship between involuntary movements may be a manifestation of low levels of social cohesion that create displacement in the first place, but the same can be said of _groupements_ with higher levels of current displacement. The 27
_groupement_ level data cannot measure the character of the displacement in any meaningful way, but analysis at the individual level can.

# **5.2 Individual Level Relationships**

Two survey waves posed additional questions on local displacement dynamics. While these additional questions restrict comparison with other survey waves, they provide the opportunity to unpack the mixed results found in the aggregate analysis. Poll 14 is a special survey that only samples cities (Ville de Goma, Ville de Beni, Ville de Butembo, Ville de Bukavu, Ville d’Uvira, Ville de Bunia and Irumu in particular) while Poll 15 is a representative sample of all _territoires_ in the three provinces.<sup>11</sup> These survey waves are labeled as “Cities” and “General” samples in the individual analysis. Analyzing these two surveys together enables the comparison of relationships by the local context, which may distort the impact that hosting has on perceptions of social cohesion.

Figure 5 plots the coefficients from series of logistic regressions to account for the binary nature of the dependent variables. The regressions include Province fixed effects and _groupement_ clustered standard errors to account for unmeasured context-specific dynamics. Responses are weighted by the inverse proportion of selection at the _territoire_ in each regression. The relationships between displacement dynamics and perceptions of each manifestation of social cohesion are analyzed separately by running 12 models for each independent variable (6 regressions for each sample).

The regressions are correlations and should not be interpreted causally. Hosting status and displacement flows are likely related to perceptions of social cohesion in indirect ways and the structure of the survey data limit the ability to specify the channels through which these relationships run. Each regression controls for characteristics that may influence respondents’ perceptions of social cohesion outside of the presence of IDPs or refugees in the local community such as province, gender, age, marital status, level of education, employment, and exposure to violence. 11Poll numbers correspond to the number wave in our larger project, as described and shown in Table 2.

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But hosting status is not randomly distributed in ways beyond these descriptive characteristics. The regressions additionally control for each respondent’s ethnic status in their community by calculating the percentage of respondents who self-identify as each ethnic group in each surveyed _groupement_ and creating an indicator variable for those who are members of an ethnic minority locally.

Figure 5 plots the coefficients of displacement status these logistic regressions, where the independent variable of interest is a binary indicator for self-reporting hosting either refugees or IDPs in your community, a binary indicator for self-reporting hosting IDPs in your community, a binary indicator for self-reporting hosting refugees in your community.

Figure 5 shows that the relationship between hosting and perceptions of social cohesion vary by context, sub-dimension of social cohesion, and the type of hosting. In cities, hosting is only positively and significantly associated with solidarity measures (participation with other ethnic groups (OR: 1.39, CI: 1.13-1.72) and contact with other ethnic groups (OR: 1.35, CI: 1.05 – 1.73)), but these results differ based on who is hosted. In cities, hosting IDPs is not significantly associated with participation with other ethnic groups, but the correlation between hosting refugees and participation is positive and significant (OR: 3.40, CI: 2.05 – 5.62). In contrast, contact with other ethnic groups is positively associated with hosting IDPs (OR: 1.89, CI: 1.41 – 2.53) in the general sample, but negatively associated with hosting refugees in cities (OR: 0.23, CI: 0.14 – 0.38).

Hosting IDPs is more consistently associated with higher perceptions of social cohesion across dimensions in the general sample. Hosting IDPs is positively associated with each social cohesion sub-dimension other than participation with other ethnic groups. Hosting refugees is positively associated with perceptions of out-groups (OR: 1.92, CI: 1.41 – 2.61) and contact with other ethnic groups (OR: 1.89, CI: 1.41 – 2.53) in the general sample, but insignificant for the other subdimensions. These differences suggest that IDPs and refugees pose different challenges to social cohesion even within the same region and that hosting status has different consequences for social cohesion in cities than in rural communities.

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30 <!-- Start of picture text --> Cities General<br>Perception of In−Group Relationships G G<br>Perception of Out−Group Relationships G G<br>Participation with Other Ethnic Groups G G<br>Contact with Other Ethnic Groups G G<br>Access to Basic Needs G G<br>Access to Services G G<br>0.5 1.0 2.0 0.5 1.0 2.0<br>Odds ratio (log scale)<br>Displacement G Hosting Displaced Persons<br>Relationships<br>Variable Solidarity<br>Governance<br><!-- End of picture text -->

# (a) Host (Any)

<!-- Start of picture text --> Cities General Cities General<br>Perception of In−Group Relationships Perception of In−Group Relationships<br>Perception of Out−Group Relationships Perception of Out−Group Relationships<br>Participation with Other Ethnic Groups Participation with Other Ethnic Groups<br>Contact with Other Ethnic Groups Contact with Other Ethnic Groups<br>Access to Basic Needs Access to Basic Needs<br>Access to Services Access to Services<br>0.5 1.0 2.0 0.5 1.0 2.0 0.1 0.2 0.5 1.0 2.0 5.0 0.1 0.2 0.5 1.0 2.0 5.0<br>Odds ratio (log scale) Odds ratio (log scale)<br>Displacement Hosting IDPs Displacement Hosting Refugees<br>(b) Host IDPs (c) Host Refugees<br>Relationships Relationships<br>Variable Solidarity Variable Solidarity<br>Governance Governance<br><!-- End of picture text --> Figure 5: Summary Plots of Logistic Regressions
Gender may influence how members of the host community experience and perceive their role as hosts. Since each of the samples are gender-balanced, Figure 6 re-reruns the logistic regressions above but after sub-setting the data by gender. Hosting IDPs is associated with improved perceptions of social cohesion among men for all sub dimensions other than access to basic needs in the general sample, but women’s perceptions of social cohesion are only positively associated with contact with other ethnic groups (OR: 1.26, CI: 1.01 – 1.56) and access to services (OR: 1.44, CI: 1.15 – 1.80). In cities, female respondents were more likely to report negative perceptions of in-group (OR: 0.59, CI: 0.41 – 0.84) and out-group relationships (OR: 0.63, CI: 0.44 – 0.90) when hosting IDPs. Women were less likely to participate with other ethnic groups (OR: 0.57, CI: 0.40 – 0.82) if they had IDPs in their communities. But men had positive associations for IDPs with relationships and solidarity in cities.

Combined, the results in Figure 6 indicate that gender is an important mediating factor in how hosting impacts perceptions of social cohesion. Women’s perceptions of social cohesion are generally negatively impacted by hosting. The presence of IDPs is positively associated with social cohesion for men, but not for women. Hosting refugees is similarly associated with improved perceptions of solidarity and relationships for men in the general sample.

# **6 Policy and Program Implications**

This study contributes to establishing forced displacement as fundamentally a development challenge that requires addressing complex dynamics, including the social causes of conflict, instability, and fragility. Social dynamics and cohesion in situations of forced displacement have potential far-reaching consequences for individuals and communities alike. Displaced persons are at risk of increased vulnerability and exclusion, especially in protracted situations. Their presence can be a source of instability and fragility for the communities that host them, especially in situations of internal displacement that see most displaced persons stay within the societal and institutional 31
32 <!-- Start of picture text --> Hosting displaced persons<br>Cities General<br>Perception of In−Group Relationships G G<br>Perception of Out−Group Relationships G G<br>Participation with Other Ethnic Groups G G<br>Contact with Other Ethnic Groups G G<br>Access to Basic Needs G G<br>Access to Services G G<br>0.5 1.0 2.0 0.5 1.0 2.0<br>Odds ratio (log scale)<br>Gender G Female Male<br>Relationships<br>Variable Solidarity<br>Governance<br><!-- End of picture text -->

# (a) Host (Any)

<!-- Start of picture text --> Hosting displaced Congolese Hosting displaced refugees<br>Cities General Cities General<br>Perception of In−Group Relationships G G Perception of In−Group Relationships G G<br>Perception of Out−Group Relationships G G Perception of Out−Group Relationships G G<br>Participation with Other Ethnic Groups G G Participation with Other Ethnic Groups G G<br>Contact with Other Ethnic Groups G G Contact with Other Ethnic Groups G G<br>Access to Basic Needs G G Access to Basic Needs G G<br>Access to Services G G Access to Services G G<br>0.5 1.0 2.0 0.5 1.0 2.0 0.1 0.2 0.5 1.0 2.0 5.0 0.1 0.2 0.5 1.0 2.0 5.0<br>Odds ratio (log scale) Odds ratio (log scale)<br>Gender G Female Male Gender G Female Male<br>Relationships Relationships<br>Variable Solidarity Variable Solidarity<br>Governance Governance<br><!-- End of picture text --> <!-- Start of picture text --> (b) Host IDPs<br><!-- End of picture text --> (c) Host Refugees Figure 6: Summary Plots of Logistic Regressions by Gender
context that caused their displacement in the first place.

The qualitative focus groups provide some important insights for international actors. International definitions of social cohesion may not match local realities. International humanitarian actors should keep abreast of the dimensions of social cohesion beyond simply the limiting of violence. The qualitative and participatory exercises described in this paper could be re-purposed for development aid, which may not fit local needs (Ferguson 1990).

In addition, the findings show that the relationship between hosting displaced persons and perceptions of social cohesion is not necessarily altogether negative. Instead, refugees and IDPs are associated with host community perceptions of social cohesion differently; refugees in general correspond to lower levels of social cohesion than IDPs. We also find that hosting in cities and general population exhibit some important differences. The backlash frequently observed in refugee studies may not be present in situations of internal displacements and such an effect can be mediated by contextual factors of displacement.

The results suggest that programming that seeks to address the needs of host communities in contexts of forced displacement may require fundamentally different approaches than those that are used in refugee or camp-based displacement scenarios. Programmatic decisions should focus on supporting host communities even in informal contexts but remain cognizant and avoid uneven distributional consequences. Programming that seeks to address the needs of displaced persons in such scenarios must consider how multiple displacement or hosting during protracted conflict presents different challenges than single, long-term displacements.

Humanitarian actors must additionally remain cognizant of gender. The analysis suggests that hosting may disproportionately and negatively impact women, in situations with IDPs in cities. Female respondents in cities were more likely to have negative perceptions of in group and out group relationships and were less likely to participate with other ethnic groups if they had IDPs in their communities. In contrast, hosting IDPs was associated with improved perceptions of social cohesion among men for all sub dimensions other than access to basic needs. International hu33
manitarian actors responding to IDP flows in cities focus programming that encourages the active participation of women in the host communities. The results indicate that inter-ethic relationships are a particularly fruitful area to target with programming among women in cities.

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