Matthew Osborne: Procedural Paper
What is the effect of conflict exposure
on individual social reintegration?
Intellectual Puzzle
Why is it that after a period of conflict some individuals manage to successfully socially reintegrate, building strong and positive
social relations with others, whereas some do not? Is it because their experience during the conflict has changed their attitudes and
behaviour towards others, and if so, in what way?
1.
Introduction and Research Questions
This project is interested in how individuals socially reintegrate following a period of conflict. To explore this
topic the research will adopt an essentially experimental approach with supportive and complementary
secondary methodologies. The following central research questions will frame the investigation:
1.
2.
3.
4.
What social ties exist between community members in communities recovering from civil conflict?
What effect does conflict have on the formation of social ties?
What effect does conflict have on the character of reported social ties?
What other factors may be affecting social tie formation?
An appreciation of the significance of the impact that conflict has on development has become increasingly
recognised by theorist and practioners (Blattman and Miguel, 2010, WorldBank, 2011). Conflict - scholars
argue - destroys human and physical capital and hence the capacity for collective action (Colletta and Cullen,
2000, Collier et al., 2003 ); damages norms of reciprocity and interpersonal trust (Posner, 2004, Letki, 2008);
polarizes communities along socio-economic cleavages (Wood, 2008) and destroys formal and informal
disputes management mechanisms (Ahmed and Green, 1999). In an environment of extreme
underdevelopment - often associated with regions undergoing post-conflict recovery 1 – such poverty and
developmental vulnerability may act as a compounding factor to existent societal fragmentation and place
significant additional pressure on communities who are attempting to recover from the traumatic shock of
violent conflict (Manservisi and Mény, 2009, WorldBank, 2011).
1
See, Stewart and FitzGerald (2000) & Matovu and Stewart (200) for a review of the social and economic consequences of
conflict.
1
The benefits of high interpersonal trust in economic systems of exchange is well recognised2, beyond these
direct economic benefits to individuals of high interpersonal trust, high societal trust levels decrease the
likelihood of ‘spoiler’ activities threatening brokered peace agreements at the community level as well as
facilitating the essential ‘first step’ social integration of individuals (Stedman, 1997, Walter, 1999, Lamb, 2008,
Lamb and Dye, 2009). It is no surprise then that trust-promotion is explicitly highlighted within the postconflict intervention literature and naturally underpins efforts to promote social integration. As Spear
(2006):176 suggests, interventions that promote trust and lead to increased social integration are “most
directly linked to establishing a lasting peace”. Woolcock and Narayan (2000), suggest that strong social
cohesion is especially critical for implementing sustainable development for communities recovering from
violent civil war. As do, Collier (2003 ) and Pouligny (2004) who argue that ‘political’ and ‘economic’
reintegration of populations is only possible after successful ‘social integration’: when a community’s
individuals achieve good working relations with each other.
Despite the acknowledged significance of successful social reintegration, there is a scarcity of quantitative
studies that explores this question at the micro-level. Macro-level analysis is unsuitable for the exploration of
the question of individual-level social integration, thus a micro-level study would respond to this shortcoming
within the existing conflict literature. As Blattman suggests “a major goal of civil war researchers within both
economics and political science in the coming years should be the collection of new data, especially extended
micro-data sets.” (Blattman and Miguel, 2010), Pg. 71.
Using laboratory experiments to examine the causes and consequences of conflict is a relatively new field but
one which presents exciting possibilities. To date, the vast majority of the studies which have used an
experimental approach to examine aspects of conflict have concentrated on the ‘causes’ of conflict
occurrence (see Abbink (forthcoming) for a comprehensive review). In contrast to most of these cause-focused
studies, which have attempted to create models of behaviour to test in a lab, this research will utilise a number
of artefactual field experiments to measure the modulating effect that conflict exposure has on individuals’
ability to form social ties and the character of existing ties: the most fundamental unit of social interaction
(Coleman, 1994).
Following this introductory section, the paper will briefly review the existing experimental literature that has
explored conflicts and social ties(2), followed by an overview of the conflict in Northern Uganda which will
be the research location for this project (3), followed by an examination of the concept of social reintegration
2
Arrow (1974) explores in detail the importance of trust within economic exchange and Karlan (2009):1 links trust with social
ties and social networks to suggest that: ” If trust is low, poverty can persist because individuals are unable to acquire capital,
even if they have strong investment opportunities. If trust is high, informal transactions can be woven into daily life and help
generate efficient allocations of resources.”
2
itself where an explanation of how dyadic social ties measurement will be used as an dependent variable (4),
followed by a methodological description (5), chapter plan outline (6), research timeline (7) and finally the
research outcomes (8) – with three appendixes included at the end of the paper.
2.
Experimental Literature: Conflict & Social Ties
We know that the components of what makes up social reintegration are abstract and almost intangible
conceptions (see below). In practice, they can most clearly be observed only through behaviour: how
individuals interact with others.
Qualitative accounts of reintegration provide perhaps the most complete and nuanced reports of individual
reintegration processes (Utas, 2003, Finnegan, 2010), however such studies have limited explanatory power
beyond the range of their given context (Weinstein and Humphreys, 2005). Questions relating to
reintegration and pro-social behaviour3 do sometimes occur in traditional survey questionnaires but the
degree of abstraction and concerns surrounding social-desirability biases raise doubts about the reliability of
such methods (Greenhill and Major, 2007)4. Certainly, experimental methods themselves have their own
methodological challenges, particularly when errors in design and implementation offer the potential to bias
resultant findings. Nonetheless, and with the above considerations in mind, a behavioural measurement of
‘social reintegration’ - which uses supplementary research methods to complement, inform and triangulate
the investigation - is more appealing (Jackson, 2009).
Though it is rare to use behavioural games to explore this subject, such an approach is not without precedent;
one of the small number of ‘consequence’ experimental studies of particular relevance to this project is the
work by Voors et al (2003) which experimentally examines the impact of exposure to conflict on social and
risk preferences in post-conflict Burundi. Whilst such preferences have been examined in a variety of
contexts (see Cardenas and Carpenter (2008)), this paper was the first to use experimental methods to gauge
the effect of violence on human decision making. Whitt & Wilson (2007) seek to identify the current attitudes
between ethnic groups who had previously been at war by using adapted Dictator Games to measure
attitudinal preferences between Bosnians, Croats and Serbs and specifically to see to whether expected
fairness norms were observed. The possibility that conflict exposure affects the ability to cooperate has been
explored experimentally in a number of papers. Coleman and Lopez (2010) use Trust Games to measure the
3
Such as, ‘Do you generally trust your neighbours’, etc.
4
Indeed, we know from Glaeser et al, (2000), that interpersonal trust measurement is vulnerable to differences between
reported and observed trust between individuals.
3
impact that a ‘Peace and Development Plan’ has had amongst conflict-affected communities in Colombia.
Fearon and Latin (2009) conduct a similar artefactual field experiment to examine the impact of a ‘community
driven reconstruction’ program to promote ‘social cohesiveness’ in post-conflict Liberia using a Public Goods
Game. Whilst, Gilligan et al (2011) use four games (Lottery, Trust, Dictator and Public Goods) to measure
the effect of conflict exposure on different aspects of ‘social capital’ at the community level in post-conflict
Nepal.
Social tie and social network formation itself has become of ever increasing interest in a range of academic
fields including sociology, economics, psychology and biology (Borgatti et al., 2009). It is well recognised
within sociology, in particular, that a person’s social ties and consequent social network has a significant
influence on their individual and group behaviour (Jackson, 2009, Granovetter, 1973, Hooper, 1976, Feld,
1981, Granovetter, 1985). Within the discipline, the social tie explanatory theory that ‘homophily’ - or likeattracting-like - drives the probability of tie formation is one of the most accepted and least challenged
concepts in social science. (McPherson et al., 2001, Monge and Contractor, 2003)5.
Social tie and social network formation itself has become of ever increasing interest in a range of academic
fields including sociology, economics, psychology and biology (Borgatti et al., 2009). In more recent times,
the role that a person’s social ties have on their behaviour and attitudes has begun to be explored by
experimentalists (van Dijk et al., 2002, Sonnemans et al., 2006)6. Experimentalists tend to examine social ties
through a network lens and thus use ‘social proximity’ – which describes the degree of separation of one
individual to another through a connecting network - as an explanatory variable. Over recent years, there have
been a large number of studies using Dictator Games to consider the explanatory effect of social distance –
including both procedures and information about the recipient – on levels of giving, (see (Frohlich, 2004) for
a review).
Most experimental research in this area uses laboratory experiments and artificially generated ‘social networks’,
however some recent studies have tried to take advantage of individuals’ real-life social networks. Leider et al
(2009) use a ‘coordination task’ to help map participant friendships and then examine the role that social
context has on altruism and reciprocity in a series of adapted Dictator Games. Brañas-Garza et al (2010)
conduct a similar experiment with undergraduate students. Goeree et al., (2003) use Dictator Games
amongst school pupils at a boarding school to argue that giving is explained by social distance but that social
distance itself is dependent on homophilic attraction.
5
See Appendix iii for a fuller explanation of the theory of homophily and the selection of relevant state and value
characteristics.
6
For a review see, JACKSON, M. O. 2008. Social and Economic Networks, Princeton, Princeton University Press.
4
As suggested, there have been a small number of studies to explore conflict and others that have explored
social ties; however, it is thought that the suggested methodological and thematic combination proposed
within this study will be unique.
3.
Research Location: Northern Uganda
One of the worlds’ longest civil wars has been fought in Uganda’s northern districts, particularly in Gulu,
Pader and Kitgum regions which constitutes the hereditary home of the Acholi people. The Lord’s Resistance
Army (LRA), led by Joseph Kony, has fought the Ugandan central government since 1986 following the rebel
groups formation from remnants of the short lived ‘Holy Spirit Movement’ rebellion led by Alice Lakwena
(Allen, 1991, Behrend, 1999, Van Acker, 2004). Initially the LRA sought to capitalise on regional tensions by
claiming to represent the interests of the northern Acholi against the National Resistance Movement (NRM)
administration led by Museveni in central Kampala. Although significant tensions and historical disparities
between the Northern districts and the rest of Uganda were indeed a reality, the LRA failed to garner
significant support from the local population and critically the blessing of the Acholi elders and lineage heads
(Van Acker, 2004). As a consequence the LRA quickly began to target the civilian population for supplies
and pursued a policy of abduction and forced recruitment.
Between 1986 -2006 attacks were widespread with an estimated 25 percent of all Northern communities
suffering direct attacks by the LRA (Ssewanyana and Bategeka, 2007) which resulted in an estimated 80,000
individuals being abducted from their homes (Blattman and Annan, 2010). Although adolescent males were
the primary targets, females and males of all ages were also taken. Dependent on age and gender, abductees
would be forced to act as fighters, porters/camp attendants or as forced ‘wives’ to LRA members of
sufficient rank and power (Beber and Blattman, 2011, Blattman, 2010).
By the active targeting of the civilian population by government and rebel forces the conflict shares
characteristics with those in neighbouring Sudan and DRC and, as with those conflicts, it led to massive
population displacement. ‘Voluntary’ displacement of civilians fleeing LRA attacks became ‘forced’
displacement by the Ugandan military (UPDA) from as early as 1996 and particularly following the
implementation of the much-criticised counter-insurgency operation ‘Iron Fist’ in 2002. As a consequence
1.6 million people, or 90 percent of the total population of northern Uganda, were forced to live in
displacement camps (IDMC, 2010) where population density reached 1700 people per hectare with
approximately 95% living in absolute poverty (Oxfam, 2006). Not only did this displacement have
significant consequences for individual health, development and well-being indicators (Ciantia, 2004, Accorsi
5
et al., 2005, Cochrane and Harris, 2009) but also for the nature of pre-war Acholi social structure and
community integrity (Nordstom, 2004, Finnstrom, 2008).
A survey conducted in 2005 highlights the widespread impact of the conflict on the civilian population; it is
estimated that the conflict has caused over 100,000 deaths in its 24-year tenure (Resolve, 2010), 40% of
respondents reported having been abducted by the LRA for at least one day, 45% had witnessed the killing of
a family member, and 23% had been physically mutilated at some point during the conflict (Pham et al., 2005,
Vinck et al., 2007). The scale of effect that this conflict has had on the population has led some
commentators to use the phrase “social torture” to describe the nature and degree of intentionality of the
suffering inflicted upon the population by both UPDF and LRA troops during the conflict (Dolan, 2009).
The Juba Peace Talks – facilitated over a two-year period from 2006-08 by the government of South Sudan –
failed in the objective of reaching a signed peace agreement between (LRA) and the government of Uganda
(Kuperman, 2009). Nonetheless, the withdrawal of support from Sudan for the LRA led to Kony and a small
number of LRA rebels fleeing into the DRC which has resulted in consequent period of sustained relative
peace and security in Northern Uganda. Since 2008 the displaced population of the region has begun to leave
the IDP camps: according to the latest OCHA report, 92% of former IDP’s have now returned to their old
homes or to new settlements outside of the camps. “The large-scale returns indicate IDPs’ growing
confidence in sustainability of the current peace in northern Uganda, with the LRA moving its theatre of
operation outside the border. However, for the 1.8 million affected, the situation on the ground can be
characterized neither as an end of displacement nor the achievement of lasting Durable Solutions. (OCHA,
2010):1”
4.
Conceptualising Reintegration
There continues to be confusion over efforts to create a cohesive conception of ‘reintegration’: Nilsson (2005)
goes as far as to suggest that reintegration is essentially a ‘theoryless field’:35. Prevailing reintegration
discourses underline the need for conceptualising or approaching post-conflict reintegration as constituted by
distinct social, economic, psychological, political and security considerations rather than as part of in a unified
and comprehensive combined theoretical approach (Kingma, 1997, UNDP, 2001, Kingma, 2002, Pugel, 2007,
Berdal and Ucko, 2009). As a consequence, the discourse on reintegration is invariably divided into more
manageable economic, political, and social components.
This study accepts that there is still much to do to generate a truly unified and actionable conception of
reintegration. Whilst acknowledging the critical importance of consequent political and economic
reintegration (see appendix I); this study will concentrate on the ‘social’ aspect of reintegration which the
6
DDR and post-conflict literature repeatedly argues is the ‘essential first-step’ towards wider reintegration of
individuals, communities and ultimately states.
Social reintegration relates to the achievement of positive day-to-day interactions between members of a
community (Brañas-Garza, 2007). Despite growing interest, there remains little clarity and consistency in
how this term is employed: “In fact, the theoretical location of social cohesion has "floated" among various
interrelated constructs, creating tremendous confusion” (Friedkin, 2004):413. The inception of the concept
of social (re)integration is rooted in Durkheim’s seminal work on social conditions and suicide (Levitas, 1996),
but since then the discourse has encompassed aspects of evolutionary biology, psychology, economics,
sociology and anthropology (Eckel and Grossman, 1996, Easterly, 2001, Frohlich, 2004, Reynal-Querol, 2002,
Vanderschraaf, 2006).
Social integration is variously defined to refer to the presence of strong social bonds reflected in, for example,
positive attitudes (or at least tolerance) towards members of the outer group (Tajfel and Turner, 1986, Pillutla
and Chen, 1999, Bowles and Gintis, 2004); greater levels of interpersonal trust (Glaeser et al., 2000, Posner,
2004, Spear, 2006); the presence of strong social bonds reflected in, for example, levels of cooperation or
greater propensity to contribute to a common good (Putnam, 1993, Putnam, 2000, Bowles and Gintis, 2004,
Coleman, 1994, Easterly et al., 2006, Fearon et al., 2009, Gilligan et al., 2011); the presence of formal and
informal networks—especially, institutions to manage and resolve disputes peacefully (Tajfel and Turner,
1986, Varshney, 2001); or to all of the above (Colletta and Cullen, 2000, Rankin et al., 2007, Letki, 2008).
Friedkin (2004) highlights the problems of oversimplifying the concept of social cohesion and suggests that
the term should be thought of, not as a ‘unidimensional’ concept – as is often described in the DDR literature
– but instead as a multidimensional concept that recognises the different aspect of social integration within a
generalised society7.
Such conceptual complexity poses significant challenges (as well as interesting possibilities) to the researcher
of post-conflict reintegration. For the purposes of this study however, – which will adopt an essentially
experimental quantitative approach - it is important that a measurable aspect of this rather vague field can be
captured.
7
For example, a given community may put more emphasis on interpersonal trust while others may put more emphasis on
contributions to generalised public goods - but this difference would not necessarily suggest that one is more integrated than
the other.
7
The ‘building block’ of dyadic social ties provides just such an observational unit: as whatever more complex
interactions may be occurring above the level of individual social ties, these more-complex interactions
ultimately depend upon - and are shaped by - the fundamental existence and character of these ‘elemental’
dyadic relationships. As Coleman (1994):43 suggests, “Social relations between two persons are, of course, the
building blocks of social organization. These relations can be seen as building blocks for much societal
organization. Social organization that grows, as in a community or a sprawling social network, is an amalgam
of such relations.”
5.
Methodology
Below, is a description of the research questions and the linked methodologies that will be used to address
them.
Question: What social ties exist between community members in communities recovering from civil
conflict?
Method: A social network survey will be implemented with a group of 20 randomly selected community
members and the existence (or not) and type of social ties that exist between these individuals and all other
community members will be recorded. Supplemental to this self-reported measure, the social network survey
will include generalised questions relating to socio-economic characteristics known to be of relevance to
homophilic attraction.
Question: What effect does conflict have on the formation of social ties?
Method: To capture the degree of conflict exposure experienced by individual respondents, an adapted
Brück et al (2010) conflict module which will be added to the survey. This module provides a
multidimensional measurement of conflict exposure that provides data that may be thematically aggregated or
used to analyse the effect of specific variables8. (See appendix II for more an expanded review of quantitative
conflict measurement methods). Following collection, data from the conflict exposure module, individual
survey and social network survey will be analysed to identify what effect the degree of exposure has had on
the formation of self-reported social ties between individuals within the community.
Question: What effect does conflict have on the character of reported social ties?
Method: As recognised, the reliability and accuracy of findings from stand-alone self-reported measurements
of social reintegration are open to question and consequently and, in complement to the implementation of
the social network survey, a series of behavioural games will be played with a sub-sample of the original 20
community members. These games use incentivised decision making options to elucidate the actual
8
See Bruck et at BRÜCK, T., JUSTINO, P., VERWIMP, P. & AVDEENKO, A. 2010. Identifying Conflict and Violence in Micro-Level
Surveys. Households in Conflict Network Working Papers, 79. – which provides a detailed explanation of the conflict module and
its method of conception, design and implementation.
8
behavioural preference of participants towards others9 and thus have the ability to capture and quantify a
critical aspect of dyadic social ties: interpersonal trust held between two community individuals.
+
Where
= Strength of Social Ties (as measured by trust and trustworthiness in behavioural games),
=
conflict exposure as measured by the conflict exposure module, and
= socio-economic, state and value
characteristics known to be of importance to homophilic attraction.
Question: What other factors may be affecting social tie formation?
Method: To better inform the data inference and to gain a more nuanced understanding of the history and
particular character of the research location a number of key-informant interviews will be conducted in each
research location. Furthermore, a section of the individual survey will include semi-structured questions that
seek to explore specific events, personal histories or community characteristics that may influence the
generalised findings from the social network surveys, conflict module and behavioural experiments.
6.
Experimental Protocol
An expanded description of the experimental aspect of the research design is included below. The design
describes firstly how the experimental hypotheses were identified (i), followed by a provisional description of
how the site and participant selection will be conducted (ii, iii), an explanation of the innovative participant
game pairings (iv), the experimental treatment table (v), an explanation of the games that will be played (vi)
and how the payments will be made (vii).
The experimental design itself will be tested in a preliminary site visit and adapted based on a review of its
implementation.
i:
Conflict Theory: Anarchy and In-Out Models
Civil war could reduce the strength of social ties and social networks in a number of ways. What might be
described as the ‘anarchy’ model would be where a simple updating story could imply that civil conflict
creates a lack of trust: plausibly people are more prone to victimisation during civil war than during times of
peace. If after each instance of victimisation people update their prior beliefs that others are not trustworthy
then society-wide levels of trust will decline. Should the institutions of state become actively involved in the
conflict on one side against another, as was the case in northern Uganda, then societal trust-loss may plausibly
be exacerbated (Vanderschraaf, 2006, Mislin et al., 2011).
9
Rather than their reported preferences from the SNS.
9
An alternative proposition is that the shock of violent conflict tests the strength and resilience of existing
social ties and produces an ‘in-out’ trust model. In such a model (developed from social identity theory, see
(Tajfel and Turner, 1986)) the strength of ties that persist – or pass the ‘shock-test’ - becomes positively
reinforced, where as others that had failed to persist become dramatically weaker. Such a mechanism seems
particularly plausible to ethnic or sectarian based conflicts where former close-associates can swiftly become
members of an enemy ‘other’ group (Easterly, 2001, Bowles and Gintis, 2004). Such a process would
promote a reinforcing cycle of in-group over out-group preference which would be expressed by individuals
increasingly relying on close friends and family as insurance against the potential threat of ‘others’ within the
community (Bowles, 2008).
A Trust and Dictator game will be used to measure and explore the levels of trust between individuals at
different social distances amongst a conflict-exposed population.
Primary Hypothesis (in-out model): Individuals with high conflict-exposure will show greater trust towards
socially close groups and reduced trust towards socially distant groups, than will be found amongst individuals
with low levels of conflict-exposure.
Secondary Hypothesis (anarchy model): High conflict exposure will reduce trust across all treatments groups.
ii:
Sampling: Site Selection
Sites for these experiments will be selected from the Kitgum district of Northern Uganda. Recent
quantitative research has demonstrated that the risk of violent attack against communities in the region was
not affected by any pre-war household or community characteristics (McIlwaine, 1998), a finding supported
by post-war surveying and qualitative interviews with former rebels who also indicated that the LRA had no
political or ideological imperative to target specific villages or settlements (Blattman and Annan, 2010);
furthermore the ACLED ArcGIS dataset produced by The Peace Research Institute Oslo (PRIO) supports
these assertions (Raleigh et al., 2010). The only identifying factor was the proximity of a given community to
the Sudanese border (Cramer, 2002): which is logical as the LRA launched raiding attacks from its bases in
Southern Sudan, a pattern found in this and other regional conflicts (Hegre and Sambanis, 2006).
To encourage variation in the exposure to conflict variable, potential sites will be geographically stratified into
4 banded areas: starting from the area closest to the border of Sudan and expanding away from the border to
the most distant point in the district10. Within these 4 banded areas, 1 nodal settlement (NS) will be selected11.
10
In addition to the sites banding, the exact distance in kms to the Sudanese border will be recorded.
11
Due to the decentralised administration of the Ugandan government with its strongly hierarchical Local Committee system,
primary schools are administered at the local level by the relevant LC1. As public institutions, these schools service the
10
From each of these nodal settlements, a random selection of 3 surrounding settlements (SS) will be made,
which together with the nodal settlement, will total 4 research locations per nodal settlement. From each of
the 16 settlements, 30 participants will be invited to attend a ‘research workshop’ at the local primary school:
totalling 480 participants. Participants in the anonymous X treatment of the trust and dictator games will be
drawn from a pool of 12 ‘extras’ drawn from the 4 nodal villages, adding a further 50 participants to the total
participant number.
The experiments will be run on 1 day, divided into in ‘morning’ and ‘afternoon’ sessions. Within each session
participants from 2 of the 4 settlements will be asked to attend12.
Band
iii:
NS
SS
Players Per
Extra Treatment
Total
Experimental
Settlement
Players per NS
Participants
Sessions
1
1
3
30
12
132
2
2
1
3
30
12
132
2
3
1
3
30
12
132
2
4
1
3
30
12
132
2
528
8
Participant Selection
Participant selection will be a multistage process which incorporates the conducting of a social network
survey (SNS)13. From selected 20 participants invited to participate in the SNS ´phase, a stratified random
selection of 6 ‘central player’ (CP) individuals will be made who will be invited to participate in the research
surrounding settlements and as such act as a reasonable geographic representation of population distribution. In addition, they
provide ideal facilities for running field laboratory experiments.
12
This method is modelled on the same process that I oversaw in previous experimental research projects in Uganda; see
SAMBANIS, N. 2004. What Is Civil War? Journal of Conflict Resolution, 48, 814-858. These workshops had a 97% attendance rate.
13
In this description, I do not include the potentially lengthy advocacy and trust building work that will be required to
encourage recruitment. However it is recognised that the local affiliates will be extremely helpful during this process. Having
conducted near-identical exercises previously in Uganda, India, Ethiopia and Nigeria in more than sixty communities and
successfully recruited more than 5000 participants for similar studies, I am confident that I will be able to achieve the required
participation.
11
‘workshops’. This will simply involve alphabetising the adults list, then draw a random number14 and invite
the corresponding adult to participate. Should they not wish to, the person immediately below on the list will
be invited and so on until the required number is achieved.
The second stage of the participant selection will involve the completion of a socio-economic survey and
SNS by the 6 ‘central player’ selected participants. These participants will be asked to designate all community
members as either a ‘Friend’, ‘Close Family Relative’, ‘Distant Relative’, ‘Other Community Member’, or
‘Stranger’ 15. These categories were selected due to their known importance in social interactions and
specifically as kinship, lineage and clan associations are of particular importance in the region and these
categorisations will be translated into the appropriate Acholi language version (Allen, 1991, Behrend, 1999,
Finnstrom, 2008). From within each group of participant-designated community members, a random
selection of 1 representative individual will be made: generating a 6 member subgroup of participants16. Once
the subgroup members have been identified, a standard survey that captures socio-economic characteristics as
well as a SNS will be conducted which will crucially also capture exposure to conflict.
iv:
Experimental Pairings
Data from the SNS phase of the research design will provide the subsequent participant pairings in the
experimental stage. This stage will be conducted several days before the experimental sessions. Such
procedural timing offers a number of advantages; firstly it reduces the pressure on the research team which
will improve accuracy; secondly it allows time for the analysis of the social network analysis and for the
identification of the game pairings (see below) and; thirdly by separating the collection of the social network
analysis and survey information, concerns over experimental framing are reduced.
During the experimental sessions the 6 CPs community members will be divided randomly into Player 1 and
Player 2 roles (with 3 CPs for each role) and – in different treatments – the subgroup members will play as
the respective alternate roles. The CP participants will be given a unique ‘game identification’ number and
related subgroup members will be given the same ID number with an attached prefix: a,b,c,d,x.
14
Random number tables will be taken from Random.org
15
Within each categorisation significant additional information will be collected. For example, if a community member is
identified as a ‘Friend’ details of their friendship will be requested, such as the period of time they have been friends/known
each other as well as how often they interact, etc see STEWART, F. 2002. Horizontal inequalities: a neglected dimension of
development, WIDER.
16
It is anticipated that in the small rural communities of northern Uganda which tend to have <100 adults it is unlikely that any
‘strangers’ will be found and therefore it is likely that the subgroup will be limited to 5; however recent experimental work has
recognised the potential bridging role that strangers can have in reintegrating communities. D'EXELLE, B. & HOLVOET, N. 2011.
Gender and Network Formation in Rural Nicaragua: A Village case study. Feminist Economics, 17, 31-61.
12
v:
Experimental Treatments & Pairings Summary
Lottery Game
All Players
Total Observations
n
480
Trust Game
Player 1
Player 2
Treatment #
n
n(a)
Treatment A
48
n
n(b)
Treatment B
48
n
n(c)
Treatment C
48
n
n(d)
Treatment D
48
n
n(x)
Treatment X
48
Player 1
Player 2
Treatment #
n(a)
n
Treatment E
48
n(b)
n
Treatment F
48
n(c)
n
Treatment G
48
n(d)
n
Treatment H
48
n(x)
n
Treatment Y
48
Dictator Game
Dictator
Recipients
n
n(a), n(b), n(c), n(d), n(x)
480
n = Central Player
n(a) = Friend of Central Player
n(b) = Close Relative of Central Player
n(c) = Distant Relative of Central Player
n(d) = Community Member to Central Player
n(x) = Anonymous
13
vi:
Experimental Protocol & Games
All game players will be gathered together in a public space (ideally a school hall or similar). Introductions
will be made and an outline of the time frame of the experimental session will given to the participants17.
Participants will be informed that they will take part in a series of games and, dependent on their decisions,
that they will have the opportunity to earn some money. All participants will be given a game card with a
unique identification number and will be told that they are to retain this card until the end to ensure they
receive their payments. Specific game instructions will not be given at this stage but rather at the beginning of
each experimental session to ensure maximum information retention, comprehension and clarity.
Participants will be told that they will be separated into smaller groups in order to play the games and for the
duration of these sessions they must not communicate with each other. Participants will then be called in
pre-determined groups by game card number and taken from the central congregation hall to the game rooms
by pairs of enumerators.
Trust Game
The game will be conducted as a series of 5, one-shot BDM version-trust games (Berg et al., 1995). Player 1s
will play as first movers and Player 2s as second movers. The Player 2’s identities will be pre-determined by
data drawn from the SNS phase (see above). A final treatment game will be played with an anonymous
community member in order to determine a reasonable baseline of the player’s experimental behaviour
(Leider et al., 2009). In order to reduce any potential experimental demand effect, the ordering of the game
treatments will be randomised prior to the experimental session.
The Player 1 will be told the identity of each Player 2 at the beginning of the round and be told that Player 2s
will know the endowment Player 1 received and what offer they made. Player 2s will be told information of
endowment and offer as well as the identity of the Player 1. Player 1 endowments will be 10,000 Shillings18.
Player 1s will therefore play five rounds against a designated friend, close family relative, distant relative,
community member and an anonymous player with the first round will always being played with the
anonymous member. To avoid framing concerns, at no point during the experimental sessions will the Player
2s or game rounds be referred to by their social network classification but rather their real names.
17
It is anticipated that the experimental session (lottery, trust, dictator and pay-offs) will take no more than 2 hours to
complete.
18
The First mover endowments will be given in 5 x 2000 Shilling notes. The current estimated daily agricultural labour rate in
Uganda is ~4000 Shillings.
14
After all first offers are made; the relevant Player 2s will be presented individually and in private their offers
by an enumerator and then asked how much they would like to return to the respective Player 1s.
Dictator Game:
The dictator game will be played as standard one-shot game and take place immediately after the trust game.
The Central Players will act as dictator and be given an endowment of 20,000 Shillings which they will be
asked to divide amongst the same matched game players (n(a,b,c,d,x)). Dictator decisions will be made in
private.
Generosity, as a motivation for giving could also act as a confounder of behaviour in the trust game and
therefore the dictator game will have a secondary purpose of acting as a control to trust game behaviour (Cox,
2004).
Risk Lottery
Some authors have noted that experimental methods in general, and the standard trust game in particular, do
not allow one to distinguish between the behaviour of a highly trusting person and a person with low levels of
risk aversion (Eckel and Wilson, 2004, Karlan, 2005)19. It has been shown that persons with greater tolerance
for risk may exhibit behaviour that on the surface appears more trusting but is, in actuality, a greater
willingness to gamble on the cooperative behaviour of the other player, and thus as a consequence, risk
preferences could become an important potential confounder in the analysis of the components of pro-social
behaviour (Schechter, 2007b, Houser et al., 2010, Schechter, 2007a).
To ameliorate this potential, a simple risk-preference game will be implemented which mirrors the first mover
stage of the subsequent trust game.
All participants (except the n(x) players) will play the lottery game in 1, one-shot round. The rules of the risk
game are as follows: the investor is given a 10000 Shillings endowment - the same amount they will be given
in the trust game - and is then given the same six investment choices to make: to invest 0, 2000, 4000, 6000,
8000 or 10000 Shillings. The experimenter then invites the participant to roll a die to determine the investor’s
payoffs. A roll of one means the participant loses her investment, two means she recovers half her
investment, three means she recovers her investment, four means she earns 1.5 times her investment, five
means she doubles her investment, and six means she earns 2.5 times her investment.
19
Or indeed are particularly generous: GOEREE, J. K., HOLT, C. A. & PALFREY, T. R. 2003. Risk averse behavior in generalized
matching pennies games. Games and Economic Behavior, 45, 97-113.
15
For example, if the participant invested 2000 Shillings of the initial endowment and subsequently rolled 4, she
would have earned 3000 Shillings from the lottery game, added to the remaining endowment of 8000,
resulting in a final payoff of 11000 Shillings.
vii:
Pay-offs
Payoffs for Players will be their earnings from 1 randomly selected game (including the lottery, trust and
dictator rounds). To avoid disappointment, all players will receive a minimum of 5000 Shillings for
participation. To avoid framing concerns for the subsequent experimental stages the game pay-offs will be
paid at the end of the experimental session20.
7.
Chapter Outline
Presented are the intended chapter outlines of the PhD. The three central data chapters are designed to
address a specific research question using complementary methods and are intended to be presented as
journal articles. The first chapter will be a substantial generalised introduction including relevant thematic
literature review and the final chapter will present the thesis findings and general discussion.
Chapter 1: Background and Motivation
Chapter 2: Existence of Social Ties
Chapter 3: The strength of Social Ties
Chapter 4: Issues affecting individual reintegration
Chapter 5: Conclusion and Discussion
20
During the initial experimental instructions delivered to the assembled participants it will be explained that payments will be
made from one randomly selected round to deter the unlikely existence of pre-game reimbursement contracts.
16
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20
Appendix I: Economic & Political Reintegration
Economic Reintegration
Economic reintegration refers to efforts to provide meaningful occupations for individuals in order that they
may provide means to support themselves and their dependents. In the Disarmament Demobilisation &
Reintegration (DDR) literature the economic reintegration component is given high priority. Some authors
argue that the central aim of rebellions is the pursuit of economic profit (Collier and Hoeffler, 2004), or at
least over time, the economic benefit of conflict overrides the original motivations for its inception (Berdal
and Malone, 2000, Malone and Nitzschke, 2005, Schechter, 2007). This suggests that taking part in a civil war
may be economically profitable to individuals: through direct benefit in the form of payments, extortion, theft
and looting; through the control of illegal mining, narcotics or smuggling operations; or through the use of
violence to obtain access to land, water or other environmental resources (Berdal, 1996, Keen, 2000).
According to most theorists and practitioners, the argument follows that the best means to prevent a renewal
of violence is to therefore ensure that the economic demands of existing or potential combatants are fulfilled:
thus removing the motivation to engage in violence (Özerdem, 2002, Spear, 2002, O’Brien and Penna, 2008).
How such demand-alleviation is achieved is matter of continuing debate (Goodhand and Sedra, 2010,
Lindberg and Orjuela, 2011).
Political Reintegration
Political Reintegration is related to the re-establishment of order, justice, and the institutions of the state
(Kingma, 1997). It is argued that during conflict alternative and often parallel political institutions in the form
of militia or rebel groups are created. Such institutions may come to effectively replace the corresponding
institutions of the government and gain legitimacy and control over large areas of territory. Under such
arrangements, the power structures which created these alternative institutions will tend to demonstrate
preference towards their own members and supporters at the detriment of their opponents. 21
The process of political reintegration must ensure that during the establishment of post-conflict political
institutions the biases and prejudices inherent in these power structures do not lead to the marginalisation or
alienation of sections of society; but rather, promote the empowerment and political engagement of all. The
21
The potential explanatory power of evolutionary game theory on the continuing discourse on the drivers of social change will
be discussed in detail in the general introduction of the PhD thesis, see Camerer (2003), Gintis (2004) & Yamagashi (2011).
21
argument being that as long as political parties exist that represent the interests of potential combatants their
need to use violence to pursue those interests is removed: echoing Von Clausewitz reasoning that “war is a
continuation of politics by other means” (Englebert and Tull, 2008, Brañas-Garza et al., 2010).
22
References:
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23
Appendix II: Quantitative Conflict Measurement
Measuring Conflict
To date, due to the limited availability of micro-level data in conflict affected countries, attempts to measure
and quantify the affect of conflict have tended to use limited, easy to standardise, macro-level level measures
of a given conflict (such as absolute battle casualty figures) and run regressions against available livelihood
measurements. Significant examples of these studies include (Fearon and Laitin, 2003, Collier and Hoeffler,
2004, Ross, 2004, Ballentine and Nitzschke, 2005).
Such an approach makes it difficult to appreciate the consequences of conflict on individuals; to what degree
they are affected and what consequence this has on their behaviour and general welfare, and it is almost
impossible to measure the social and political transformations that occur in societies affected by conflict. As
Blattman & Miguel (2010) suggest “The leading question is not whether wars harm human capital stocks, but
rather in what ways, how much, for whom, and how persistently” – questions that cannot be answered with
aggregated macro-level data.
Over the last decade considerable attempts have been made to address this identified data weakness by
expanding the micro-empirical literature on the ‘legacy’ of conflict on development (Wood, 2008). These
attempts can be grouped into two general research agendas: the first utilises subsidiary analysis mechanisms to
add detail and nuance to existing large scale n-sample datasets and the second is concerned with the
generation of conflict-specific modules to be attached to future household surveys. The use of subsidiary
analysis mechanisms is itself divided by studies that aim to solely capture the temporal element and those more commonly - that attempt to incorporate temporal and spatial and aspects of the conflict legacy (Brück
et al., 2010).
Conflict Exposure over Time:
This first group of studies has attempted to a capture the legacy of conflict by combining information on the
duration of the conflict with birth dates taken from large population datasets. The most convincing results
from these type of studies is where a survey is available from before the outbreak of the conflict and one
afterwards and a ‘difference in differences’ method has been applied to examine the observed change in some
socio-economic indicator such as educational attainment (Alderman et al., 2006).
24
Even assuming that problems surrounding the conceptualisation of conflictare resolved22 and sufficient
information on birth dates and social wellbeing indicators are available, significant limitations to this method
remain. Firstly, findings are limited to age-related individual characteristics which are unlikely to persuasively
capture the entirety of the desired ‘conflict legacy’ effect. Secondly, the implementation of such methods do
not allow for the exclusion of other non-conflict related ‘shocks’ that may have played a part in any driving
observed changes, such a famine. Nor indeed do such methods ensure that the aggregation measurement
problems associated with macro-data sets are solved23.
Examples of such studies include de Walque (2004), Alderman (2006), Bundervoet et al, (2009), Leon (2010).
De Walque’s paper looking at the long-term legacy of the Khmer Rouge orchestrated genocide in Cambodia
relies purely on temporal comparisons, whilst the later works from Alderman through to Leon begin to
include an ever greater amount of spatial data in their analysis. Though the inclusion of spatial data appears to
offer the potential for greater understanding and analytical strength, the methods by which such a data is
gathered creates its own confounding difficulties.
Conflict exposure over location
It is clear that aggregated datasets on a national or regional level may miss essential dynamics of a given
conflict, and especially datasets that measure conflict severity through the number of direct battle deaths over
large geographic regions.24 In response, various methods have been used to try to address this clear weakness;
usually this entails introducing a dummy variable into an econometric model that is based on some level of
local administrative unit with the target country. Evidence of violent activity in this administrative unit is
then gathered and registered against the location variable to inform the wider data.
Despite the attractiveness of the potential to obtain spatially-sensitive conflict data, such a methodological
approach contains inherent weaknesses. As with temporal and macro-level datasets the problem of data
reliability due to the likelihood of significant measurement bias is unanswered. Indeed, due to the typical
reliance on journalist, NGO or government sources such information has a high degree of arbitrariness –
particularly when attempting to rank, order and classify the difference between reported conflict events. In
22
Although apparently obvious, it can be challenging to come to an agreed conceptualisation of conflict/civil war and
concurrently an agreed understanding of when a given conflict began and ended, see STEDMAN, S. J., ROTHCHILD, D. &
COUSENS, E. M. 2002. Ending Civil Wars: The implementation of peace agreements, Lynne Reiner Publishers..
23
In fact, it’s likely that they would be further compounded, see GROVES, R. M. (ed.) 2009. Survey Methodology, New Jersey:
John Wiley & Sons., UNSD 2002. Household Sample Surveys in Developing and Transition Countries, New York, United Nations .
24
Especially when we consider the fact that conflict intensity can be highly localised within a country, region or sub-region - as
in the example of the LRA insurgency in Northern Uganda.
25
addition, conflict event data does not systematically capture all such events across a region, rather it is likely
that conflict reporting will be highly linked to access and thus disproportionately record conflict events in
easy reach of major roads and/or highly populated areas whilst failing to equitably report similar events in
remote locations. Recent studies which have attempted to generate a conflict intensity index using such
methods including, (Gonzalez and Lopez, 2007, Akresh et al., 2011, Shemyakina, 2011). Perhaps the most
ambitious of the latest studies to attempt to capture detailed spatial conflict data is the work by Raleigh et al
(2010):2 which utilises precise satellite event positioning software (ArcGIS) to “Creat[e] a dataset that codes
the specific geographic location of armed conflict events will allow both focusing at small-scale behavior and
compiling information for larger geographical units that do not coincide with national boundaries.” The level
of detail contained in the Armed Conflict Location and Events Dataset (ACLED) is impressive and builds on
earlier spatial identification work by Cunningham et al (2005) and the data presented in the University of
Uppsala’s (UCDP/PRIO) Armed Conflict Dataset (Uppsala Universitet, 2011). And yet, despite the ever
increasing extent of available spatially and temporally available data the essential problems associated with its
collection method, verification and coding remain - challenging the data’s ability to produce powerful
empirical findings25.
Household Surveys with conflict experience information:
Household surveys used to generate generalised livelihoods datasets often include some questions which can
be used to extrapolate the degree of exposure to conflict a household has been exposed to.26 Examples of
such studies include Kondylis (2008) & (2010) agricultural and market outputs in the former Yugoslavia and
Verwimp and Van Bavel (2005) who uses a nationally representative stratified sample to explore correlations
between displacement or Rwandan refugee and fertility.
Whilst it is now recognised that development and poverty reduction efforts cannot be disassociated from the
implications of violent conflict (Justino and Verwimp, 2006, Manservisi and Mény, 2009, Justino, 2010,
WorldBank, 2011), it remains the case that specific conflict related data is not usually collected from national
scale household surveys. Data that does exist tends to come from individual researcher’s fieldwork where
their interest contains a conflict dimension. Bellows and Miguel, (2008) analyse the data taken from three
surveys conducted after the cessation of violence in Sierra Leone between 2005-7 and which asked specific
conflict related questions; for example ““Were any members of your household killed during the conflict?”,
“Were any members injured or maimed during the conflict?” and “Were any members, made refugees during
the war?”. Other examples of conflict specific studies include Deininger (2003) and Verpoorten (2009) who
25
On the principle that findings are only as reliable as the data from which they are produced.
26
Which is of course why these earlier macro-level conflict regressions and comparisons could be initiated.
26
gathered their own conflict specific survey data in Uganda and Rwanda. Verpoorten’s study relies on a smallscale survey at the household level and combines with qualitative verification to overcome problems relating
to its low non-random sample. Deninger uses a nationally representative survey and aggregates the household
answers at the community level in order to obtain a spatial measure of conflict intensity.
The inclusion of a conflict related ‘module’ to standard household surveys offers the potential to provide
detailed and comparable information on individuals from a range of diverse situations and geographic regions.
It is reasonable to assume that had such information been available to previous studies it would have been
included, at least as a complement, to the aggregated proxy data used within the earlier macro-level studies of
conflict exposure. Indeed, collection of conflict information in a standardised module would overcome many
of the shortcomings faced by the spatial and temporal conflict exposure studies mentioned above.
The problem of recall bias affecting participants’ responses would demand that such studies are implemented
soon after the cessation of violence in location. The logistical difficulties, safety and ethical concerns of
organising a large scale survey in such locations could present considerable challenges to its successful
completion27. Should such difficulties be overcome however, the potential to improve our understanding of
the effects of conflict exposure on a range of development questions is apparent.
27
Which would help to explain to some degree at least, why such studies remain rare.
27
References:
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28
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29
Appendix III: Homophilic Attraction
Homophily:
Unlike the process ‘social reintegration’, which lacks a strongly unified theoretical understanding, the drivers
of social tie formation are well documented.
It is one of the most empirically established principles that similar people associate with similar people or ‘like
associate with like’ (Coleman, 1957, Coleman, 1961, Blau, 1977, Billy and Udry, 1985, McPherson and SmithLovin, 1987, McPherson et al., 2001). There are many logical reasons for this; it may be that similar
individuals experience lower ‘transaction costs’ as result of the ability to communicate easily which, in turns
increases the ability to evaluate the intentions of others and even to predict their behaviour: (Festinger, 1957,
Werner and Parmelee, 1979). Trust and solidarity against ‘others’ should be easier to foster amongst those
who are similar: (Portes and Sensenbrenner, 1993, Buskens, 2002, Mollica et al., 2003). Social ties between
similar types may be longer lasting as lower ‘transaction costs’ afforded by homophilious relationships allows
for greater resistance from shocks and thus creates a positive cycle of reinforcement resulting in longer and
more durable associations (Felmlee et al., 1990).
As a consequence of this mutual attraction, individuals’ social networks become segregated along a variety of
core demographic, behavioural and moral variants. This self-attraction is known within sociology as the
theory of ‘Homophily’ and is so powerful within the field that its existence is almost taken as an accepted
truth within the wider social capital and social network literature (DiPrete and Gelman, 2011).
The early work by Lazarsfeld & Merton (1954) distinguished two types of homophily; Status homophily and
Value homophily. Status homophilic attributes include the major socio-demographic characteristics that tend
to stratify society in general; i.e. age, gender, race and ethnicity as well as acquired characteristics such as
religion, education and occupation. Value homophilic attributes reflect the internal differences that are
thought to shape our attitudes towards future behaviour: our attitudes, abilities, beliefs, and aspirations.
There exists an extensive experimental psychological literature on Value homophily that argues that
individuals with a similar ‘world outlook’ will be attracted towards each other; see Huston and Levinger
(1978)28.
The most significant State and Value homophilic attributes are described below:
28
There remains some debate over the influence of the interactive dimension of state and value attributes over time without
going so far as to challenge the overriding principal of mutual attraction.
30
Race and Ethnicity:
Much of the early work on homophily in society took place in the United States from the 1950s onwards.
The United States is recognised to be a significantly segregated society and it is therefore unsurprising that the
resulting sociological research conducted there places significant emphasis on the Stative attribute of Race
and Ethnicity in the formation of social ties (Pettigrew, 1969, Lincoln and Miller, 1979, Marsden and Hurlbert,
1987, Marsden, 1988, South and Felson, 1990, Farley and Frey, 1994, Kalmijn, 1998, Carr and Kutty, 2008)29.
Age:
After the Stative variable of Race and Ethnicity, Age is usually considered to be the most significant
dimension. Age homophily is highly dependent on the framing of the study in which it is explored. For
example, when considering emergency insurance networks or kin-relationships the age dimension of
individuals is less significant. In contrast, studies of close friendships identify age homophily as the
dimension that can be more significant than any other (Marsden, 1988). Age homophily contains a significant
baseline component due to the likely effect of age segregation occurring during childhood and adolescence.
(Verbrugge, 1977, Feld, 1984, Marsden and Hurlbert, 1987, Shrum et al., 1988, Suitor and Keeton, 1997,
LeVay, 2006, Kossinets and Watts, 2009)
Gender:
Gender homophily is strongest in studies of friendships but remains of consequence in studies of social
interactions, economic behaviour and trust and cooperation. The strength of the gender homophilic effect is
strongly associated to the prevailing social norms that dictate the gender roles in a given society. There exist
significant literatures which question the development of gender identities in childhood and the perpetuation
of these identities throughout adult life. Social norms translates into network composition and this has been
found to be particularly true studies of Western workplaces (or work roles) where minority genders tend to
form strong homophilious groups whilst having significantly higher hetrophilious network connections than
the majority gender (Hannan and Tuma, 1979, Hogan and Astone, 1986, Smith-Lovin and McPherson, 1993,
Chafetz et al., 2006, Finnstrom, 2008)
Religion:
The importance of religious homophily in a state is reflective of the strength of religious observance. Most
studies on religious homophily have been conducted in the highly observant USA where marriage, friendship
29
It is unlikely that Race and Ethnicity will be of significance in the context of Northern Uganda due to the ethnic homogeneity
of the intended research location – however, to ensure that this is the case, I will record Race and Ethnicity of participants.
31
and general associations was significantly affected by religious homophily when race and ethnicity were
controlled for (Hooper, 1976, Verbrugge, 1977, Wuthnow, 2003, Lauermann, 2009). As with age, religious
homophily varies in strength depending on which type of relationship is being observed. It is found that
religious homophily is strongest when considering forms of financial or emotional support and weaker in
relation to ties at work or recreation (Marx and Spray, 1972, Feld, 1984).
Education & Occupation:
Education and occupation has been shown to consistently effect the formation of social ties. Individuals who
work alongside each other have an increased frequency of interaction and thus opportunity to forms social
ties and at the same time increased opportunity to overcome the potential hetrophobia effect. Education
effects are tied to the baseline age segregation effects of institutional education as well as feeding into Value
homophilic characteristics relating to outlook and perspective. (Marsden and Hurlbert, 1987, Yamaguchi,
1990, Louch, 2000).
Social Class:
The suggestion that social class affects individual social tie formation may sound anachronistic in a western
‘meritocracy’ and yet the dimension of ‘social class’ on homophily is highlighted throughout the sociological
literature (Argyle, 1994). The difficultly of translating class status across cultural boundaries requires the
adoption of a sensible proxy for Social Class30.
The ‘Value’ Attributes of Politics, Attitudes, Abilities, Beliefs and Aspirations:
Beyond the State attributes mentioned above, Value attributes which reflect how an individual see themselves
within the wider world is known to play a part in social homophily. Value attributes appear to be most
significant when considering friendship relationships and is complemented by the literature on peer pressure
acting determining driver of individual behavior (Duncan et al., 1968). The attraction of individuals with
similar intelligence was one of the first areas of research explored in the development of the homophily
theory. Almack conducted a series of psychological experiments with children and now a positive clustercorrelation between friendship preferences and recorded IQ levels (Almack, 1922).
30
As Finnstrom FINNSTROM, S. 2008. Living with Bad Surroundings: War, History, and Everyday Moments in Northern Uganda
(The Cultures and Practice of Violence), Duke University Press. and others indicate, land is extremely important to conceptions
of wealth amongst the Acholi and therefore it seems a sensible (and a readily measureable) substitute to allow for the capture
of the homophilic effect of social class distinction. The study of and debate concerning ‘class’ is so vast and potentially
contradictory that problems linked to the simplification of this concept to land ownership alone are reduced on the principle
that it is at least as reasonable a definition as proposed alternatives.
32
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34