The Nature of the Dispute and the Effectiveness of International Mediation
Author(s): Jacob Bercovitch and Jeffrey Langley
Source: The Journal of Conflict Resolution , Dec., 1993, Vol. 37, No. 4 (Dec., 1993), pp.
670-691
Published by: Sage Publications, Inc.
Stable URL: https://www.jstor.org/stable/174545
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The Journal of Conflict Resolution
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The Nature of the Dispute and the
Effectiveness of International Mediation
JACOB BERCOVITCH
JEFFREY LANGLEY
University of Canterbury
The literature on mediation focuses largely on experimental laboratory studies or descrip
tions of single cases. This article goes beyond such approaches by analyzing systematically h
dispute characteristics affect mediation outcomes. A theoretical framework for studying m
ation behavior is developed and its central variables are evaluated against the mediation patte
of 97 international disputes in the postwar period. Using multivariate analysis and logline
methods, the results indicate that dispute features such as fatalities, complexity, nature of
issue, and duration of dispute are most predictive of mediation outcomes. The authors use th
results to specify a causal model that explains the data and to consider how best to evaluate
fit of alternative models of mediation to their data.
M ediation is widely regarded as the most common form of third-part
intervention in international disputes (Bercovitch 1984; Butterworth 197
Holsti 1987). It is a noncoercive and voluntary form of conflict manageme
that is particularly suited to the reality of international relations, where sta
and other actors guard their autonomy and independence quite jealousl
Although mediation is becoming increasingly popular in all social contex
there is still much about its performance and effectiveness that we do n
understand. Clearly, mediation cannot be effective or successful in each a
every dispute. Some disputes are amenable to mediation, but in others, t
parties may have to use different means. In this article, we assess how t
characteristics of a dispute affect the performance and effectiveness o
international mediation. We do so by developing a mediation-events data
AUTHORS' NOTE: This article was completed while the first author was the Lady Da
Professor in International Relations at the Hebrew University in Jerusalem. We are grateful to P
Camevale, Allison Houston, Herb Kelman, Dean Pruitt, Pat Regan, and J. David Singer for t
helpful comments.
JOURNAL OF CONFLICT RESOLUTION, Vol. 37 No. 4, December 1993 670-691
? 1993 Sage Publications, Inc.
670
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Bercovitch, Langley /INTERNATIONAL MEDIATION 671
and searching for a parsimonious, formal framework that can best interpret
the relationship among the various factors we highlight.
There is, to begin with, some disagreement on what precisely constitutes
international mediation. Some studies (e.g., Northedge and Donelan 1971)
define mediation rather narrowly. Narrow definitions of mediation are consistent with the attempt to capture the "essence" of mediation and to draw
boundaries between mediation, conciliation, facilitation, good offices, shuttle diplomacy, and fact-finding. This seems a futile exercise. When intervening in an international dispute, a mediator may exhibit all or any combination
of these behaviors. This is why we prefer to adopt a behavioral approach and
define mediation broadly as "a process of conflict management where
disputants seek the assistance of, or accept an offer of help from, an individ-
ual, group, state or organization to settle their conflict or resolve their
differences without resorting to physical force or invoking the authority of
the law" (Bercovitch, Anagnoson, and Wille 1991, 8). Admittedly, this is a
broad definition indeed, but we believe it to be a useful one because it draws
attention to the basic components of mediation; namely, disputing parties, a
mediator, and a specific conflict management context.
A better understanding of international mediation can only come about
from an approach that can analyze one or all of the salient variables and
components that make up a mediation relationship. Undoubtedly, two of the
most important components that make up this relationship are the nature and
characteristics of the dispute. Whatever is meant by an international dispute,
it is clear that some disputes can be mediated successfully, whereas others
frustrate the efforts of many diverse mediators.
We are mindful of the fact that we are focusing on a specific, albeit basic,
component of mediation. We are nonetheless convinced that it would be
interesting to examine, in a systematic fashion, the influence and impact that
different disputes can have on the performance and effectiveness of international mediation.
A SYSTEMATIC APPROACH
This article must be seen as part of our efforts to place internat
mediation within an empirical context and as a response to recent ca
the analysis of mediation to employ more sophisticated multivariate
niques (Bercovitch, Anagnoson, and Wille 1991). It makes use of an
lished but recently expanded dataset (see Bercovitch 1986, 1989; Berco
Anagnoson, and Wille 1991) to test the validity of earlier findi
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672 JOURNAL OF CONFLICT RESOLUTION
international mediation and to identify those dispute characteristics that
the greatest impact on mediation outcomes. We present conceptually
significant relationships and then use a loglinear model for multidimen
analysis to ascertain the empirical validity of these relationships.
Statistical analyses of mediation at the international level have been
(Bercovitch 1986, 1989; Bercovitch, Anagnoson, and Wille 1991; Frei
Holsti 1966; Levine 1971; Raymond and Kegley 1985). Of these, Raym
and Kegley (1985) are the only scholars who have attempted a multiva
analysis, but their findings relate only to the incidence of mediation r
than to its effectiveness or outcomes. Here we take the pivotal aspec
these works and place them within a conceptual framework that serves as
basis for our inquiry and analysis.
In searching for the antecedents of effective mediation, we note that m
of the existing, and largely anecdotal or experimental, literature on int
tional mediation places enormous emphasis on the mediator and his or
attributes as the key to achieving a successful outcome (e.g., Brett, Dri
and Shapiro 1986; Carnevale 1986; Young 1972). From this perspec
mediation may often be regarded as an art or a skill that one possesse
acquires. Successful mediation is thus presumed to be dependent on t
efforts of gifted and able mediators. It is as if other factors cannot, or do
impinge on a mediation relationship. The mediator is undoubtedly an im
tant influence, but, we suggest, only one influence among others.
We assume that mediation is an adaptive process; different mediator
different things in different situations, and that its particular form i
situation depends on who the parties are, what the dispute is all about
who the mediator is. Figure 1, which we refer to as the contingency fr
work of mediation, draws attention to four major clusters of indepen
variables that determine mediation outcomes (cf. Wall and Lynn 1993)
The contingency framework of mediation was developed by Bercovi
Anagnoson, and Wille (1991). The framework builds on comparable (bu
refined) models that can be found in Wall (1981) and Raymond and Ke
(1985). In our framework, the outcome of mediation is assumed
determined by both the context and the process of mediation. The contex
any mediation may itself be divided into three clusters of variables: (
nature of the dispute, (b) the nature of the parties, and (c) the nature o
mediator. The process dimension of the framework refers to actual me
strategies and their impact on the outcome.
The contingency framework is a useful analytical tool that can he
scholars to organize the literature on mediation and practitioners to ev
its policy implications. It also opens up before the researcher many ave
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Bercovitch, Langley/INTERNATIONAL MEDIATION 673
Figure 1: A Contingency Model of Mediation
of data collection and theory development. The particular avenue we will
pursue here concerns the nature of the dispute in its many facets.
DATA AND METHOD
The first objective of this study was to build up a database on internat
mediation. To this end, we have systematically scanned two major e
data sources, Keesings Archives and the New York Times, since 1945
information on international disputes. In assembling our list of disput
relied on the prior compilation of Small and Singer (1982), but lowere
threshold of fatalities to 100 only. Thus we define an international dispu
continuous clash between two or more states and involving at least 100 fat
Our search yielded 97 international disputes from 1945-1990. For ea
those disputes, we gathered information on opening and closing dates, is
presence of allies or others, fatalities, and other contextual variables. O
the most important variables we investigated concerned the means
manner of dispute termination. Procedures of termination were divide
violence, obsolescence, negotiation, mediation, and termination by reg
or international organizations. We found that our 97 disputes had experie
364 separate mediation attempts (the real number of mediation attem
much higher, but we could rely only on cases where mediation was rep
to have taken place). Some disputes experienced no mediation at all, ot
experienced one or two attempts, yet others experienced more than
different mediation attempts. Those 364 mediation cases constitute our
of analysis.
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674 JOURNAL OF CONFLICT RESOLUTION
TABLE 1
Mediation Outcomes
Outcome
N
Valid
%
Offered only 76
Unsuccessful
Cease
fire
207
30
71.9
10.4
Partial settlement 34 11.8
Full
settlement
Total
364
17
5.9
100.0
Having
identified
o
number
of
indicator
mediators'
status
in
t
strategy
in
a
and
the
used,
etc.)
to
series
of
earlier
Wille
1991;
Berc
conditions
unde
international
predictive
of
inquiry
characteristics.
disput
success
further
by
First then, let us look at the outcomes of all these mediation attempts (we
have omitted from our analysis cases where mediation was offered only; the
focus of our inquiry is on mediation offered, accepted, and undertaken).
Given the complexity and uncertainty that may characterize the term "outcome," we have decided to adopt a strictly behavioral approach (but see Frei
1976) and focus on the observed differences mediation has had on the parties'
conflict behavior within a four-week period. Thus we look at mediation
outcomes in terms of four possible dimensions: unsuccessful, cease fire,
partly successful, and fully successful. For purposes of our analysis, we group
together the last three dimensions into a "successful" category and contrast
it with the other cases in the "unsuccessful" category. As we can see from
Table 1, 71.9% of all mediation attempts were unsuccessful, that is, had no
discernible impact on the subsequent behavior of the parties, whereas 29.1%
of mediation cases did achieve some degree of success.
How is the outcome of mediation affected by the nature of the dispute?
Under what kinds of disputes is mediation more effective? We begin our
analysis by identifying significant dispute variables and suggesting their
possible impact on mediation outcomes.
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lo
Bercovitch, Langley /INTERNATIONAL MEDIATION 675
THE NATURE AND CHARACTERISTICS OF THE DISPUTE
It seems a truism to suggest that the nature of a dispute will
significant impact on the success or failure of a mediation attempt
and Pruitt (1989), in their excellent review of mediation research,
that unfavorable dispute characteristics "are likely to defeat even
adroit mediators" (p. 405). Similarly, Ott (1972) argues that "the su
failure of mediation is largely determined by the nature of the dispu
the characteristics and tactics of the mediator marginal at best" (p
It would be useful to go beyond such general statements and d
aspects of a dispute, code these systematically, and analyze their i
the success and failure of mediation. This is what we propose to d
section. We begin by reviewing three general aspects pertaining to th
of the dispute that are generally thought to affect its course and
These are (a) the intensity of the dispute, (b) the duration of the dispu
time of intervention, and (c) the issues at the heart of the dispute.
INTENSITY
When discussing the impact of dispute intensity on the outcome
international mediation, we are immediately confronted with two funda
tal difficulties: definition and operationalization. Although intensity
garded by everyone as an important dispute characteristic, there is a l
clarity as to what precisely intensity signifies.
Kressel and Pruitt (1989) conclude that high-intensity disputes ar
likely to experience successful mediation. But, under the rubric of inten
they include such diverse factors as the "severity of prior conflict," the
of hostility," "levels of anger," and "intensity of feeling," as well a
strength of "negative perceptions." They do not suggest how these ca
defined, let alone operationalized. In their discussion of public-sector
mediation, Kochan and Jick (1978) argue that "the intensity of the im
will be negatively related to the effectiveness of the mediation pro
(p. 213). But what they mean by "intensity" is not made explicit. Thi
of definitional precision leads to considerable difficulty in operationa
dispute intensity. To avoid this confusion, we will use one relatively
indicator to test the hypothesis that mediation is less likely to succeed in
intensity disputes.
The most obvious and accessible measure of dispute intensity i
number of fatalities in a dispute.1 We can logically expect a high le
1. Alternative measures of intensity, such as the overall duration of a dispute and th
of fatalities per month, were also tested but proved to be unreliable indicators.
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676 JOURNAL OF CONFLICT RESOLUTION
intensity to be reflected in the number of fatalities incurred by both s
Therefore, we postulate that high-fatality disputes will be less amenab
mediation. We will examine this relationship below.
DURATION OF THE DISPUTE AT THE TIME OF INTERVENTION
A number of studies speak of a crucial moment in the life cycle of a di
at which mediation will be most likely to succeed. Northedge and Don
(1971), for example, note that "the position is more favorable when th
exists a concatenation of circumstances which are already in operatio
tending toward an improvement of the situation" (p. 308). Zartman (1
has suggested that a combination of "plateaus," "precipices," "deadloc
and "deadlines" will produce moments of "ripeness" when the parties
highly motivated to settle their disputes. The assumption here is that i
waxing and waning of the complex social forces that make up an internat
dispute, there are moments during which both parties will welcome m
tion more openly. The exact nature of these moments is a matter of co
erable speculation.
Some theorists, such as Claude (1971) and Edmead (1971), have
gested that mediation should be attempted early in the dispute, befo
positions become fixed, attitudes harden, and an escalating cycle bec
entrenched. Others, such as Ott (1972) and Pruitt (1981), suggest
mediation will be more successful later, when conflict costs have be
intolerable and both parties realize that they may lose too much by conti
their dispute. We will examine below how the likelihood of succe
mediation relates to the temporal dimension of a dispute.
ISSUES
It would seem logical that the issues at the heart of the dispute will
quite influential in determining the outcome of mediation. This influence
be divided into two areas: (a) the substantive nature of the issues at st
and (b) their number and complexity. There is general agreement in
literature that particular sorts of issues will lend themselves to mediation
others will not. But there is disagreement as to exactly which issues ar
most amenable to mediation.
Ott (1972) has argued that mediation will be more successful in
absence of vital national security interests, and he draws attention to
particular difficulties faced when the question of territorial control
involved (p. 616). Lall (1966) supports this view, noting that "when terr
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Bercovitch, Langley / INTERNATIONAL MEDIATION 677
is at stake the party in possession tends to resist third party involvement"
(p. 100).
On the other hand, Northedge and Donelan (1971) highlight matters of
national "honor" as being particularly problematic. Bercovitch (1984) and
Hiltrop (1989) lend weight to this argument. In studies of labor mediation,
they found that tangible issues, such as pay and employment conditions, were
more amenable to mediation than disputes over intangible "matters of
principle," such as union recognition. Kressel and Pruitt (1989) also conclude
that "matters of principle" will defy mediation.
To make sense of this somewhat confused picture, we coded the issues in
dispute into "territory," "ideology," "security," "independence," "resources,"
and "other."2 The coding allowed for each dispute to have a primary,
secondary, and peripheral issue. Here we will focus mostly on the primary
issue in dispute.
It is also possible to distinguish between tangible and intangible issues in
dispute (Aubert 1963). Tangible issues pertain to concrete elements that can
be measured in some way (e.g., money, territory, etc.). Intangible issues relate
to parties' perceptions of needs or concerns with image, legitimacy, and
presentation. Intangible issues usually reflect matters of beliefs and principles. As such they may be more difficult to discuss or mediate. Zubek et al.
(1992) find strong evidence of an association between intangible issues and
prolonged hostile behavior in community mediation. Does the same relationship hold for international disputes? Or are issues important only when
combined with other variables (Vasquez 1983)?
We turn now to the second aspect of the issues in dispute-complexity.
Broadly speaking, the greater the complexity of the issues in dispute, the less
likely that mediation will be successful. In his study on the process of
mediation, Moore (1986) repeatedly draws attention to the influence that
"the number and complexity of the issues involved" (p. 172) have on the
outcome of mediation. This view is supported by several studies of mediator
behavior (e.g., Bercovitch 1984; Fogg 1985; Kolb 1983), which suggest an
inverse relationship between dispute complexity and effective mediation.
Alternately, it may be just as plausible to hypothesize, as Lax and Sebenius
(1986) or Raiffa (1982) do, that greater complexity creates greater opportu-
nities for trade-offs, sequencing, and packaging, thus enhancing the
chances of successful mediation. This relationship, too, should be examined
empirically.
2. No disputes were coded as having resources as the primary issue, and it is difficult to say
anything meaningful about "other," so both of these categories do not appear in the cross-tabulation of issue and outcome.
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678 JOURNAL OF CONFLICTRESOLUTION
ANALYZING RELATIONSHIPS: A MULTIVARIATE APPROACH
QUALITATIVE DATA AND MULTIVARIATE ANALYSIS
Our discussion thus far identified a number of factors or variables wit
significant impact on the success or failure of mediation. Traditionally
impact is assessed using various bivariate models where the relations
between each variable and mediation effectiveness is examined one at a ti
We want to examine all these variables simultaneously, to examin
interactions among them, and to assess their direct and indirect impa
mediation effectiveness. To do so, we must employ a more sophisticated m
of analysis that enables the simultaneous consideration of all the variable
The dependent variable in this analysis, the success or failure
mediation attempt, is inherently qualitative. Therefore, we must emp
multivariate method that is appropriate for data of this type. The analys
qualitative data has traditionally been limited to the use of two-dimen
contingency tables. But the development of log-linear techniques in th
twenty years means that this limitation no longer applies.
Log-linear methodology enables the researcher to examine multidimens
contingency tables containing qualitative (or categorical) data. Unfortunat
this technique has hardly been used in the field of political science. T
to developments built on the pioneering work of Goodman (1970, 19
1973), log-linear methodology has attained a much higher profile in
chology, sociology, and psychometrics precisely because of the advant
it offers in both theory and application over traditional multivariate techniq
3. Traditional multivariate techniques like analysis of variance (ANOVA) and m
regression (MR) are designed and are strictly appropriate only for continuous or interv
data. We reject the all too common practice of arbitrarily redefining qualitative variab
continuous, and the resulting "measurement error, bias, and the loss of a significant am
information" (King 1989, 4; see also King 1986). Log-linear techniques are in many
analogous to ANOVA, but because they are specifically designed to deal with qualita
categorical) data, they produce models that are more powerful and results that are more
in terms of both statistical theory and the substantive hypotheses under investigation.
This article employs general log-linear analysis to explore the goodness of fit of a nu
of specific models to the data observed in our study. We also use logit models, a special t
log-linear analysis, when our analysis is asymmetrical (i.e., when one variable has
identified as the response, or dependent, variable). Both general log-linear models and
models are based on maximum likelihood (ML) estimation techniques rather than least-
procedures. For a discussion of the advantages of ML estimation and the potential of lik
models of inference in political science research, see King (1989).
Kennedy (1983, 229-34) has demonstrated that compared to ANOVA, MR or can
analysis of variance (CVA) logit models tend to fit observed data better, can be more pow
and are easier to interpret. A further advantage is that a number of useful follow-up proce
are incorporated in log-linear analysis. For example, the X parameter estimates of the ef
each interactive term within a model can be individually tested for statistical significan
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Bercovitch, Langley/INTERNATIONAL MEDIATION 679
We use log-linear methods here for a number of reasons. First, the analysis
remains qualitative and does not attribute meaning to arbitrarily assigned
numerical values. Concepts in our study such as success and failure or the
tangibility and intangibility of issues do not lend themselves to traditional
multivariate techniques such as ANOVA and multiple regression, which rely
on the assumption of continuous (or interval) levels of data measurement.
Second, the strength and utility of the results and log-linear's model-building
and hypothesis-testing orientation have considerable intuitive appeal. And
finally, we employ this technique to demonstrate its potential in the field of
mediation research.
LOG-LINEAR METHODOLOGY
The analysis presented here follows the methodology outlined by Ken
(1983) in his excellent introductory text on log-linear analysis for beh
research. It is also influenced by Agresti (1990), Christensen (1990),
(1981), Haberman (1978a, 1978b), Knoke and Burke (1980), andMaras
and Busk (1987). A brief, nontechnical explanation of the method w
given here.
In the usual two-dimensional contingency tables, the objective is to
determine if one or both variables have an effect on the distribution of values
in the other, or to establish that there is no such effect at all. Similarly, in
multidimensional contingency table analysis, the main objective is to identify
which variables are independent, which variables influence other variables,
and, most importantly, which pairs or groups of variables have an interactive
effect on others.
Once we have established which variables will make up our multidimen-
sional table, we propose to identify the interactive effects that have the
strongest influence on the data (i.e., which relationships between variables
are responsible for the observed distribution of the data within the cells of
our table). More specifically, in this case, we want to know which relationships and interactions will influence whether a mediation case will fall into
the success or failure category.
We begin by combining those effects suggested in the literature as
influential and positing a causal model. This model is then expressed in
log-linear terms and tested for its ability to reproduce the observed cell
frequencies (goodness-of-fit). Should the fit of the model be inadequate, we
can then test the strength of individual, interactive effects in the model and
suggest possible revisions to our multivariate hypothesis. In selecting the
final model, we strive for (a) parsimony (a model that contains the fewest
possible interactive effects for ease of interpretation) and (b) acceptable
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680 JOURNAL OF CONFLICT RESOLUTION
goodness-of-fit (a model that produces expected cell frequencies that fit
observed data reasonably well).
Three measures can be used to test the fit of general models and the imp
of individual effects. First, the likelihood ratio chi-square statistic (L2) is u
to test for the overall agreement between the expected cell frequenci
generated by a model and the actual cell frequencies observed in the
(Kennedy 1983, 89).4 A good-fitting model will have a relatively smal
and is generally said to be adequate when the p value is greater than
(Gilbert 1981, 68; Agresti 1990, 176).5 An ideal model would be one th
surpassed this significance threshold and in which L2 was equal to the degr
of freedom (Kennedy 1983, 222).
Second, the L2 statistic, because of its additive properties, can be divi
into component parts. As a result, the strength of an individual, interac
effect can be found by calculating its component L2. The component L2 of
effect is the difference in general goodness-of-fit that results from adding
effect to a particular model.6 An important effect that improves consider
the fit of the model will have a large component L2.
Finally, the parameter estimates (X) for each effect can be analyzed
relative size and statistical significance. Naturally, an important effect
have a relatively large parameter estimate.
4. In some of the literature on log-linear methods, L2 is sometimes written as G2. For a
explanation of the calculation of this statistic and its relationship to the more common Pe
X2 statistic, see Agresti (1990), Kennedy (1983), and Marascuilo and Busk (1987).
5. Most researchers will be familiar with the Pearson chi-square statistic as a tes
independence in two-dimensional contingency table analysis, where a significant X (p < .
indicates disagreement between the data and the null hypothesis. However, when test
general log-linear model, the opposite is the case. A nonsignificant L2 (p > .05) is the des
result because this indicates agreement between the given model and the data. For ea
understanding, we will say that a p value greater than .05 is "significant." This should n
confused with the component L2, which can be interpreted as one would normally interpret t
conventional 2 .
6. Determining the impact of each component term in a model is sometimes referred
partitioning the chi-square. To calculate the component L2 of each effect, we assess the ch
in the goodness-of-fit given by comparing a model containing the term in question wit
identical model not containing that term. To ensure that we are testing only the contribution
that specific term, we must "control" for all other possible influences; therefore, the term b
tested should be removed (or added) to the model containing all terms of the same order
three-way interaction term should be tested for its relative contribution to the full three
interaction model. For example, the component L(ICF) is found by comparing the full thre
interaction model with a model that is the same except for the absence of ICF:
L2(ICF) = L2(F,IF,DF,CF,IDF,CDF)
- L (F,IF,DF,CF,IDF,CDF,ICF)
= 7.29
-.92
= 6.37
Thus the component L2 for ICF, as seen in Table 3, is 6.37.
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Bercovitch, Langley / INTERNATIONAL MEDIATION 681
MODEL BUILDING AND TESTING
The variables that are included in our analysis have been collapse
the dichotomies shown in Table 2. The notation given is used as a k
shorthand when discussing log-linear models. For example, (F) is the
effect7 of fatalities, (FO) is a two-way interaction between fataliti
outcome, and (IFO) is a three-way interaction between issues, fatalit
outcome.
In our review of the literature, we have identified a significant relationsh
between low complexity (C) and successful outcome (0), and between lo
fatalities (F) and successful outcome (O). So our first model includes th
interactive effects (CO) and (FO). Furthermore, we posit links between
tangible issues and low complexity (IC); tangible issues and low fataliti
(IF); low complexity and early intervention (CD); low complexity and lo
fatalities (CF); and early intervention and low fatalities (FD). Using thi
notation, our initial model (Ml) of the dynamics of the dispute variables
their impact on mediation outcome is written as follows:8
M1 = (IC,IF,CD,CF,FD,CO,FO).
To help the reader interpret this somewhat unfamiliar notation model, M
is represented diagrammatically in Figure 2. The arrangement of the variab
in Figure 2 is important. Statistical analysis can establish only correlatio
not causality. Therefore, when hypothesizing models and interpreting resu
the decision about the direction and nature of causal relationships must
guided by theory.
If the interactive effects in model Ml are indeed influential, then the mo
will predict cell frequencies that fit the observed data closely. However,
log-linear test of the ability of this model to reproduce the cell frequen
observed in the data yields an inadequate fit: L2(M1) = 35.31, df= 19, p
.013.
To revise Ml, we must assess the importance of each individual effect
the model and attempt to identify other important effects that are missing
the Ml model, we hypothesized a number of specific interactive effects,
7. Main effects are the independent, noninteractive effect of each variable (the independ
marginal distribution).
8. The main effects of all variables are included in Ml but are not given separately in
model notation. It is assumed that each variable continues to have an independent effect to som
degree; therefore, all main effects are incorporated in general models. Our interest is
determining which interactions are important above and beyond these independent effec
therefore, only interactive effects will be given in the notation. The exception to this is the n
model (in this case, the model of mutual independence, M0, in Table 4), which includes on
main effects.
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682 JOURNAL OF CONFLICT RESOLUTION
TABLE 2
Variables and Categories for Log-Linear Analysis
Parameter Notation Categories
Outcome
(O)
(a)
Success
(b) Failure
Fatalitiesa (F) (a) 100-1000
(b) 1000+
Issues
(I)
(a)
Tangible
(b) Intangible
Complexity (C) (a) One or two issues
(b) Three or more issues
Duration at time of interventiona (D) (a) 0 to 12 months
(b) 13 months or more
a. Fatalities and duration are based on continuous data, but were in fact coded as categoric
variables.
Figure 2: Model M1
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in doing so, we also hypothesized several null effects. For example, because
little is known about the more complex interactions in international mediation, we hypothesized all three-way and four-way effects to be null. Because
the fit of our initial model has proven to be inadequate, sound methodology
compels us to test the significance of both hypothesized and null-hypothesized
effects.
To accurately test the impact of each effect, we must control for all other
influences and deal with the model in a systematic fashion. Our initial model,
M1, as shown in Figure 2, is arranged so that some variables temporally precede
others. As we move from left to right in the model, we find variables that are
at first responses, but then become explanatory influences on subsequent
variables. To test the individual contribution of each effect, we move through
the model in a stepwise fashion, testing the various explanation-response
relationships in turn.9 The results of this exercise can be seen in Table 3.10
Table 3 clearly shows how partitioning the L2 into its components offers
considerable insights into the relative strength of individual, interactive
effects. It is important to remember that effects that do not achieve signifi-
cance should not be completely discarded at this point; this process serves as
a guide only."
In this step-by-step, or rather effect-by-effect, analysis, we find support
for all the effects in our initial model Ml except for the effect of complexity
on duration (CD). But the CD effect does approach significance and still
deserves further consideration. Tests of effects hypothesized to be null have
revealed two significant, three-way interactions: the combined effect that the
nature of the issue and the complexity of the dispute have on the level of
fatalities (ICF); and the combined effect of complexity and the duration at
the time of intervention on outcome (CDO). In light of this information, it
would seem prudent to revise our initial model.
A number of contending models are shown in Table 4. The first model-
MO-is our null hypothesis. This is the model of mutual independence. It is
included merely for purposes of comparison. The very poor fit of this model
clearly demonstrates that the variables in the analysis are not independent of
each other. Our Ml model shows considerable improvement, but, as noted
earlier, the fit is not adequate.
9. This process is outlined in Kennedy (1983, 211-23).
10. Table 3 gives the component L2 for all hypothesized and null hypothesized effects when
fitted to full logit models of the same order within their respective subtables. In logit models,
the main effects of independent variables are not fitted, but the main effect of the dependent
variable is fitted in all cases.
11. Because the terms in Table 3 are fitted to full-order interactive models, their effects may
not be as pronounced as they may be when incorporated in more restricted models where fewer
terms, and therefore less data, are used to estimate model parameters.
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684 JOURNAL OF CONFLICT RESOLUTION
TABLE 3
Component L2 for All Hypothesized and Null-Hypothesized Effects
Component
Effect Component L df p <
1 .00b'c
(IC)
52.61
Effects fitted to (ICDD table (IF)
4.56
(DF)
(CF)
(ICF)
(IDF)
(CDF)
(ICDF)
10.17
1 .0b'c
Effects fitted to (I)a table
Effects fitted to (ICFD) table (ID)
(FD)
(CD)
(ICD)
(IFD)
(CFD)
(ICFD)
(IO)
Effects fitted to (ICDFO) table
(FO)
(CO)
(DO)
(DFO)
(CDO)
(IDO)
(ICO)
(IFO)
(CFO)
3.94
1 .05b'c
6.37
1 .02c
3.02
1
.23
1
.70
.92
1
.50
1
.30
1.21
.10
2.95
1 .01b
1 .10b
10.04
1.44
1
3.02
1
.30
.10
.17
1
.70
.92
1
.50
.06
1
.90
1 .01Ob,
10.58
1 .02 'c
5.83
.06
1
.90
1.90
1
.20
9.11
1 .01C
.05
1
.15
1
.70
1.20
1
.30
.26
1
.70
.90
All higher-order
interactions
combined
.61 5 99d
a. The underlined variable denotes the dependent
in the step-by-step analysis.
b. Effects hypothesized in model M1.
c. Statistically significant effects.
d. All higher-order interactions (four-way and f
model by L = .61, df= 5, p < .99, suggesting that
nonexistent.
As a result of our analysis of compon
model: M2. This model incorporates t
found to be influential. Also, a test of th
new model suggests that it be retained
12. When incorporated in model M2, the CD effe
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Bercovitch, Langley/INTERNATIONAL MEDIATION 685
TABLE 4
General Log-Linear Tests of Contending Models
Model
L2
df
p<
Mo (I, C, D, F, 0) 149.14 26 .000
M1 (IC, IF, CF, CD, DF, CO, FO) 35.31 19 .013
M2 (IC, IF, CF, CD, DF, CO, FO, ICF, CDO) 25.38 17 .087
M3 (IC, IF, CD, DF, CO, FO, ICF, CDO) 25.38 18 .115a
a. The comparable Pearson X2 statistic gives an even better fit of 2 = 21.23, df= 18,
show improved goodness-of-fit, and it surpasses our criteria for signif
The ability of this model to reproduce the observed data appears to be ad
A standard log-linear follow-up procedure, the examination of t
parameter estimates generated by M2, was conducted.13 The effect o
plexity on fatalities (CF) (which in Table 4 can be seen to be close t
criteria for exclusion) has a particularly small parameter estimate th
not reach significance: X(CF) = .006, Z = .05. In short, this effect i
influential and makes virtually no contribution to the fit of the M2 m
In model M3, we remove the questionable CF relationship and ob
no change in L2. We do observe, however, that the significance of th
improves and the overall fit of the model is improved by the increas
number of degrees of freedom.14 Thus, as a result of this simple pr
testing general models and examining individual component L2s and
eter estimates, we have found a model that satisfies our criteria of par
and predictive power.
Finally, we use another measure to test the ability of the model to e
the variance in the data across all the variables in the cluster. The measu
a log-linear R2 statistic analogous to R2 in multiple regression. Whe
calculated on the fit of model M3, we get R2 = .829.15 In other wor
model accounts for nearly 83% of the variance in this cluster of var
We will retain M3 as our model of the dynamics of the nature of the d
and the outcome of international mediation.
13. For a comprehensive discussion of the interpretation of log-linear X parameter estimates,
see Alba (1987). Here we compare only the relative size of Xs and perform standard Z tests of
significance.
14. As noted earlier, as the L and the degrees of freedom of the model converge, the fit of
the model can be said to improve (Kennedy 1983).
15. It should be noted that this measure is not directly equivalent to R in regression analysis.
In essence, it gives a measure of the variance explained beyond that which can be accounted for
in the null hypothesis. For a fuller description and discussion of this measure, see Christensen
(1990, 150); Haberman (1978a, 17), and Kennedy (1983, 228). This log-linear R2 is calculated
as follows:
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686 JOURNAL OF CONFLICT RESOLUTION
Model M3 is represented graphically in Figure 3. The coefficients on t
interactions are the X parameter estimates generated by the model for
effect. Parameter estimates are not multiplicative, as in traditional p
analysis, because our data, and hence our method, are qualitative and do
usually work in such equations. Thus we cannot multiply paths betwe
variables to estimate the size of indirect causal effects (see Knoke and Bu
1980,45). Lambdas are, however, excellent indicators of the relative stren
of interactive effects within the given model.
All coefficients in Figure 3 are positive, indicating a correlation betw
the first categories of the variables concerned [categories marked (a) in Tabl
Thus we find a very strong correlation between tangible issues and lo
complexity disputes. Clearly, disputes over tangible issues are usually sin
issue disputes and as such lend themselves to compromise solutions.
We also find a moderately strong correlation between tangible issues
low fatalities. Independent of this, there is a further combination of
complexity and tangible issue that correlates with low fatalities. Low c
plexity also ties in with early intervention, which in turn is quite stron
correlated with low fatalities. This is expressed as a two-way effect, for
equally plausible that early intervention will keep fatalities low and t
fatalities will tend to be low early in the dispute, which may act as an impe
to intervene.
Fatalities is one of the three direct influences on outcome that has b
identified. There is a clear, positive relationship between low fatalities
successful mediation outcomes. Other direct influences on outcome are
interaction of low complexity and brief dispute duration, which correl
2 )L2(M0) - L2(Mi)
L2(M0)
Where L2(Mo) is the fit of the null-hypothesized model and L2(Mi) is the fit of the model of
interest. Because the null hypothesis represents the total variability of the data (i.e., between the
saturated model and the smallest possible interesting model, or null hypothesis), R gives us a
measure of the amount of variation in the data that is explained by the model of interest. In this
case, the null hypothesis is the mutual independence model.
R2 for M3 is given below:
R2( L2(M0)-L (M3)
R (M0)
149.14- 25.38
149.14
= 829
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Bercovitch, Langley/INTERNATIONAL MEDIATION 687
Figure 3: The Nature of the Dispute and Mediation Outcome: A Causal Model
NOTE: Coefficients given are lambda parameter estimates. Z-value tests of significance are
given in parentheses. Significant at the 95% confidence level.
with success and, independent of this, the positive impact of low complexity
on successful outcome.
Model M3 has shown its ability to explain much of the variance in the
data across the cluster as a whole, but what of its ability to explain outcomes?
When we apply the log-linear R2 equation to an analysis that explicitly posits
outcome (O) as the dependent variable in combination with the effect of
fatalities on outcome (FO), the effect of complexity on outcome (CO), and
the effect of the interaction of complexity and duration on outcome (CDO),
we get R2 = .656.16 Model M3 accounts for around 65% of the variance in
outcome across the cluster of dispute variables.
16. The L2s for this equation were found by fitting the logit models given below to the ICDFO
table. In this case, the null hypothesis is the model O, where outcome is independent and the
model of interest includes those effects found to have an impact on outcome (O, FO, CO, CDO).
Thus we have a measure of the amount of variance in outcome explained over and above that
of the null hypothesis:
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688 JOURNAL OF CONFLICTRESOLUTION
The nature of the dispute is clearly a major determinant of mediat
outcomes. A good deal of the variance in outcome is yet to be explained.
is not surprising when we remember that, in this article, we considered o
one of the clusters of variables that have been identified in our concep
framework as affecting mediation outcome.
CONCLUSIONS
For too long we have assumed that mediation can alter the key el
of a dispute without really studying how these key elements can
mediation. Mediators in the personal, communal, or international
operate within a specific context, a context that presents constraint
as opportunities for a mediator. There is a reciprocal relationship b
the context of mediation and its style and effectiveness. Each cont
require its own "do's" and "don'ts." In other words, the contingent
generic-application of mediation may be the key to its success.
Here we have analyzed how the nature of the dispute, as one of t
crucial contextual determinants, affects mediation outcomes. We h
aggregated the nature of the dispute into concrete, empirical dimen
issues, relationship, and interactions, and gathered data on issues, part
conflict management behavior in 97 international disputes. In this s
use our initial set of 364 mediation cases to determine which
characteristics have an effect on mediation and how they affect it.
We use log-linear analysis to examine the impact of significant v
on mediation outcomes and the interactive effects among these v
Our findings indicate the direct impact that fatalities and dispute com
have on mediation outcomes and the interactive effects of fatalit
dispute complexity with issues and timing of intervention. High f
encourage further hostility and contentious behavior, and these dimin
likelihood of mediation effectiveness (just as they diminish the ch
an agreement in negotiations) (see Pruitt 1981). Dispute complexity
in any event is associated with lengthy, protracted conflicts and
R(O,FO,CO,CDO) L2() - L(O,FO,CO,CDO)
L2(0)
42.79- 14.68
42.79
= .656
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Bercovitch, Langley / INTERNATIONAL MEDIATION 689
fatalities, also appears to be incompatible with successful mediation. Our
results suggest that dispute duration also has a strong inverse relationship
with successful mediation, but only when it combines with fatalities and
complexity.
These results are unsurprising in that they indicate that intensely hostile
disputes, with many issues at stake and high fatalities, are not particularly
amenable to mediation any more than they are to negotiation, adjudication,
or even the intervention of an international organization. They do, however,
offer a clear set of policy implications from the mediator's perspective.
Mediators can enhance the likelihood of an agreement by reducing or
repackaging the number of issues in dispute; focusing on tangible rather than
intangible issues; initiating mediation once the disputants have had some
time to sort out their conflict, but long before the level of hostility and
fatalities get too high; and pursuing mediation strategies that can be adapted
to the demands of different disputes.
The results may not reveal anything startling, but it is better to have such
information confirmed than to speculate about it. The kind of work we have
described above draws attention to prior contextual conditions and their
impact on conflict management in general and mediation in particular. It is
futile to describe mediation or mediation behavior as if it were unrelated to
these conditions. Just as mediation purports to change, affect, or influence
these prior conditions, so too can these conditions change or affect mediation.
There is a reciprocal relationship of influence in all aspects of conflict
management.
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