Catherine H. Tinsley
Imagine that the Central Intelligence Agency (CIA) suspects a Pakistani national living in Canada is planning a terrorist attack against the United States. The CIA has been working with Canadian authorities to track the man’s movements and analyze his future intentions. Border patrol has been alerted because the suspect appears to be part of a Canadian-based terrorist cell that may soon try to enter the United States. The National Security Agency (NSA) has been contacted to monitor the suspect’s telecommunications. Last week, the suspect phoned a U.S. citizen and resident, which triggered the involvement of the Federal Bureau of Investigation (FBI).
As this scenario illustrates, current threats to U.S. security can be global, can come from varied nonstate actors (including isolated individuals), and can require extensive coordination across intelligence community (IC) agencies. Indeed, the IC has recognized a need to integrate information and analysis, as captured in various agencies’ strategic plans. The Director of National Intelligence writes that “information sharing is a top priority” and that we must move from a mentality of “need to know” to a mentality of “responsibility to provide” (Office of the Director of National Intelligence, 2008). The Defense Intelligence Agency (DIA) Strategic Plan lists “support[ing] unification of effort across the IC to promote horizontal integration fostering access to data and sharing information” as one of its five major strategic actions (Defense Intelligence Agency, 2007). This coordination goes beyond simply the need to share information with each other. Instead, it requires analysts to understand and appreciate the experience and knowledge that each different agency brings to the table. This deeper
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9
Social Categorization and
Intergroup Dynamics
Catherine H. Tinsley
Imagine that the Central Intelligence Agency (CIA) suspects a Pakistani
national living in Canada is planning a terrorist attack against the United
States. The CIA has been working with Canadian authorities to track the
man’s movements and analyze his future intentions. Border patrol has been
alerted because the suspect appears to be part of a Canadian-based terror-
ist cell that may soon try to enter the United States. The National Security
Agency (NSA) has been contacted to monitor the suspect’s telecommuni-
cations. Last week, the suspect phoned a U.S. citizen and resident, which
triggered the involvement of the Federal Bureau of Investigation (FBI).
As this scenario illustrates, current threats to U.S. security can be
global, can come from varied nonstate actors (including isolated individu-
als), and can require extensive coordination across intelligence community
(IC) agencies. Indeed, the IC has recognized a need to integrate informa-
tion and analysis, as captured in various agencies’ strategic plans. The
Director of National Intelligence writes that “information sharing is a top
priority” and that we must move from a mentality of “need to know” to a
mentality of “responsibility to provide” (Office of the Director of National
Intelligence, 2008). The Defense Intelligence Agency (DIA) Strategic Plan
lists “support[ing] unification of effort across the IC to promote horizontal
integration fostering access to data and sharing information” as one of its
five major strategic actions (Defense Intelligence Agency, 2007). This coor-
dination goes beyond simply the need to share information with each other.
Instead, it requires analysts to understand and appreciate the experience
and knowledge that each different agency brings to the table. This deeper
197
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198 INTELLIGENCE ANALYSIS: FOUNDATIONS
understanding will help attenuate communication problems (Fischhoff, this
volume, Chapter 10), such as agents talking past each other or dismissing
each other’s analysis.
Unfortunately, cross-agency collaboration can be thwarted by the famil-
iar pathologies found in all intergroup endeavors. These include misaligned
organizational incentives, ossified bureaucratic policies, and conflicting
political pressures. For example, agencies within the IC are “mission spe-
cific” (Sims, 2005), meaning they serve different customers who may be
asking different analytic questions about the same target or event. Each
agency in the IC naturally has “its own terminology, routines, and expec-
tations about what people can ask for” (Simon, 2005, p. 150). Moreover,
interagency “turf wars,” which appear to arise from historical inertia and
budgetary conflicts (Sims and Gerber, 2005), provide inherent challenges
to interagency collaboration.
Discussing any particular bureaucratic, political, and budgetary con-
flicts is beyond the scope of this chapter, which instead focuses on how
the pluralistic structure of the IC can engender cognitive and motivational
biases that hinder effective cross-agency collaboration. Special attention is
paid to the agency grouping and how social categorization processes can
influence individual behavior. Social categorization is the process by which
we make judgments about individuals (and who they are in relation to our-
selves) based on their group membership. When we encounter other people,
we tend to encode not only individual information about that person, but
also social information—in particular, whether he or she is a member of
one of our “in-groups”—the groups to which we belong—or is an “out-
group” member, or outsider. In the context of the IC, where a salient group
boundary is agency (or subagency) affiliation, social categorization suggests
that analysts register whether other analysts are members of the same or
different IC agency.1 This encoding can produce mental roadblocks to
coordination by eliciting well-documented intergroup dynamics, including
differentiation, ethnocentrism, and integration neglect (explained below).
These roadblocks are not unique to the IC, but rather are fundamental
1 This agency grouping does not mean that other social groups are irrelevant. Indeed, within
some agencies there are large distinctions between analysts and collectors (e.g., the CIA).
Groups are people’s subjective representations of others vis-à-vis the self. These groups may
exist because people interact regularly and share a common fate (Campbell, 1958), such as
with workgroups, or groups may be large collectives where individuals are connected by vir-
tue of common symbolic attachments (Geertz, 1973). The motivational and cognitive biases
discussed in this chapter would pertain to any social group distinction that is relevant for the
actors involved. For simplicity of presentation, however, I choose the agency level as the focal
social group because this follows both the formal organizational structure and other work
describing agency affiliation as a dominant social category in the IC (see Sims and Gerber,
2005, or Fingar, this volume, Chapter 1).
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
aspects of organizational life, unless deliberate efforts are made to over-
come them. More relevant to the IC is how these dynamics play out and
how they might be managed.
Before describing the usual pathologies that can arise from an inter-
group environment, I briefly detail research in organizational behavior to
explain why these pluralistic structures evolve. In most organizations, and
particularly for the mission-diverse IC, social groups function to simplify
tasks and create high-quality (i.e., well-grounded and solidly analytic) prod-
ucts. The idea is not to restructure the IC to rid it of multiple social groups
(which is likely to be impossible anyway), but rather to attenuate negative
externalities that this intergroup environment can produce.
INTERgROUP DYNAMICS AS A FACT
OF ORgANIZATIONAL LIFE
Social groups exist in all organizations and often create cognitive and
motivational roadblocks to cooperation and collaboration. Despite their
pernicious consequences, organizations cannot eradicate groups. For orga-
nizations, groups are necessary for efficient coordinated action. For individ-
ual employees, groups are necessary for constructing identity and making
sense of their workplace.
The Organization’s Need to Form groups
All organizations differentiate—meaning they split their employees into
different groups (Lawrence and Lorsch, 1967). Differentiation allows for
specialization, production efficiency, and accountability. Imagine if every
employee was responsible for the same job tasks—no one would master
any special skills, and failure to accomplish job tasks would rest with
everyone and hence with no one. The IC can be modeled as a decentral-
ized conglomerate organization (Chandler, 1962). In one organizational
chart2 the Office of the Director of National Intelligence is at the top. One
level below it are the program agencies (CIA, DIA, FBI, NSA, etc.). On the
next level are the “departmental agencies” or those that primarily report
directly to a Cabinet member (Drug Enforcement Administration, Depart-
ment of Homeland Security, Department of State’s Bureau of Intelligence
and Research (INR), Department of the Treasury, etc.). On the final level
are the “service agencies” (Army, Air Force, Navy, Marine Corps, and
Coast Guard Intelligence). Of course, the IC can be grouped in other ways
(e.g., on the basis of whether the agencies’ primary function is collection
2 Chart published in National Intelligence: A Consumer’s Guide to National Intelligence
(Office of the Director of National Intelligence, 2009, p. 9).
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200 INTELLIGENCE ANALYSIS: FOUNDATIONS
or analysis, or whether their primary concern is foreign intelligence or law
enforcement). Yet, alternative ways of grouping personnel does not threaten
the central thesis that the multiorganizational character of the IC creates
groups that differentiate themselves from one another and engender cultural
barriers to collaboration.
The important point is that the IC is structured, and the basic struc-
tural unit is the agency. In the IC, the first order differentiation of analysts
is based on agency affiliation. The structure allows each agency to produce
intelligence products tailored to the needs of its primary customer base. For
example, in April 2001, when a U.S. EP-3 surveillance aircraft collided in
mid-air with a Chinese fighter plane and the EP-3 landed on the Chinese
island of Hainan, different IC agencies produced intelligence assessments
that answered very different types of questions reflecting the interests and
responsibilities of their different customers. Thus, the INR, whose primary
customer is the Department of State, produced intelligence to answer ques-
tions such as: What are the diplomatic implications of the collision? What
signals has the Chinese government sent that might help to resolve the cri-
sis? What is the government telling its own people about the incident? The
DIA, whose primary customers are in the Department of Defense, addressed
different questions: Are the Chinese moving any military assets? Are there
any signs that units have increased readiness levels? What are Japanese
and South Korean media saying about the incident and U.S. forces based
in those countries?
The NSA and National Geospatial Agency (NGA) addressed more
technical questions about the types of equipment on board and what the
implications would be of some or all of it falling into the hands of the
Chinese government. The CIA, reflecting its broad customer base and
responsibilities, provided a second take on many of the questions posed and
answered by other agencies. These illustrations make clear that specializa-
tion is necessary, appropriate, and essential to address specific customer
concerns. Only by being close to customers can analysts know what they
require and produce truly useful intelligence products.
Throughout the differentiation process, organizations make trade-offs
about where and how much to differentiate, with the aim of maximiz-
ing goals such as: (1) resource efficiency, (2) time efficiency, (3) employee
accountability, (4) responsiveness to the environment, and (5) adaptability
over time (Nohria, 1991). For the IC, resource efficiency would be the abil-
ity to produce quality intelligence with economy of labor and capital; time
efficiency would be the ability to do so rapidly. Employee accountability
describes the ability to hold employees responsible for required activities.
Responsiveness to the environment means satisfying the requirements of
U.S. policy makers as well as the need to protect sources and methods.
Finally, adaptability refers to the ability to innovate to meet changing
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
security threats and policy decisions. To maximize this portfolio of issues,
the organization decides how much to differentiate and where to draw the
distinctions.
Naturally, this differentiation process creates groups (e.g., agencies)
that have their own unique intelligence priorities and routines. Although
agencies may share common rules for evaluating source reliability or expli-
cating underlying assumptions, the agencies develop different decision rules
on what topics to cover and different standard operating procedures on
which streams of data are the most reliable to use. For example, the INR
may rely more heavily on diplomatic and open-source information; the DIA
may rely more heavily on military channels; the CIA may focus primarily on
clandestine human intelligence collection; and the FBI may use other human
informants with information relevant to law enforcement. These decision
rules and procedures are likely to align with the agency’s mission, but they
will in some sense dictate how data are collected, fused, used or discarded,
interpreted, and presented. Thus it is not surprising that differentiated agen-
cies can produce intelligence that is not completely uniform, even if each
is a well-researched product reflecting solid evidence and analysis. Some
systemic tension is natural; the idea is to understand and manage it rather
than try to eliminate it.
Individuals’ Need to group
Differentiation benefits organizations through efficiency gains and
specialization. This specialization can also benefit individuals because it
encourages employees’ skill development. Yet skill specialization can also
make the employee more dependent on the organization because high-asset
specificity cuts both ways (Williamson, 2002). Do individuals benefit from
the presence of multiple social groups in their environment?
Some have argued that social categorization processes (constructing
social groups) is a natural human process. As social creatures, we tend to
carve up our social landscape into groups (see social categorization theory,
Deschamps and Doise, 1978; Vanbeselaere, 1991), in part to construct
our own identities (Tajfel, 1969; Tajfel and Turner, 1979). Generally, we
come to understand who we are by virtue of the groups to which we do
and do not belong (Smith and Berg, 1987). In fact, we tend to view other
people, first and foremost, as members of a particular social category (in-
group or out-group) (Brewer and Feinstein, 1999; Fiske et al., 1999). This
social categorization happens relatively effortlessly (Fiske, 1998) and is
often based on visually prominent and culturally relevant features, such
as age, race, and (here) agency affiliation (Brewer and Feinstein, 1999;
Fiske, 1998). Of course, people have multiple in-group identities (Stryker
and Statham, 1985; Tajfel, 1978), but when these categories compete for
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202 INTELLIGENCE ANALYSIS: FOUNDATIONS
attention, one usually dominates, depending on contextual cues (Brewer
and Pierce, 2005). For example, a female professional may think of her-
self as an analyst at work and as a mother at home. Moreover, an analyst
might think of herself as an analyst when talking to collectors and as a CIA
employee when talking to a DIA analyst.
This type of automatic characterization not only helps us self-identify,
but also allows us to form a basic understanding of a socially different
“other” (Bodenhausen et al., 1999). Social groups can be thought of as
social categories, and people tend to form prototypic representations of
these categories in the form of exemplary members (actual members who
best embody group features) or ideal members (an amalgamated abstraction
of group characteristics) (Kahneman and Miller, 1986). As individuals self-
categorize, they represent themselves less as unique individuals and more as
embodiments of the relevant prototypic features (Hogg and Terry, 2000).
That is, self-categorization cognitively assimilates the self with the in-group
prototype. Therefore, this social grouping process gives an individual direc-
tion or guidance because group prototypes “describe and prescribe percep-
tions, attitudes, feelings, and behavior” (Hogg and Terry, 2000, p. 124).
People tend to conform to their groups (Asch, 1955) for both cognitive and
motivational reasons. Cognitively, conformity reduces uncertainty—when
confronted with a situation, individuals know how to react based on proto-
typical group norms. Social norms carry both a descriptive and injunctive/
prescriptive function (Cialdini and Trost, 1998). Motivationally, conformity
increases that member’s attractiveness in the eyes of other in-group mem-
bers (Mowday and Sutton, 1993).
Thus social categorization processes give people a sense of identity at
work (who they are) and provide them with guidance on how to behave.
Yet, these processes function like any other heuristic in constraining peo-
ple’s thoughts (e.g., expectations and attitudes about people and situations,
and attributions for events) (Salancik and Pfeffer, 1978) and behavioral rep-
ertoire. Social categorization may be natural, effortless, and in some ways
beneficial, but is not without the ethnocentric consequences discussed next.
HOW SOCIAL CATEgORIZATION INFLUENCES INDIVIDUALS
As noted above, individual thought and behavior is influenced by the
social environment, such as how employees are split into groups, what
behavior is rewarded, and what institutional routines develop. Interestingly,
people are often unaware of the extent to which their thought and behavior
have been shaped by their social context. We often believe that we think
and act as unconstrained free agents, when in fact, our “rational” thoughts
and behavior, including our awareness and imagination, are bounded by
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
our own frames of reference. In particular, we underestimate the extent to
which our thoughts and behaviors are shaped by subjective construal rather
than direct perceptions of an objective reality (Griffin and Ross, 1991).
“Culture” is one term that is often used to label a shared frame of
reference or a shared social context. Culture can be defined as a constel-
lation of values, assumptions, beliefs, behavioral norms, and routines that
define a group of people united by ethnic or organizational membership
(Benedict, 1934). It is what makes a collection of people a “group” (or as
Tylor, 1871, first described it—culture is a “superorganic” entity). Culture
offers members a social blueprint that interprets stimuli and guides group
members (Boas, 1940). Groups can differ according to how tight or how
loose their culture is, meaning how much “deviance” group members are
allowed before being sanctioned (Triandis, 2002).3 Most groups have com-
plex cultures, meaning one type of behavior (e.g., competition) is rewarded
in some contexts and a different behavior (e.g., cooperation) is rewarded
in another context.4 Yet, all cultures outline expected beliefs and behaviors
(although they may be context dependent) and reward conformity to these
ideals. In this way, cultures shape individual thought and behavior.
Decades of research supports the idea that culture influences group
members’ thought and behavior by showing that people of different cul-
tures respond to the same stimuli with different attitudes, beliefs, and
activities (Berry, 1980; De Vos, 1975; Erez, 1986; Leung and Bond, 1984;
Triandis, 1989; Wagner, 1995). Dearborn and Simon (1958), for example,
showed that socialization through organizational training systems produces
“managerial mindsets” that limit how people conceptualize problems and
solutions. In their study, they asked groups of executives from a manu-
facturing firm to study a particular company, and asked the executives to
identify the company’s most pressing problem. The study had three groups
from three functional cultures—sales executives, production executives,
and human and public relations executives. Each cultural group viewed
the same company data through a different lens, and thus offered three
entirely different proposals about the company’s most pressing problem
(sales, operations, and human relations, respectively).
3 Furthermore, depending on the size of the cultural group boundary, cultures can include
“subcultures.” Echoing footnote 1, for example, the CIA can have a dominant culture (certain
values, norms, and routines), then different subcultures for analysts versus collectors. This
level of analysis issue should not detract from the basic sociocognitive dynamics outlined in
the chapter. Social categorization processes can occur at any organizational level. The purpose
here is simply to document the intergroup dynamics that emanate once these categorization
processes occur.
4 For more on cultural complexity and its relation to context-dependent behavior, see Brett
et al. (2007).
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204 INTELLIGENCE ANALYSIS: FOUNDATIONS
Similarly, Tinsley and Pillutla (1998) found that socialization into
different national cultures led people to interpret the same negotiation
task in different ways. One cultural group assumed the goal of the nego-
tiation was to maximize joint gain, whereas the other cultural group
assumed the goal was to minimize the difference between each party’s
outcomes. This goal discrepancy corresponded with the groups’ actual
outcomes and with parties’ satisfaction with those outcomes.
In sum, cultural profiles offer members a roadmap for interpreting stim-
uli and guiding behavioral reactions. At the same time, by focusing atten-
tion and behavior, these roadmaps also constrain thought and action. By
institutionalizing an optimal way to think and behave, these roadmaps can
suggest that other thoughts and behaviors are suboptimal or even wrong.
Accordingly, interactions among members of different cultural groups that
have different missions, approaches, and routines can be strained.
INTERgROUP DYNAMICS FROM
SOCIAL CATEgORIZATION PROCESSES
One of the most robust findings from cultural research is that of eth-
nocentrism, which literally means putting one’s own group at the center
of the universe. Anthropologists (Boas, 1940; Mead, 1964; Kroeber and
Kluckhohn, 1952; Lowie, 1966; Malinowski, 1944) find that people learn
to be ethnocentric through socialization in a particular social system, which
rewards appropriate thought and behavior while sanctioning inappropriate
thought and behavior. Hence, members come to believe that their group’s
values, beliefs, behaviors, and organizing principles are superior to those
of any other group. In the IC, this might be reflected in the CIA believing
its practices to be “the gold standard” (Goss, 2005) or in the INR being
promoted as “the biggest little intelligence shop in town” (Aspin quoted in
Ignatius, 2004). Evolutionary psychology considers ethnocentrism to be an
innate outgrowth of nepotism (van de Berghe, 1981), meaning ethnocen-
trism has a natural survival value for the group.
In-group Bias
Psychologists tend to focus on the costs of ethnocentrism, including “in-
group bias” or the tendency to see members of one’s own group in a more
positive light relative to members of other groups (Tajfel, 1970). For example,
in the IC, this might be reflected in a predisposition to favor types of informa-
tion (e.g., clandestine human intelligence) produced by the agency in which
the analyst is embedded. Across a variety of studies outside the IC, people
have judged members of their in-groups to be smarter, more attractive, more
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
cooperative, fairer, more trustworthy, and more hard working than members
of out-groups (cf., Brewer, 1979; Tajfel, 1970, 1982). This prejudice generally
seems to entail withholding positive traits from the out-group rather than
actively assigning negative traits to them (Fiske et al., 1999), and it is found
to enhance the status of the in-group rather than degrade the out-group
(Tajfel, 1982). Strikingly, this in-group bias occurs not only across real-life
groups, but also can be activated with groups created in the laboratory based
on minimal or random criteria, such as having the same birthday or similar
final digits in Social Security numbers (Brewer, 1979; Brewer and Kramer,
1982). Moreover, in-group bias can occur with or without direct interaction
(e.g., attitudinal biases that arise simply through observation or awareness of
an out-group member), and without any prior personal history between the
parties involved (Kahn and Zald, 1990).
From a practical standpoint, in-group favoritism is problematic in
social landscapes with more than one group. First, it leads to discrimina-
tion, with in-group members being treated better than out-group members.
People award higher monetary payouts and emotional payouts, such as
helping behavior, to in-group members than to out-group members. Second,
the bias leads to perhaps the most common problem in intergroup relations,
“reciprocal antipathy,” or the difficulty of getting groups to cooperate with
each other. As Kramer notes (2005, p. 407):
The problem of securing cooperation between interdependent groups has
been a central and recurring theme in the study of intergroup relations
from its inception (Sherif, 1966a; Sumner, 1906). Whether they are mini-
mal groups created in laboratory settings (Tajfel, 1970), groups of boys at
summer camp (Sherif et al., 1961), groups within organizations (Mouton
and Blake, 1986), or even nation-states (Kahn and Zald, 1990), recipro-
cal antipathy between groups seems to develop with surprising frequency
and alacrity.
In the IC, for example, this might create problems with respect to
information sharing and create various “security regulations” that make it
difficult for analysts to access information not collected or disseminated to
their agency, or rules that limit access to certain databases (see Fingar, this
volume, Chapter 1).
In-group bias impairs actors from different groups from cooperat-
ing with each other, even to achieve a mutually desired end state. Often
simply associating oneself with an in-group leads to biases favoring one’s
group over others (Cadinu and Rothbart, 1996; Smith and Henry, 1996;
Turner, 1987). Homophily, or the tendency to be attracted to those who
are similar to oneself (Blau, 1977; Berscheid and Reis, 1998), suggests that
the simple categorization of others into a different group can produce bias
and decrease cooperation.
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206 INTELLIGENCE ANALYSIS: FOUNDATIONS
Therefore, in-group favoritism does not necessarily stem from faulty
incentive structures. Actors from two different groups can be given incen-
tives to solve a particular problem or to share mutually needed informa-
tion, yet still suffer coordination difficulties. Rather, in-group favoritism
is rooted in the sociocognitive categorization mechanism, which primes
a sense of difference that eschews cognitive and motivational roadblocks
to cooperation. Recall that self-categorization is a process where someone
cognitively assimilates his or her self-concept to the in-group prototype. A
critical feature of group prototypes is that of meta-contrast, meaning proto-
types maximize similarities within each group and differences across social
groups (Hogg and Terry, 2000). For example, Ledgerwood and Chaiken
(2007) find that people tend to radicalize their attitudes to assimilate to
those of the in-group and contrast from those of the out-group. This might
play out in the IC, for example, in predispositions to dismiss alternative
judgments and hypotheses that originate outside of one’s agency (the “not
invented here” problem).
Out-group Homogeneity
A second outgrowth of ethnocentrism is the “out-group homogeneity
effect,” or the tendency to see members of one’s own group as differentiated,
but to perceive out-group members as similar and unvaried (Quattrone and
Jones, 1980). Seeing in-group members as more varied cannot be attributed
to knowledge and exposure, as this effect is found between groups, such
as “men” and “women,” who interact frequently (Mullen and Hu, 1989).
The problem that arises from out-group homogeneity is stereotyping.
A stereotype is a mental model that an actor has of another person based
on the target’s social category membership (Lippman, 1922; Fiske and
Taylor, 1991), so that the actor ascribes personality traits to the whole
social category and subsequently confers these personality traits onto any
member of that social group (Spencer-Rogers et al., 2007). Holding ste-
reotypes about another social group is useful to the extent that members
of the group behave in stereotype-consistent ways. Unfortunately, research
shows that actors tend to discount stereotype-inconsistent behavior from
targets. For example, actors tend to follow stereotypic information about
an interdependent work partner, even when this information is fictitious
and assigned on a random basis (Tinsley et al., 2002; O’Connor and
Tinsley, 2009).
Although stereotypes are technically a cognitive phenomenon, they
elicit an emotional concomitant that can be negative.5 The IC, like other
5 Although most stereotypes are thought to elicit negative emotions toward others, not all
stereotypes do so. Fiske and colleagues (1999, 2002) detail four general types of stereotypes
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
organizations, has many stereotypes that affect the way analysts in one
agency think of and deal with their counterparts in other agencies. Com-
mon stereotypes include the perception that INR analysts are predisposed to
believe what foreign officials claim to be the case and attach greater weight
to diplomatic reporting than other forms of intelligence; that CIA analysts
give greater credence to clandestinely acquired human intelligence; and that
DIA analysts are prone to exaggerate military threats and to favor worst case
possibilities.
Whether these stereotypes are true or not (or are based on truth but
exaggerated, or were true but no longer are so) is irrelevant. Any stereo-
types that analysts hold of each other will influence their expectations of
each other and their decisions about whether or not to reach out and ask
one another for help. Stereotypes can cause collaboration problems because
the actor is conferring group-level information on an individual, who may
or may not “fit the profile.” Thus, analysts can misunderstand each other’s
needs and abilities. Moreover, because we tend to discount situational
explanations for others’ behavior (Ross, 1977; Jones and Harris, 1967),
and these attribution errors are more pernicious for out-group members
(Allison and Messick, 1985), an actor could easily misperceive a target’s
intent and ascribe a more sinister motive, making any interaction more
emotionally trying than it needs to be.
Do these intergroup problems pervade every organizational interac-
tion? Of course not, but social categorization and intergroup dynamics
represent the backdrop against which everyday organizational activities
occur. Like background music that sometimes fades out of awareness and at
other times becomes an annoying distraction, intergroup issues can remain
quiet or create a disconcerting amount of static. The next sections describe
research on when intergroup dynamics are relatively dormant versus when
they come forward as a powerful force shaping the interaction.
WHEN MIgHT INTERgROUP DYNAMICS BE MORE ACUTE?
In certain circumstances intergroup biases have an especially acute
influence on members’ cognitions and behaviors. Generally, the degree of
along two dimensions, the warmth of the target and the presumed competence of the target.
Thus, an actor’s social categorization of a target can elicit feelings of: (1) low warmth/low
competence, (2) low warmth/high competence, (3) high warmth/low competence, or (4) high
warmth/high competence. Presumably, actors who think the target belongs to this last social
group should have a relatively easier time working with this target than with a target catego-
rized in one of the other three groups. Indeed, in a collaboration task, O’Connor and Tinsley
(2009) found that people’s positive stereotypes of each other lead to high collaboration and
high output, even when the information was false and even when only one party made such a
positive inference about the other. Unfortunately, however, Fiske et al. (1999) find that people
tend to reserve this high-warmth/high-competence stereotype for fellow in-group members.
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214 INTELLIGENCE ANALYSIS: FOUNDATIONS
to imagine a day in the life of an out-group target decreased stereotype
activation and in-group favoritism.
Similarly, decreasing group distinctiveness by having out-group members
disclose personal information or by removing cues of social dissimilarity like-
wise decreases intergroup bias (Bettencourt et al., 1992; Brewer and Miller,
1984; Gollwitzer et al., 1999). All these interventions are likely to reduce
in-group favoritism because they function subconsciously on the actor. The
actor is not aware of the social categorization processes or, more specifically,
that the target’s categorical distinction from the self has evaporated.
Social Networks
Once actors are individuated, integration still requires a way for them to
connect. Network scholars insist that every organization has a complex web
of informal ties among individual employees (Krackhardt, 1990; Granovetter,
1985). Many kinds of social networks exist, such as advice networks, trust
networks, and communication networks. These networks can literally be
mapped by asking employees whom they go to for advice, whom they trust,
whom they talk to every day, whose job they could assume with only 1 day
of training, or whom they would recruit to support a proposal that might be
unpopular. Generally a tie is said to exist between two people only if both
individuals claim it does (Wellman and Berkowitz, 1988).
Network scholars also advance the idea that these social ties grow
organically during the natural course of task accomplishment and that they
can either be functional or dysfunctional to the organization (Krackhardt,
1990). Because managerial perceptions of social networks are usually inac-
curate, upper managers are exhorted to uncover these networks through
objective mapping. One configuration that is particularly problematic is an
“imploded relationship,” in which a group of actors tightly linked within
a group have no (or few) links outside the group. Also problematic is the
“bow tie,” in which two imploded groups are linked to each other by only
one (or a few) connections (Krackhardt, 1990).
Most prescriptive research in this area focuses on how individuals can
build more personally useful social networks. Granovetter (1985) discusses
the “strength of weak ties,” or the notion that the most useful people in
your network may be those who are one tie removed from you, as they
are likely to have access to novel information and opportunities; by con-
trast, people to whom you are immediately linked tend to have the same
information you have. Thus, Uzzi and Dunlap (2005) caution us to beware
of networking only with people we like or with those who are geographi-
cally convenient because they are not likely to offer new information or
perspectives.
Because most scholars look at networks within firms, where they appear
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SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
to flourish without encouragement, only scant research is available on how
to promote the organic growth of networks. Gulati’s work (1995; Gulati
and Nickerson, 2008) that looks at network ties across firms discusses the
importance of trust in alliance formation. Generally, alliances grow from
the motivation and instigation of individual actors. Actors must feel they
need something the target has (e.g., another type of intelligence) and must
trust that if they ask for it, the target will be responsive. When someone
allows himself or herself to be vulnerable and the other person does not
violate that vulnerability, trust grows.
In the context of the IC, collaboration across agencies both requires
trust and can engender trust. Collaboration requires trust because the initi-
ating analyst will identify and admit to a need (making the initiating analyst
vulnerable) and responding analysts will share sensitive information to meet
these needs (making responding analysts vulnerable). Trust helps bridge this
chasm of risk. When initial acts of faith result in fulfilled promises, recipro-
cal disclosures, and non-opportunistic behavior, then trust builds.
Unfortunately, the process of building trust can take some time. Build-
ing trust among analysts of different agencies can be difficult to engineer
from above. “Bonding” experiences, such as Outward Bound trips that are
not task relevant, risk becoming trite. However, creating a work-related
task in which analysts from different agencies must cooperate with each
other should build trust, assuming the agents perform well together. Allow-
ing these agents space to cooperate in a task-focused manner, and giving
them a little extra time to get to know each other, might foster mutual trust.
One intriguing idea is that analysts may be able to develop “swift trust”
(Myerson et al., 1996), which is the collective perception that vulnerability
that may exist in temporary systems will not be exploited. Swift trust seems
to occur for people whose personalities predispose them to trusting others.
Highly trusting people look for confirmation in other’s behavior, in particu-
lar whether those others have been helpful and enthusiastic (Popa, 2007).
Therefore, some (e.g., high trusting) analysts who might be able to achieve
a high rate of production collaborate rather quickly, despite the temporary
nature of this interaction.
Online tools such as A-Space, Intellipedia, and the Analysts Resource
Catalogue offer resources for analysts wishing to network with each other
in real-time to solve discrete tasks and find answers to less well-defined
research questions. In these new communication spaces, people may feel less
vulnerable, and this “swift trust” might develop more readily. The burgeon-
ing research on social networking sites, such as Facebook and LinkedIn,
might be useful to investigate because many of these social networking
sites are now being used for transactional purposes (e.g., online market-
ing and product promotion). Traditional communication literature makes
a great distinction between the types of messages that can be effectively
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216 INTELLIGENCE ANALYSIS: FOUNDATIONS
communicated online versus face to face. For example, Media Richness
Theory (Daft and Lengel, 1984; Daft et al., 1987) contends that the more
ambiguous and uncertain a task is or the more equivocal the communica-
tion needs, the richer8 the communication medium should be. However,
whether this is still true for the generation bred on virtual communications
and connections is unclear.
Casciaro and Lobo (2005) instruct upper managers to leverage the
power of likable people to initiate connections among various unconnected
individuals. They find that most people would rather interact with a “lov-
able fool” than a “competent jerk” in an interdependent work task. Thus,
they argue that likable people (those who are empathetic, generous, and
socially skilled) can reach out to others and even serve as brokers among
different groups. Although the idea that people will respond to likable oth-
ers makes sense (even if they are relative strangers asking for resources),
whether any of these connections would flourish once the “likables” are no
longer involved is uncertain.
The emphasis on likability calls to mind Cialdini’s extensive work
on persuasion—how to get people to do something for you that they
otherwise might not do. His six “weapons of influence” (Cialdini, 2008)
include (1) likability—we are more likely to say yes to someone we like
than to someone we do not like; (2) authority—we are more likely to say
yes if we’ve been instructed by an authority figure to do so (see above sec-
tion on integration through managerial hierarchy); (3) commitment and
consistency—we are more likely to commit to larger favors after having
already done a smaller favor (the “foot-in-the-door” technique); (4) social
proof—we are more likely to do something if we see others doing it (see
above section on culture and conformity); (5) reciprocity—we are more
likely to do something for someone who has done something for us; and
(6) scarcity—we are more likely to do something if we will get something
scarce in return. Future research might look at whether these principles
can be applied by analysts to encourage others to collaborate with them.
Moreover, do analytic networks grow organically, emanating from pockets
of likability, commitment, and scarcity?
8 A communication medium richness is a function of (1) the medium’s capacity for immedi-
ate feedback; (2) the number of cues and channels available; (3) language variety; and (4) the
degree to which intent is focused on the recipient. Richer media are said to create a greater
“social presence,” immediacy, and warmth.
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217
SOCIAL CATEGORIZATION AND INTERGROUP DYNAMICS
CONCLUSION: WHY INTERAgENCY
COLLABORATION IS VITAL
Hazards flourish in areas where no one is directly responsible. In the
IC’s current environment of complex interconnected systems, risks are dif-
ficult to monitor, and uncertainty is inescapable. Unfortunately, because
of this complex interconnectivity, even minor hazards can escalate to have
large consequences (Perrow, 1984). This uncertainty is not all bad. New
situations can bring new opportunities for process of innovation. At the
same time, meeting new challenges can eschew unintended negative results
that can be disastrous. Thus, integration processes should be undertaken
mindfully. Intelligence needs to be as interconnected as the system of poten-
tial hazards might be. This interconnectivity means integrating intelligence
analysis across agencies to help IC members “work the spaces between the
cases” (Hayden, 2009).
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