Swinging the Tomahak - The Role of Cultural Experts in War Fighting

Dr. William Mitchell, Royal Danish Defence College Institution for Leadership and Organization R & D Section, C2 and Intelligence


This article describes the role of the cultural expert as open source intelligence  (OSINT) capacity within the military intelligence (MI) organization, supporting  the operational planning process (OPP) in a complex battlespace. The article  begins with the ontological foundation for the development of cultural  knowledge in a battle space, then synchronizes this understanding with current  effects based philosophy, and then illustrates how it is used in the field to  support course of action (COA) production.1  Examples presented in this article  specifically illustrate how cultural experts working with identity and norm  attribution can help with network identification, generating hypotheses,  populating iterative models, and target generation in an area of operations (AO).   

Learn all you can about Ashraf and Bedu. Get to know their families, clans, and tribes, friends and enemies, wells, hills, and roads. 

T.E. Lawrence, The 27 Articles of T.E. Lawrence (“Lawrence of Arabia”) The  Arab Bulletin, 20th August, 1917  US Army Manual (2009), FMI 3‐24.2, Tactics in Counter Insurgency, March 2009   


The role of cultural intelligence to support leadership in their decision‐making  has once again come to the forefront of warfare.  It is not as new as one would  like to think, it was for the most part the mainstay of the British & French Colonial Empires. Here a few troops could maintain a colony through the  knowledge of local cultural norms and identities: “/…/ captains, lieutenants and  sergeants must perform with excellence in areas such as local politics, as well as  social, education and economic development of the population.”2  My own  experiences with the French Foreign Legion training the local military units in  Chad, Central Africa, and Zaire, certainly impressed the value of integrating a  high level of updated political and cultural intelligence into our daily planning.  With limited logistical support and no close air support (CAS) ‐ our lives simply  depended on it.  15 years later I can still remember of names of key actors in my  areas of operations (AOs) from the Zaghawa and Tama clans of Eastern Chad.3   

This article is an introduction to the role of cultural experts as a battlespace  intelligence capacity to support our war fighting organization and its decisionmakers. To be clear, this article is not about how we use cultural awareness to  win hearts and minds, it is about how we exploit cultural intelligence within our  operational planning process (OPP) to support course of action (COA)  production. This includes target generation and evaluation within an effects  based approach to operations (EBAO) framework by our military intelligence  (MI) organization.   The mainstay of our organizational sense‐making4 support  available to battlespace leadership is our MI organization and analysts.  Intelligence in its most generic sense is the sum of what is known, integrated  with new information, and interpreted for meaning.Therefore a fundamental assumption of this article is that operations in war are intelligence enabled, and  commander driven. If operations are not intelligence enabled and commander  driven, what are they enabled by?     

It is within this organizational context, and the age of complex battle  spaces, that having a cultural expertise within the MI organization has a direct  role to play in COA production and the resulting actions in the battlespace. Focusing on the role of the cultural expert integrated in the processing stage of  the MI cycle as an Open Source Intelligence (OSINT) capacity, this short article  will only be able to present a limited picture of the role of cultural knowledge in  the processing stage of MI. Specifically  it will illustrate how cultural expertise  concerning identity and norms can inform MI network identification and  management, hypotheses generation and evaluation, and iterative model  generation in an area of operations (AO).  The article is divided into three  sections; the theoretical foundation for exploitation of cultural knowledge in  the battlespace based on social constructivism, existing war fighting  philosophy, and illustrated examples of the integration of cultural expertise in  war fighting.     


PART I: A Constructivist Foundation 
Sense‐making, at every level of decision‐making, in any organization or  individual, in any situation, is subject to some ontological foundation or  worldview that will inform that process. One can choose to engage the metatheoretical level in self‐reflection as to one’s methodology, as done in this  article, or one can choose to ignore it, and hope by doing so it does not  undermine your attempts to manage uncertainty in the search for knowledge.   Discussions concerning knowledge development in war are no different, and  despite my preferences for discussions grounded in anecdotes from the battle  space, it is my belief that the management of uncertainty is always better  served by a self‐reflecting engagement of the ontological positions we  inherently adopt when building those anecdotes.  Symmetrical measures for  strategic reference within the logic of strategic choice6 for parties to a conflict  can no longer stand alone. The last 15 years has seen the development of war  fighting environments that depict two distinct ontological7 domains for  strategic reference, one physical and the other cognitive.8 An example of this  shift in strategic interaction understanding comes from the Taliban leadership  themselves, where 15 years ago they defined victory by the taking of Kabul (physical dimension) – today they define victory by a cognitive term roughly  translated from several Pashto words as – legitimacy (cognitive dimension).  They plan their operations to de‐legitimize the Afghan government.  Conversely, based on a two pronged strategy promoting security and  development, the NATO plans operations to legitimize the Afghan  government.   Social constructivism as it is used here to explain battlespace complexity is  defined as the view that the material world shapes and is shaped by human  action and interaction dependent on dynamic normative and epistemic  interpretations of the material world.9 Constructivists consider interpretation  as an intrinsic part of social science that stresses contingent generalizations,  meaning that they do not freeze our understanding but open up the social10  world. The issues currently focused upon, originate from the belief that  reflexive knowledge (interpretation of the world) when imposed on the  material reality of the world becomes knowledge for the world (see Fig. 1). This  understanding suggests that ‘social facts’ such as identity or norms, can act as  the objects of the intelligence cycle emerging from the interaction between  knowledge and the material world – intersubjectivity 11 – neither of which are  fixed.12   


Fig.1 Constructivist Sense‐Making 


Adopting a constructivist framework provides a theoretical foundation for  our understanding of complex battle spaces that incorporates both the  cognitive and physical domains. Ontologically speaking it is this intersubjective  dynamic that suggests directly that understanding the battlespace does not  just depend on understanding the material ‐ but also the ideational.13 That  concepts such as culture, identity, and norms that have played a role in  understanding the international environment14 in which we have made security  policy for over a decade,15 can also play a role in battle space sense‐making.   

Epistemologically, constructivism is well developed as the methodological  bridge16  between positivist and behavioural approaches; this is extremely helpful in terms of sense‐making in a complex battlespace, opening the social  sciences to a greater degree than ever before, for use in MI analysis and operational planning, without rejecting the material/efficiency concerns of  positivists.17

Traditionally MI has been dominated by positivist approaches to sensemaking based primarily on material/efficiency descriptions within the time and  space dimensions of World War I, World War II, and the Cold War,18 where the  social‐sciences were given very little place in MI.19  This is not an easy shadow  for MI to shake. Constructivism as a theoretical approach, like intelligence  analysis as a process, does not lay claim to an objective certainty. Instead, it is  in the fundamental nature of both to advocate a pragmatic approach to  managing uncertainty, a characteristic also shared with C2 research in  general.20  Civilian intelligence analysis has for some time used constructivist  techniques to supplement or even direct collection processes.21 Profiling  personalities or governments, such as assigning them an identity as a radical or  a moderate, has been used to help predict which norms are relevant, and based  on those norms, predict patterns of behaviour. 

In Ted Hopf’s “Promise of Constructivism in International Relations Theory”  presented in International Security in 1998, there is a clear theoretical outline of  a brand of constructivism fully capable of an instrumental role in the MI cycle,  particularly where it  concerns the attribution of identities and norms. 

Identities are understood as having three accepted functions in a society.  They tell you who you are, and who others are, and they tell others who you  are. Identities are necessary in social systems to maintain a minimum level of  predictability or stability.22 Therefore any actor that is socially organized has an  identity as a unit in the system, and this identity implies it has its own  preferences and consequent actions within the system.23 Thus this identity is a  functional concept in MI analysis methodology because it can contribute to  establishing the subjective context for evaluation in a battle space. A conventional constructivist understanding of identity also allows evaluative  access to norms, contributing to the construction/evaluation of strategic  preferences. This in turn may be used to make predictions on how the actor will  react under a given set of circumstances in the battle space. It does so by  formally recognizing the existence of the intersubjective dynamics concerning  the construction of an actor’s identity, including that the producer of the  identity is not in control of what it means to others, and will therefore also  include an ‘intersubjective’ degree of influence over the final meaning.24 

Norms are also viewed by conventional constructivists as a functional  concept and can generally be defined as the ‘shared’ understandings of  standards for behaviour. The first is that norms are embedded in webs of preexisting meta‐norms. This allows for the establishment of a fixed  understanding of systemic influence within the relevant system of social  exchange such as a battlespace.  The second, it allows for the establishment of  fixed understandings where it concerns the perceived behaviours within the  system of social exchange. Or if you will, it allows for the nature of behaviours  adopted, producing objectively recognizable non‐material influence on  decision‐making, to be fixed for consideration within a subjective assessment.  Finally, and very important to the conceptual linkage of norms to strategic  preferences, is that norms define interests and identities.25 Here the actual  application of the intersubjective dynamic surrounding the influence of norms  meets its’ contextual end state within MI through the evaluation of preferences  and how actors go about achieving them. 

Furthermore, constructivism’s inherent purpose is to understand the role of  intersubjective interaction between the cognitive and physical domain,  consequently it is naturally at ease with the current EBAO26 philosophy that  informs current operational doctrine in the West. Quite simply both are based  on recognition of the cognitive and physical domains with regards to sensemaking.


Part II: Existing Doctrine & Philosophy 
The constructivist understanding presented here currently lies within a military  context defined by a NATO in transition27 that started in the 90’s and a high  profile mission in Afghanistan.  The development of the concepts in this paper  are not immune to this context, and are heavily influenced by what EBAO  represents as a sense‐making framework for complexity requiring both the  social and physical sciences.28   

The analytical challenges of engaging this complex environment are  reflected well in Tom Czerwinski’s ’billiard’ metaphor and the concept of  tagging.29 NATO’s PMESII30 guideline attempts to do just that with the  complexities of an asymmetric battlespace by dividing it up into different  dimensions for strategic reference when decision‐making or planning. Instead  of there being just a military dimension, they must now consider PMESII  dimensions of their battlespace.31 By doing so the PMESII network hopes to  make the predictions of the non‐linear interactions more manageable.     

PART III: The Role of Cultural Experts in War Fighting
Most intelligence cycles32 in the military are iterative processes that reflect four  stages; direction, collection, processing, and dissemination, in some way or form  (see Fig.3). The purpose of the intelligence cycle is to deal with all the available  information, decide relevance, search for the missing information, process it  into something even more relevant, and make it ready for distribution. 


Fig. 2 PMESII – A System of Systems Understanding 



Fig. 3 Generic Intelligence Cycle 


Complexity in modern warfare requires more than Order of Battle styled  reports (ORBATS.)33  ORBATS are one of the traditional products of basic MI  output. It usually covers tracking primarily material/efficiency concerns from  the military dimension such as aspects of the opponent’s equipment, capabilities, performance,34 and some relatively light socio‐political matters  relative to leadership or logistical support.35  For the implementation of EBAO  to be effective ‐ it must be supported by relevant36 intelligence collection from  non‐military dimensions and an expansion of the knowledge base primarily  through non‐ORBAT information37. The nature of MI analysis has traditionally  been descriptive in terms of the time and space dimensions.38 However EBAO  requires a great deal more predictive battlespace awareness (PBA)39 for the  commander and it is here the challenges lie in terms of adjusting the training of  our MI analysts. In short, applying PMESII to meet the challenges of the  complex battlespace within an EBAO context will require a shift from a focus  on descriptive analysis to predictive analysis in terms of the nature of MI  analysis40. It is here cultural experts have a role to play in the war fighting  organization. Unclassified knowledge experts of any kind are an OSINT  capacity, and current conflicts call for a greater role for cultural knowledge  experts (see Fig.4).  The remainder of this section presents several examples of how cultural  expertise can be exploited in the Operational Planning Process (OPP) through  its contribution to the MI cycle. The examples will focus on the contribution of  expertise concerning identities and norms to the MI cycle and COA production.     

(1) Network Philosophy 
 The technological aspect of network centric warfare (NCW) is no longer the  main challenge41, it is the human and social networks that we are now  grappling with to improve our sense‐making in the battlespace.42 From the  perspective of a constructivist approach to managing complexity, network  thinking acts as method managing and communicating a representation of the intersubjective relationships between the physical and cognitive domains in the  battlespace. Usually depicted as a system of systems (such as PMESII), it slows  the intersubjective dynamic down relevant to the task at hand, and enable  opportunities for a more comprehensive understanding of actions and effects  within the EBAO framework.  Fig.5 illustrates how network thinking can frame  the intelligence cycle relevant to the commander’s intent in an AO in  Afghanistan.  The objective represented here is simply for the Coalition Forces  (BLUE) to move more of the undecided population (WHITE) over to supporting  the Government, than there was when they first arrived in theatre. Cultural  expertise will come into service here where it concerns the attribution of  identities and their objectives, for example vis‐à‐vis WHITE, as well as  consideration of how their own actions affect this system as a whole. 43 Ideally  this would require cultural experts involved in the Intelligence Preparation of  the Battle Space (IPB), input into the tasking or direction of collection assets,  and management of collected data relative to the established framework of  AO networks. It is important to note here that generic skills in terms of  establishing or attributing identities and norms (patterns of expected  behaviour), are more important than culture specific knowledge. 

Based on this network centric framework for commander’s intent in the  AO, standing iterative models for the AO can be established and maintained  that will assist in timely effects assessments. For example in Fig.6, a standing  model representing the compounds of the AO and the political leanings of their  owners, if kept up to date, will support the Commander in making a timely  decision. This could be whether or not to risk close air support (CAS) in an  engagement, vis‐à‐vis their objective of moving undecided support towards  the government. MI analysts with cultural expertise, particularly where it  concerns attributing identities (in this case RED, WHITE, BLUE,) will be the  most effective at keeping this standing model as accurate as possible through  the iterations. Simply because they should be in a better position to judge what  collected intelligence suggests in terms of populating the model based on  identities.   

From the standpoint of the MI cycle, cultural experts will contribute directly  to how we determine what should be tasked, collected, processed, and  disseminated.  From a knowledge development standpoint, MI cultural experts  as an OSINT capacity will assist in building our networks to counter opposing networks in complex battle spaces. Determining which networks are relevant  to the commander’s intent for an AO, and what can be managed (information  collected, collated, and interpreted) in a timely manner by your own  knowledge development network is very challenging (see Fig.7.)  It stands to  reason that if local norms and customs play a large role in the behaviours and  actions of actors in an AO, having MI analysts with a cultural expertise will  assist in COA production.  


Fig. 4 Role of Culture Experts the MI Cycle 


(2) Iterative Modelling 
 From a constructivist standpoint iterative modelling converts the dynamism  behind network thinking to more practical applications of managing  intersubjectivity, within a ’tagging’ framework  of inter‐systemic relations such  as PMESII. It is also an essential skill if we are to have any chance at  maintaining timeliness in a more complex battle space. A model can be a  replication or representation of an idea, an object, or actual system.44 More  importantly, it often describes how a system (or network) behaves.45 Models can be used to describe, explain, and predict. They can be used in the  intelligence cycle to create baseline references and for building up databases of knowledge that can be manipulated to advantage (as in Fig.6). Specifically, the  ability to systematically produce relevant mental models to increase the overall  effectiveness of MI output is paramount.46 EBAO inherently places the weight  of modelling application on prediction in terms of qualifying desired and  undesired effects47 and the production or assessment of actions.   


Fig. 5 Network Thinking Applied, NATO 


Fig.8 is an example of simple iterative modelling put into the Afghanistan  context, depicting a local Improvised Explosive Device (IED) cell, and another  network structure reflecting the local Taliban Command & Control (C2)  structure or an ‘outer‐shura.’ In both models the organizational structure,  process, and function are represented, and therefore are well suited for use  with MI cycle iterations. However these networks exist against a background of  social and cultural complexity. Providing cultural perspective on the context in  which these networks exist is an important role for cultural experts. 

Basic iterative models for an AO quickly become part of the overall system  of systems understanding through link analysis as well. Fig. 9 illustrates how a  comparative analysis of the intelligence populating the two basic iterative models in an AO produce links between them that can be quickly represented  and shared with other analysts. However understanding the nature of these  links must include due consideration to the existing cultural dynamics that  form the backdrop to any actions. It is here cultural experts, as part of an  integrated OSINT platform, provide insight and perspective into COA  production.  


Fig. 6 AO Compound ID vs. Commander’s Intent 



Fig. 7 ‘Network vs. Network’ Understanding for an AO in Afghanistan 


Fig. 8 Basic Iterative Models in Action 


Fig. 9 Basic Iterative Models & Link Analysis 


(3) Hypotheses Generation and Evaluation 
From a constructivist perspective hypotheses generation and evaluation are  the methodological skills necessary to slow intersubjectivity down by  analytically forcing different systems into dynamic relationships with other  systems for analysis. Managing a system of systems framework such as PMESII  inherently places the weight of analysis and estimates on hypotheses defined  relationships, primarily between PMESII domains. Managing the social  dimension is the primary role of cultural experts in the MI cycle. They can do so  through managing standing iterative models, such as land ownership by tribe,  thus assisting in the generation of useful dynamic hypotheses for the AO.  Fig.  10 and Fig. 11 illustrate how crossing known firing positions in an AO with  known tribal divisions within the AO can produce some useful hypotheses for  use by the MI and OPP cycles. Therefore ased on this, target generation and  evaluation resources can be focused on key members of Khel B’s C2 structure,  mutually supported by focused non‐kinetic operations synchronized with  psychological operations (PSYOPS.) The validity of the dynamic hypothesis can  be checked with each MI cycle iteration.  


Fig. 10 Known Firing Positions in AO vs. AO Tribal 


Fig. 11 Military Dimension‐Social Dimension Integration 


Resulting dynamic hypothesis for use in the OPP for COA generation: Members  of the Khel (Clan) B are more likely to directly support the Taliban than members  of Khel A, C.   

Within this context cultural expertise can also be used for the generation  and evaluation of targets relative to an AO. In short, the use of pattern of life  analysis to help focus collection assets, and ‘box in’ high value targets related  to these models, are of particular use.  Here local norms or customs could help  us predict when a target will be required to talk or meet with someone.  Elements such as tribal rankings and traditional communication processes are  extremely useful to narrow the focus of collection assets and generate  targeting opportunities.48 Fig.12 and Fig. 13 represent the same process but  with processed signals intelligence (SIGINT) analysis exploited together with  the relevant tribal information for the AO. Again the ‘what to put together’ and  ‘how’ will sometimes be the result of already existing hypotheses, such as in  this case the hypothesis used by the SIGINT to relate the SIGINT hits to  movement and a pattern of transport with confidence. The role of the culture  expert is to exploit the MI cycle to insure that such relevant tribal information is  as accurate as possible and therefore giving the produced hypothesis validity in  its role of COA production support.  


Fig.12 Analysed SIGINT Hits vs. AO Tribal


Fig.13 Military Dimension vs. Social Dimension


Resulting dynamic hypothesis for use in the OPP for COA generation: Members  of Khel B are more likely to have knowledge of Taliban weapons caches in AO  then members of Khel A, B.   

Cultural expertise contributes directly to making the network philosophy,  iterative modelling, and hypotheses generation and evaluation more effective  in complex battle spaces.  This short article attempted to illustrate that cultural  expertise not only has a direct role to play in the MI cycle and COA production,  but that this role is built on solid ontological foundation, that in turn,  synchronizes well with current EBAO philosophy. These techniques have been  in use by some elements of Western MI; however there is plenty of room for  further research and a synchronization of standards.  In the process we could  build a common MI analytical language for use in complex battle spaces, and  for promoting sense‐making tools, that will last well into the 21st Century. The  further development of culture experts as an OSINT capacity for MI will likely  be one of those tools.   



The Title refers to the Canadian first nations, the Algonquian word for a light one handed axe that  became famous as the native’s preferred weapon of choice for close combat  and the subsequent honour of scalping defeated opponents. Highly decorated  tomahaks became symbolic gifts that reflected the importance of various  chiefs and the honours afforded to them. The English spelling of the word is  “Tomahawk” and is better known as the adopted name of a US cruise missile system. 

2 Raoul Giradet, La Société Militaire de 1815 à nos jours, Perrin, 1998, 228. 

3 For a good overview of this period see Colonel Henri Boré, “Complex  Operations in Africa,” Military Review, March –April 2009, 65‐71. 

4 See the growing Command & Control (C2) epistemology  engaging power to  the edge (Alberts & Hayes, 2005) research with a specific focus on agile sensemaking   (Alberts and Hayes, 2005, 27). The building of  cultural expertise as an  OSINT capacity as  presented here will affect common C2 variables such as  information, predominant information flows, information management, and  sources of information directly, because of its focus on military intelligence (MI)  analysis and planning. As a result, secondary affects on key C2 variables such a  Command, Leadership, Control, Decision‐making, Organizational Processes  (Alberts & Hayes, 2005, 218; SAS‐026 NATO 2002; SAS‐050 CCRP/NATO  2006). 

5 This understanding includes classified and unclassified sources of information  or knowledge and is widely accepted in intelligence studies. The inclusion of  unclassified sources has always been there, but their role has become  prominent as Open Source Intelligence (OSINT) in tact with the quantum leap  forward of internet information sharing.

6 See Luttwak 2001, 3‐50; Luttwak 1998. 

7 Understood in this paper as simply the nature of reality. 

8 Nicholson 2006, 133‐136. 

9 Adler 1997, 322; Adler 2002, 104‐109. 

10 A general reference to the generic meaning in social science. 

11 See conventional constructivism in Ted Hopf’s “Promise of Constructivism in  International Relations Theory” presented in International Security in 1998.   

12 Adler 1997, 327‐328. 

13 Checkel 1998, 324‐348; Reus‐Smit 2001, 218.   

14 See Katzenstein 1998, 1993. 

15 The 1990s saw the fastest growth of constructivist thinking in security policy  analysis: Hopf 1998; Barnet 1996, 1998, 1999; Finnemore 1993, 1996, 1998,  2001; Kratochvil 1996, 1989; Klotz 1995; and Wendt 1992, 1995, 1999.   

16 See Adler 1997, 318‐363; Hopf, 1998; Checkel 1999, 2001 

17 The US Marine Corps, Vision and Strategy 2025 document articulates this  quite well within a military context. 

18 For  example see Daniel Yergin  1977, 123; David Hallloway 1983. 

19 See Katz 1989, xii ‐xv. 

20 See Johnson 1998, 1999.   

21  See Goodman 2003, 3‐12; Herman 2004, 125‐126. For some of the earliest  examples see Katz 1989, 137‐164 and the role of social science in the Cold War. 

22 See Hopf 1998, 75. These three aspects of identity, made the concept more  manageable within international relations when examining the behaviours of  states. The same understanding is adopted in this study to provide a functional  approach to the identification of normative behaviours.   

23 Katzenstein, 1996. 

24 See Hopf 1998, 176‐178. Hopf was referring specifically to the state actor,  whereas I am referring to actors within a battlespace. 

25 See Klotz 1995, 19‐20; Katzenstein 1996,  33‐75 

26 EBAO calls for an expansion and exploitation of our knowledge base to support the planning, execution, and assessment of actions in a complex battlespace defined by a physical and cognitive domain.

27 See Rogers 1996, 22-23.

28 See Phister et al. 2004,1-2;Czerwinski 1996, 21-132;Owens 1995,35-39. 

29 See Czerwinski 2003, 114-115.

30 PMESII – Political, Military, Economic, Social, Information, Infrastructure domains of a battlespace and represents a system of systems approach. It can also be portrayed accurately as interacting social networks.

31 NATO Bi-Strategic Command Pre-Doctrinal Handbook, 2007, 5-3.

32 For generic understanding see Clark 2004, Ch.1; Herman 2004, 293-296; Mitchell 2002, 486. 

33 I am using the UK MOD Doc 1999, 1A‐2 definition.

34 For a good example of the comparative tech focus see Libicki & Johnson  1995, 48‐49.   

35 Military intelligence output is divided generically into basic and current  intelligence – current intelligence is situational and not referential in character. 

36 See Schoffner 1993, 31‐35. 

37 For example, ASCOPE in US Army Manual 2009. 

38 See Phsiter  2004, 2. Known as Intelligence Preparation of the Battlespace  (IPB), its purpose is to keep the commander aware of recent, current, and near  term events in the battlespace. 

39 Using SAB‐TR‐02‐01 2002 definition. 

40 See Mitchell 2002, 481‐485. 

41 See the ‘father’ of EBAO, Smith 2006, 195‐238; Smith 2005. 

42 See Holmes‐Eber & Kane 2009, 31‐35. 

43 This network model is an example of constructivism in action, where key  concepts such as identities and norms, or patterns of expected behavior (Hopf,  1998) are exploited in conjunction with predictions or recommendations of  physical actions, or COA production.

44 Taken from SAS 050 2007, 23.

45 See Clark 2004, 29. 

46 See Mitchell 2002, 480‐485; Heuer 2006, 47‐105. 

47 See Smith 2006, 149‐193.

48 Unfortunately actual targeting examples could not be cleared for an open forum at the time of writing.



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