Theory of an Emerging-State Actor : the ISIS Case

This paper proposes a new theory of non-state actors who engage in irregular warfare to seize territory and govern openly. The theory is examined in the historical case of the Islamic State of Iraq & Syria (ISIS) to answer “what is/was” the Islamic State? The paper offers several contributions. First is the proposal of a new theory on emerging-state actor that differs notably from traditional other non-state actors and insurgencies. The theory consists of both a causal loop diagram and key propositions. A detailed system dynamics simulation (E-SAM) was constructed to test the theory. The propositions of emerging-state actor theory are constructed as synthetic experiments within the simulation using the ISIS case and confirm evidence of emerging-state actor behavior. The propositions are tested within a range of contingencies to identify their applicability. The novelty of E-SAM as a simulation for irregular conflict is its ability to handle multiple forms of conflict including non-violent political grievance, terrorism, insurgencies and emerging-state actors. E-SAM can be loaded with scenarios to simulate non-state actors in different domains: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.


Introduction
The rise and staying power of the Islamic State of Iraq & Syria (ISIS) created enormous regional instability that survives after its territorial collapse.Although ISIS's predecessor Al-Queda in Iraq (AQI) presented a threat as a traditional insurgency, ISIS operates in an entirely different manner.Terming ISIS an insurgency is difficult because they operated openly.Likewise, explanations that ISIS is a messianic religious cult or some form of mafia discounts how ISIS governed and sought to establish civic institutions in territory it controlled.So what was ISIS?What strategies can contain or defeat it?Can the ISIS phenomena be replicated elsewhere?
This paper proposes a new theory of a non-state actor, called an emerging-state actor, and presents the dynamic hypothesis that ISIS is a case-study of this kind of non-state actor.Emerging-state actors operate in fundamentally different modes than other non-state actors like insurgents or terrorists and this difference helps explain the rapid growth of ISIS and why other insurgencies might shift to this mode of conflict in the future.The theory of emerging-state actors as it applies to ISIS is developed within the existing framework of non-state actors.A dynamic hypothesis of an emerging-state actor is then developed through a series of logical statements connected in a causalloop diagram.Experiments are conducted on the propositions of the dynamic hypothesis using a detailed system dynamics simulation called the Emerging-State Actor Model (E-SAM) (explained fully in Appendices) to build confidence in the theory.The paper finishes with a conclusion that summarizes the insights, discusses limitations, and identifies future opportunities for research with the emerging-state actor theory as well as the simulation model created for this effort.

Detailed Problem Description
In 2003 Al-Queda Iraq (AQI) emerged as a potent threat to the stability of Iraq.The strength of AQI peaked in 2006 before declining as the result of three circumstances: a troop surge of US Forces, a Sunni-Shia civil war that AQI helped spark, and the indigenous resistance to AQI growing out of the Anbar Awakening.In 2013 ISIS seized of Ar-Raqqah, a medium sized city in eastern Syria with an estimated 13,200 militants.By late 2014, ISIS had grown to between 50,000-80,000 militants strong, taken control of nearly thirty per cent of the territory in Syria and Iraq, and threatened regional stability.It took the combined intervention of over five different international forces, of which the US led-coalition was just one, plus the combined militaries and local militias of Syria and Iraq to remove ISIS from the territory it held.The rapid growth of ISIS and staying power represented a problem in the study of insurgencies and how to contain them.How did ISIS grow so quickly between 2013 and 2014?What made ISIS so difficult to confront?What would've happened had the foreign interventions not occurred?

Literature Review
Although the literature on insurgencies is extensive, in 2009 Kilcullen argued that Cartesian or reductionist quantitative analysis to model insurgencies may not be the best approach, and instead complexity theory and systems theory approaches may be more practical.There are only a handful of quantitative system dynamic efforts dealing with insurgencies or irregular warfare in the manner described by Kilcullen.An early multi-polar examination of conditions that give rise to internal violence in developing economies was conducted by Khalid Saeed in 1983.The paper analyzed how social and political factors determined long term growth.Instability in the form of dissidence and subversive activities were modeled, but not explicitly as a violent insurgency or with resources becoming controlled by the dissidents.[4] In 2010 Turnley et.al. specifically modeled an irregular warfare environment to provide a computational representation of the interdependence between kinetic and non-kinetic aspects of a battlefield.The model highlights the interaction of latent structure as it is affected by kinetic activity, but Turnley does not model the organization of the insurgency itself as a key factor in the dynamics of how it operates.[5] In 2011 Anderson used actual data from the Anglo-Irish War of 1919-1921 to model insurgency and counterinsurgency theories indicating potential gaps in the theory when compared to simulation results.However, the IRA was never able to seize and hold territory with this approach and may not best represent the dynamics of an actor like ISIS which seizes territory to the exclusion of all other actors.[6] In 2013 Saeed et.al. developed a generic structure to model political conflict which could include insurgencies.[7] The model, like Turnley, focuses on decision-making and choices of the population rather than the explicit structure of how an insurgency like ISIS might operate.
In 2014 Aamir presented a paper on modeling terrorist organizations using existing system dynamic models of business entities.However, except for Attacks & Agency the models Aamir used were from existing system dynamics literature on business models, built generically, rather than aiming to model the performance of any one insurgent group.[8] This paper seeks to build upon the work of this existing literature by proposing a dynamic hypothesis that ISIS represents a new form of insurgency created by an "emerging-state" actor.In this effort I will adopt Turnley's approach of using U.S. military definition of terms, the aspects of modeling ISIS as a firm or state from Aamir, and pay close attention to the causal mechanisms (financing, recruiting, gaining equipment) that allows ISIS to operate and achieve its goals missing from the theoretical structure of Anderson and the generic structure of Saeed.The crucial feedback loops between state and non-state actor discussed by Saeed are explicitly modeled.
My contribution to the literature in this paper is the theory of an emerging-state actor, that ISIS is such an actor and the testable propositions of what constitutes such an actor.I test the propositions of the theory in simulation experiments to see whether they are valid within the context of the model boundaries or not, and validate those boundaries.Finally, I have contributed a detailed simulation model in E-SAM that can simulate the performance of a wide variety of unconventional conflicts between state and non-state actors.E-SAM can be used either as a wargame by military planners or a research tool by analysts or academics.The model contains a combat simulator configurable by scenarios to represent different terrain and types of environments as well as starting conditions.[9] The model serves as a platform for conducting a portfolio of policy tests to understand the behavior of an emerging-state actor versus an insurgent non-state actor or clandestine terrorist network -but as well conduct policy tests on interventions against such actors. [1]

Hypothesis Development: What is ISIS?
Developing a hypothesis that ISIS was an emerging-state actor first requires identifying the existing perspectives on terrorism, insurgencies and irregular warfare then locating ISIS within this typology of non-state actors.Part of that effort involves making explicit the modeling boundaries and how the problem is being sliced.This section concludes with the proposed hypothesis of ISIS as an emerging state actor.[10] Existing terms often do not distinguish between tactics used by a non-state actor and threat to the state by a non-state actor.The two figures below, Figure 1 and Figure 2, both represent continuums along axes.Beginning with "tactics," a continuum of the methods of operations employed in furthering an agenda by non-state actors can be notionally established using terms and definitions from the U.S. Military.In Figure 2, at the left of the continuum, are non-state actors who seek to achieve their agenda through unconventional warfare defined as "…operating through or with an underground, auxiliary, and guerrilla force in a denied area."[11, p. 261]

Figure 1. Tactics Continuum
On the right side of the continuum are those non-state actors who further their agenda through a "…violent struggle among state and non-state actors for legitimacy and influence over the relevant population(s)," [11, p. 125] the key distinction being to what extent the non-state actors are operating in a clandestine or more open fashion and seeking legitimacy over the local population.The continuum ends at irregular warfare excluding conventional full-spectrum operations and nuclear war as being beyond the reach of non-state actors.

Unconventional Warfare
Irregular Warfare This was more a form of irregular than unconventional war.Because of this shift in approach and end goals, ISIS at this time was better located in the upper-right quadrant and deserving of a term representative of insurgencies that govern openly and no longer execute solely unconventional operations but embrace all aspects of irregular warfare.As ISIS set up courts of law, collected taxes, established government services, and enforced social norms the group clearly began operating as a "state-like" actor, and given its rise might be better termed "emerging-state" or "proto-state" actor.Indeed, the qualities of an "emerging-state" actor well qualify the upper right portion of the previously established quadrant.Locating ISIS in this space along with illustratively placing other non-state actor groups, the graph now appears as in Figure 4.

Figure 4. Illustrative Location of Non-State Actors by Segmentation
This structure now provides a shaping context for the discussion of "what is ISIS" and a point of alignment in the modeling effort: the amount of relevant population under some form of control by ISIS.From Turnley, two forms of control over a population are identified: control through coercive power and control through government via legitimacy.Coercive power results from the exercise of "coercion and reward" and is "particularistic as it is support for a specific action or specific person, not for an institution or a system of government."Coercive power is more resource intensive as it "requires the investment… to induce compliance whenever necessary.[6]" Legitimacy is a form of power that relies on the function of procedures that the governed considers fair established with credibility over time.Unlike coercive power used to ensure compliance, control by others is replaced by self-control, which socially is a much cheaper way to ensure social order."[5, pp. 38-40] Turnley illustrates the transitioning distribution of a population controlled through coercive power and governed through legitimacy with a diagram presented as Figure 5.  as the length of time in which all previous functions have also been successfully executed.Likewise, the length of time it takes to transition a population from control through Coercive Power to Legitimacy determines the overall resources required to govern that population.A middle-stage, lying between Coercion and Legitimacy, is identified from Hurd's research.In this model a third stage, "self-interest" or Calculated Legitimacy lies between Coercion and Legitimacy.The difference between Coercion and Calculated Legitimacy as described by Hurd: "is that an application of coercion leaves the coerced actor worse off than it was beforehand…whereas a selfinterest perspective sees the actor as better off than it would be taking any other available path." [13, p. 386] The in-between state more accurately captures some of the complex patronage relationships where out of purely self-interested ethnographic groups will temporarily align with the local power, but quickly remove that alignment if their interests diverge.In summary, by creating credible institutional procedures replicated over time provisioning both punishments and services any state-actor will affect the distribution of a target ethnographic group among Coerced, Calculated Legitimacy and Governed that indicates along a continuum the extent of external-threat vs. self-restraint that is necessary to achieve compliance of that population to the state.

Modeling Boundaries & Approach
Prior to creating a simulation model, the proposed theory to be tested must be developed into a strong logical argument.In system dynamics these logical structures are made visual and explicit with causal loop diagrams (CLD) that distill into to a key feedback loops the hypothesis of what is generating the proposed behavior.From this CLD, the detailed simulation model of hundreds of equations can be constructed.However, since models can never truly represent reality, boundary selection must be made explicitly clear.Reasonable boundaries for proposed hypothesis can be selected through a "slicing approach" to complex systems as advocated by Saeed in 1992.[14] In complex systems modes of behavior can exist in time, geography (both a geography of 'terrain' and a geography of 'things'), and simultaneous modes.In this paper the complex system will be sliced as depicted in Table 1.Additional commentary on these selections is provided in the Appendix B. Causal loop diagrams can demonstrate the different phases already identified: clandestine terror networks, insurgencies and emerging-state actors.All three phases operate within the same system, but the differences between them manifest in the theory of emerging-state actor behavior and performance.These differences can then be tested in the simulation model for validation against the hypothesis that ISIS is an emerging state actor.

Axes
This paper proposes that this cycle begins with a State Actor and the desire to credibly govern a specific ethnographic group.The higher that desire, the higher the legitimacy of the State Actor within that ethnographic group.This desire also exhibits a tolerance of civil reforms.This means when grievances do arise -they can be resolved through less-than-violent means.However, if a State Actor has a low desire to credibly govern, this decreases their legitimacy to the ethnographic group, increasing grievance, and the unwillingness to allow civil reforms leads over time to general uprising and resistance.This initial stage is depicted in Figure 7 below.which fund further military actions.This is when a clandestine terror stage morphs into an insurgency stage of conflict.

Figure 9. Insurgency Stage of Conflict
The logic of an insurgent is to leverage the local legitimate grievances of an ethnographic group and leverage that into finances and manpower to conduct violence against the state.This adds two more positive feedback loops to the existing.As local grievances increase, so do militants, and if local grievances were to decrease, militants and their actions would also decrease.This is illustrative of the importance of resolving local grievances, through political reform and changing the desire of the State to credibly govern, as a sustained approach to ending an insurgency over time.[3,pp.6-7 location 173-199] These could be criminal activities targeting populations that are not aligned with the insurgents such as ransoms, extortion, reselling of stolen property, looting, and selling of bloodantiquities (stolen historical artifacts).Criminal activities also include activities which are illegal globally but may be tolerated locally such as the illegal drug trade.Finally, criminal revenues include informal taxation schemas that bear more resemblance to extortion than a formal state levied tax.These funds increase non-state actor insurgent's finances, allowing them to support and pay more Combatants.Logically, a sustained reduction in local grievances through reconciliation, ability to gain finances, or reduction of combatants through military action all hold the potential to reduce the reinforcing feedback effect that powers the classic non-state actor insurgent, especially when applied in combination.The means of these reductions are accessible both to the State and to a lesser degree the local ethnography.
The first difference with the emerging state actor CLD is the input of non-local grievances that bring foreign recruits to an area.These militants may be aligned to the local grievances at first, but a reduction in local grievances will not result in a reduction of foreign intervention since those grievances are non-local.The second difference is that military actions in this model are designed not only to terrify or intimidate populations, but also to seize territory.This territory then enables an additional feedback loop of "territorial revenues" from land-intensive resources to be activated.Control of territory allows a non-state actor to control the resource extractions that occur in that territory.These territorial revenues require coordination of workers and leveraging infrastructure, and they are difficult to secure when an insurgency operates in a classical clandestine manner.In Afghanistan the Taliban took advantage of opium farming, while in Nigeria Boko Haram helps fund itself through oil while in Columbia the Revolutionary Armed Forces of Columbia (FARC) exploited the production of cocaine.For ISIS, the territorial revenue is oil located in the territories they seize.These additional financial inputs produced from lucrative, fungible, globalized trade charge the reinforcing feedback loop that runs through finances to obtain more militants, conduct more military actions and thus gain more territory.
Seizing territory opens another powerful feedback loop of enabling non-state actors to begin governing the population.This creates the processes by which coercive power shift to calculated legitimacy and legitimate governing power.Populations controlled through legitimacy are less resource intensive to control, since the population "self-controls" and also allows taxation of normal commerce and individuals.The shift to Legitimacy also feeds back on itself.The more people governed through Legitimacy, the easier finances are collected through taxation, which fund local governance mechanisms.These local governance mechanisms can provide the services that only a sovereign state actor can provide: law enforcement, judicial proceedings, building infrastructure, social services, and other government services that may have been lacking in the area.
When we add these aspect to our existing CLD structure, three loops emerge: seizure of territory, control of population through legitimacy, and foreign recruiting by playing on global grievances.The larger CLD is depicted in Figure 10.

Figure 10. CLD of an Emerging-State Actor
The emerging state actor theory to this point can be summarized as: 1.A failure of governance by the state-actor and inability to tolerate civil reforms decreases legitimacy, increases grievance and leads to general uprising and resistance.
2. This resistance manifests first in the form of clandestine terrorism which increases the perception of instability, further decreasing the legitimacy of the state.Likewise, violent acts reduce incentives of the State Actor to credibly govern the ethnographic group from within which these actions emerge.
3. Local grievances bring militants and a non-state actor either emerges or is drawn into conflict.4. The non-state actor uses militants and finances to conduct military actions.
5. As the non-state actor gains controlled population begins extracting coercive revenues through criminal activities and recruiting locally from within the controlled population.
6. Within its territory, the non-state actor attempts to monopolize the use of force, taxation, control of movement, and regulation of the economy.By operating in a sovereign manner, the nonstate actor shifts to an emerging state actor.
7. Coercive revenues & territorial revenues are used to finance governing mechanisms which can begin building legitimacy to shift the controlled population into a governed population.
8. As the emerging-state actor gains a governed population, it also gains taxation revenue and increases its draw of non-local foreign recruits by propagandizing its non-local grievances, which may or may not align to local grievances.
9. The loops complete into a positive feedback loop of exponential growth.More militants mean more military actions, which means more territory and access to controlled populations, which can begin to be governed, fueling finances, which fund more militants and military actions.
The shift from a classic non-state actor insurgency to an emerging-state actor, in this sequence, begins at step 6 and completes in step 7.This can be described in another way.For a non-state actor to become an emerging-state actor it must at some point: A. Control territory to the exclusion of all other state actors.
B. Seek to govern that territory in an open manner to build legitimacy.
In the case of ISIS's predecessor AQI, the group was able to reach step 5 and partially step 6.Even though AQI certainly influenced a population and extracted criminal revenues from them, AQI was never able to meet the two criteria above to complete the transition from insurgency to emergingstate actor.In this formulation, an emerging-state actor is self perpetuating, a foregone conclusion once militants enter the system.To complete the CLD in Figure 11, balancing loops are added representative of various limits to growth.

Figure 11. Emerging-State Actor with Balancing Loops
These are endogenous limits on the emerging-state actor which even absent external pressure, can and will engage to slow down or reverse the growth over time.The "Expansion Requires More Garrison Forces" loop activates as an emerging-state actor controls more population -requiring more forces to garrison than population to prevent uprisings against their rule.This reduces the number of combatants available to gain more territory.Furthermore, the force ratios for garrisoning a population controlled through coercive power are higher, ranging from 8:1 to as high as 55:1 than the ratios necessary to police a population, ~2.8:1, governed through legitimacy.This loop can also act in the same way the "Failure to Govern" loop does for the State Actor, starting a general uprising against the emerging-state actor.Another negative feedback loop in the emerging-state actor theory is "Descent into Factions."ISIS owes its existence to the activation of this loop within Al-Queda as a previous incarnation split from the global terrorist network in 2013.A third negative feedback loop, the "Dynastic Cycle" loop begins with the corruption and abuse of arbitrary power available to a state, similar to Katouzian's theory of arbitrary state and society.[15, p. 7] These abuses erode governing by legitimacy, feeding both the Uprising & Resistance loop and the Descent into Factions loop.However, Descent into Factions and the Dynastic Cycle loops have significant delay functions and therefore may develop well after an emerging-state actor has established itself.As modeled by Langarudi, the Katouzian dynastic cycle can take decades to manifest.[15,pp.10-16] The Afghanistan Taliban, as an emerging-state actor, maintained its governing legitimacy despite widespread abuses until the post-9/11 U.S. invasion in 2001.The attached E-SAM has all these balancing loops modeled numerically so the conditions for their activation can be examined.
The emerging-state actor theory can help explain not only the rise of ISIS in 2013, but the collapse of AQI forces in 2006-2007.The inability of AQI to establish institutions and processes with which to govern legitimately meant it relied only on coercive and often abusive power.This activated the "Expansion Requires More Garrison Forces" negative feedback loop from local fighters.Beginning in the Anbar Awakening of 2006 that was followed soon thereafter with an U.S. troop surge AQI faced local-opposition fighters.AQI as a classical insurgent could not sustain itself in that environment, perhaps a lesson learned by its members and carried forward into the new incarnation of ISIS.Based on the previous theoretical development, I propose the following dynamic hypothesis: the Islamic State (ISIS) is an emerging-state actor, which uses methods of irregular warfare to capture territory to influence populations ("coercive power"), which it then attempts to govern in furtherance of its objective to become a functioning state ("legitimate power").I recognize that although the term for this category might be new in this application, the behavior and model is not, as other actors, such as the Taliban in Afghanistan and Hezbollah in Lebanon have taken this route as indicated by the segmentation.

Hypothesis that ISIS is an Emerging State Actor
To test the hypothesis, I created a simulation model of sufficient detail to test the propositions of the emerging-state actor theory and the hypothesis that ISIS is an emerging-state actor.The model is created in two sections: a strategic architecture of both the state government named the "Green Actor" and ISIS, named the "Red Actor."The strategic architecture identifies the resources and capabilities that determine performance at any point in time.The second section is a World Model within which these two Actors compete against one another over control of a variety of ethnographic groups and with varying of foreign intervention.This strategy-dynamics approach to modeling recognizes that these resources accumulate or deplete driven by flow-rates and the changes in the resource.[16] Sub-systems representing the constants, parameters, information flow, and leadership decisions, behaviors and side-choosing of ethnographic groups, as well as the influence of other resource levels, all combine to affect the rates of change.Reinforcing and balancing feedback interactions between these resources can be used to explain the dynamics of strategic performance.This aggregate strategic architecture is depicted in Figure 12.

Figure 12. ISIS Strategic Architecture
The strategic architecture represents the resources, capabilities, and skills of each the Green and Red Actor.The world model defines the "environment" within which subsystems interact with local conditions (where recruits and resources are located relative to what is controlled), competitors (who will resist expansion and what means are used), and even internal dynamics (how effectively revenue and expenses are managed) interact with the subsystems.Two baseline scenarios were run in the simulation.Both seek to replicate the conditions in Syria and Iraq beginning in 2010, the grievances of the Arab Suuni's that led to the rise and expansion of ISIS.The Baseline Historical scenario then includes the significant foreign interventions that   In the Baseline Historical ISIS (Red Actor) is defeated from a combination of measures.The growth of its population requires an increasing amount of Garrison troops just as foreign intervention begins increasing and fewer Foreign Combatants are arriving.In the Baseline without Intervention ISIS reaches an "outer envelope" of expansion at about ~60% of available territory.This limit is caused by three key factors.First the Green Actor opposition to ISIS becomes heaviest as they reach the strongly defended cities of Aleppo, Baghdad, Kirkuk etc.Second, the territories on which ISIS must fight to gain that next incremental amount of territory consists of densely packed urban areas that are not as favorable to its style of fighting.Third, the ethnographic makeup of the population in the territory being taken shifts away from ISIS's favor, reducing their ability to recruit local militants.What was once a 9:1 ratio of local to foreign militants drops to almost 1:1.This activates the Resistance & Uprising limit to growth negative loop identified in the CLD.Even though by converting the populations they have controlled to being governed over time, reducing the rate at which opposition fighters accumulate, the aggregate external and internal threats mean "just staying still" for ISIS isn't sufficient.The emerging-state actor must continue recruiting locally and from abroad to hold onto what they have.ISIS has reached its limit to growth -at least for the remainder of the simulation duration.

Experimentation to Test the Hypothesis
Having formed a logical construct of the hypothesis and its simulated baseline, it is worth returning to the proposed dynamic hypothesis: the Islamic State (ISIS) is an emerging-state actor which is using methods of irregular warfare to capture territory in order to influence populations ("coercive power") which it then attempts to govern in furtherance of its objective to become a functioning state ("legitimate power").This hypothesis can be tested against the simulation model.Six propositions emerge from the dynamic hypothesis.Propositions 1-5 are formulated as experiments where a simulation is run ceteris paribus with the only change being the stated formulation change to the subject proposition.Significantly worse experimental performance from baseline indicates potential validity of the proposition within the boundaries of the model, eg.without this element ISIS would've performed much worse.Proposition 6 is an experiment comparing a classical insurgency performance against the baseline of ISIS.Where appropriate a limited range of contingencies are tested to identify the boundaries of this validity, such as the value of the underlying resource or the time the transition to legitimacy may take.The list of experiments and formulation changes is described in Table 2.

Change Summary Command Script Formulation
Experiment 1: ISIS must take and control territory.
Remove ability to gain territory because of combat.
Set Experiments 3a-3d confirms that using government services and credible institutional procedures is important to maximize growth.But as with territorial resources, there are contingencies.When ISIS is willing to credibly govern at 75% or even 50% they perform reasonably well in terms of maximum expansion and combatants.However, at below 50% desire to credibly govern ISIS's performance significantly drops.Part of the reason they still have so many Combatants at max is that their territorial expansion is so limited -they have not provoked a major response from Iraq or Syria.Like an insurgency in a remote region that the government leaves alone for the most part.Experiments 4 & 5 confirm that both local recruiting and foreign recruiting are essential.Although it may not be surprising that local recruiting is essential, the significant difference foreign recruiting makes in comparing Proposition 5 performance to the Baseline is noteworthy.
The final experiment, simulating a "classical insurgency" (EXP6 Historical) removes two key elements of emerging-state theory, the seizure of territory and open governance.It then compares ISIS-as-an-insurgency versus ISIS as emerging-state actor (Baseline Historical) in Figure 16.In both simulations ISIS begins gaining combatants quickly but ISIS as an insurgency-quickly stalls out and begins a general decline.As it never seizes territory the "insurgency" does not present an obvious target for military offensives as the emerging-state actor ISIS does.It still contains a great deal of lethal capacity as seen in the Total Civilians Killed all Ethnographies, but the key chart is in the bottom right -which charts the Calculated Legitimacy an Actor presents to ethnographies.Whereas ISIS acting in the fashion of an emerging-actor can generate this form of strategic sidechoosing at least among Sunni Arabs, ISIS as an insurgency never gains even this limited form of legitimacy from the population.The insurgency ISIS dwindles away to end up in similar straits as the emerging-state actor version, but never having obtained the massive success and ability to create a worldwide brand.It is possible that AQI suffered a scenario such as this in 2006 when it rapidly gained coercive control of a population of nearly one million civilians but was unable to openly seize territory in its area of influence nor transition to an open system of governance due to the requirements to remain clandestine due to the presence of US forces.AQI also showed little interest in even a show of providing services.All lessons learned perhaps by its successor ISIS.

Conclusion
In this paper I used the growth and staying power of ISIS in Iraq & Syria even against combined domestic and international militaries to present the theory of an emerging-state actor.Confidence in the theory of an emerging-state actor and its key propositions was gained, though the theory remains unproven, through a limited initial simulation tests conducted in this paper.Calling upon global rather than local grievances the emerging-state actor draws foreign fighters and seizes territory upon which it exercises sovereign control and begins openly governing.The use of governing mechanisms shifts the population from being controlled by coercive power to being governed by legitimacy, freeing up garrison troops to continue expansion and territorial gain.My dynamic hypothesis that prior to its defeat at the hands of a combined multi-national and domestic militaries the Islamic State in Iraq & Syria operated as emerging-state actor using the means of

Figure 7 .
Figure 7. Conditions for Civil Conflict

Figure 15 .
Figure 15.Dashboard of Performance Both Scenarios

Table 1 .
Proposed Slicing of Simulation Model

6. Hypothesis Design through Causal Loop Analysis Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 13 March 2018 doi:10.20944/preprints201803.0073.v2 Peer
[7]viewed version available at Systems 2018, 6, 16; doi:10.3390/systems6020016Existingcausalloopstructureforinsurgencies in the literature is limited as discussed previously.Because the models used by Aamir were already extant, he did not provide an integrated causal loop structure.[8,p.8]Intheir'Farmers,Bandits,andSoldiers'modelSaeedet.al.likewise did not depict a causal loop diagram.[7]Only in Anderson's paper was a causal loop diagram of his theoretical construct created, as depicted in Figure6.[6,p.8]Figure6.Anderson COIN CLDAnderson's model is limited in its utility in examining ISIS and other emerging state actors using irregular warfare.This is because Anderson's model is built on the premise that insurgents are fighting a "classic" insurgency following O'Neill's definition that largely confines insurgents to operating in a guerrilla manner, e.g."raids, ambushes, bombings, etc."[6, p. 3] This is consistent with the Joint Forces definition of unconventional warfare of "operating through or with an underground, auxiliary, and guerrilla force in a denied area."[11,p.261]This does not comport with behavior that is state-like, or defined above as emerging-state behavior.

Table 2 .
Proposition & ExperimentsThese tests are made both against the Baseline Historical and Baseline without Intervention.The results of these tests and final values against four measures compared to the two baseline scenarios are summarized in Table3.The evidence for Experiment 1 & 2a indicates that an emerging-state actor must take both territory and have some valuable resource upon that territory to fund expansion beyond ~20,000 Total Combatants, the upper size of most insurgencies.However, the contingency tests of 2b & 2c indicate that the resource need not be all that valuable relative to the expenses of maintaining the emerging-state actor.ISIS still grows just as strongly when black market oil sells for $22bbl and $11bbl respectively vs. $45bbl.The reason why is the pathdependency of the positive feedback loops identified in emerging-state actor systems above in Figure11.Once ISIS has reached a tipping point of sufficient population in either Calculated Legitimacy or Governed, the territorial based resource revenues become less important as they can rely on population-based taxation.