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NOTES:Just finished highlighting, cut the last two cards nextCollin, I merged your complexity work in here, change anything you likeNeed answers to and overviews next

Look to UTNIF2012 SimCity for more defense and extensions, also Michigans predictions KI want to combine this with existential risk bad stuff and our big impacts framework

The alternative is still up in the air, probably localism so we only have one advocacyRead Heiss 9 from localism fileUnsure how util works with this, or if its just incompatible

Sub-point a) Plan Meets Advantage

Evaluate the future locked in by the affirmatives- they frame each of theirimpact scenarios as Rube Goldbergsfinal event- as if dropping the marblein the machine will guarantee a desirable outcome. The race car track, thedominos, the isolated causations are all part of their link chain and so we allpretend that the 1AC already knows exactly how those cards will be played,but these are the systemic effects that can take the marble off course. Thisis the folly of status quo policymaking- risk cannot be seen as a flash ofinstability to be predicted and controlled the instability is inherent andconstant enthropy.Mangalagiu, 11[Diana Mangalagiu, Prof of Strategy at Smith School of Enterprise and Environment-University of OxfordRisk and resilience in times of globalization An emerging research program for Global Systems Science: Assessing the state ofthe art, 10/4/11,http://www.gsdp.eu/ //AC]The recent financial crisishighlights the challenges of, and the potential of catastrophic impacts from the failure toaddress global, systemic and long term risks. The crisis was neither prevented, nor effectively anticipated,by the hosts of expertsin risks and futures employed by the industry. Despite the sophisticated strategicplanningand risk management approaches adopted byindividual banks and regulators, the lack ofreflexivity in anticipatory knowledge processes, coupled with overconfidencein calculable andmanageable risks, contributed tothe denial, dismissal and ignorance of new forms ofvulnerability and, in particular,systemic risk(Wilkinson and Ramirez, 2010; Selsky et al, 2008). It also highlights that risk management approaches thatfocus on stress testing the parts (e.g. individual banks, companies, governments, cities etc.) of a system are no longer enough.The notion of systemic risk and practices of systemic risk management are being influenced by multiple traditions in scholarship(e.g. complexity science, resilience concepts), contesting theories of risk (e.g. social, mathematical, psychological) and thepractical experiences harvested through professional bodies focused on risk management in banking and financial services,environmental management, urban planning, insurance and reinsurance, etc. In this WP, we focus on identifying and comparing

how risk management, the search for resilience and their respective approaches to strategic foresight and anticipatoryknowledge might be better related and more effectively practiced in a range of different contexts such as at the organizational,sectoral-, national- and international-systems levels. Our first year deliverable is the state of the art concerning risk, systemic

risk and resilience in times of globalization. The conventional riskmanagement paradigm assumes that alossevent isrelatively limited, specificand isolated andwith proper analysis can be anticipated and thus,avoidedor contained and mitigated. In the conventional risk management paradigm the default is to forecast the future - or aprobabilistic analysis i.e. the assumption that the future is knowable. Formal interest in risk and risk management originatesfrom the fields of engineering and epidemiology in the 20th century (Kates & Kasperson, 1983) and from interdisciplinary studiesof natural hazards (White & Haas, 1975). Since then the social sciences created significant independent contributions to riskresearch (Golding, 1992). Krimsky (1992) summarized the roles theory can take in risk analysis, which are quantitative laws,taxonomic frameworks, models, functionalist explanations, cognitive explanations, or analogical models and interpretive
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representations. Beck (1992, 1994) and Giddens (1991, 1999) pointed to the elaborate role risk plays in the macro organizational

levels of modern society. Societies are self-reflective in the sense that they seek to govern theirown behavior to avoid catastrophic consequences. As such, the concept of risk is also politically relevant(Lupton, 1999). Providing an overview of the different perspectives on risk research, Renn (1992) distinguishes the technicalperspective on risk (expected or modeled value, probabilistic risk assessment), economic perspectives (risk-benefit analysis),psychological perspectives (psychometric and cognitive analyses), sociological perspectives (plurality of approaches), andcultural perspectives (grid-group analysis).

CONTINUEDAnother stream of literature focuses on the perception and social construction of systemic risk. First, studies look into theparadoxical situation of policy makers to stimulate innovation but also to regulate risks arising from accelerating innovation. Thisargument is put forward to support post-normal science and decision-making as the appropriate approach to modern (systemic)

risk management situations. Then, risk perception biases for catastrophic risk have been examinedandultimately, the classic reductionist treatmentof risk management was held responsible for risingoccupation with risk in society. Public actors play a paradoxical role in the relationshipbetween risk and innovation,between the interests of the public and private actors (Ravetz, 2003). Ravetz seesaccelerating innovation as a necessary tool for private companies to compete in a globalizing knowledge economy and the role

of the public to ensure an environment in which speedy innovation can take place. On the other hand, public actors needto ensure the safety of new technologies and innovation acting as an agent for theircitizens, remaining the source of public trust and safety provider for citizens. Besides thisparadoxical role, technological innovation threatens the global environmental system; so,

how much technological innovation is desirable and how much risk in it acceptable?Ravetz argues that finding appropriate answers to this question can only be found in apolicy-making process that involves the public in dialogues about scientific findings and bydisclosing ambiguities in scientific finding, thus embracing policy principles for a post-normal world of science.CONTINUEDAn initial review of the literatures relating to resilience reveals a fragmented field. In social ecology, resilience is concerned withthe longer-term survival and functioning of ecosystems species, populations and services in a changing or fluctuating operatingenvironment. The social ecology approach introduced by Holling (1973) argues ecological systems are non-deterministic becauseof inherent complexity. characterizes the ecosystem as complex set of elements and parts existing in dynamic interrelationshipand interdependency. The key contribution of the ecological view of resilience is to provide a focus on the systemic nature of theproblems and on the longer-term demands on policy and management. It emphasizes the need to keep options open, whileappreciating heterogeneity and keeping a broader than local view organization this is in contrast to dominant managementapproaches which are concerned with compartmentalizing issues, limiting change to the margins and views of the future rooted

in attempt to preserve the present. The critical distinction is that between resilience and stability.The stability/equilibrium paradigm approaches the future with the aim of strengtheningthe status quo by making the present system resilient to changeand aiming to achieve stabilityand constancy. In the management literature, the focus when using the resilience concept is on the persistence and survival ofindividual businesses and institutions in face of change. A bulk of the management literature on organizations focuses on thestrategies for individual businesses to be resilient to change -- on innovation, experimentation and leadership to ensure survivaland growth of a specific institution/business -- however the ecosystem perspective requires us to think about the health and ofthe forest and the services its provides rather than the role of individual species! What are the sources of resilience in the system

and or an organization? The process of increasing resilience is different from optimizationandimproving system performance in existing conditions what organizational characteristics build resilience. Successful adaptationrequires for individual organizations, agents and businesses to continue to full fill their own goal and function but must alsoinclude measures of promoting adaptive capacity of the system. Despite the richness in conceptual thinking underpinning theconcept of resilience, there is limited evidence of how groups, organizations are societies are translating the notion of resilience

into practice. The constructivist tradition in social theory argues that social response is non-deterministic because of plural perception and the negotiations of values, cultures,

choices and epistemologies. The managers are part of the system that is being managedand define the system and its characteristics in different ways. Understanding the loss,creation and maintenance of resilience through the process of co-discovery scientists,policy makers, practitioners, stakeholders and citizens is at the heart of building thecapacity to deal with whatever the future might bring.Anecdotal evidence suggests that some societiesare organizing for resilience. For example, both the governments of Canada and Singapore have resilience as the goal of theirnational strategic plans. There is a nascent literature emerging, as yet unmapped, on operationalizing resilience beyond theorganizational level. For example, in an approach to adapting an urban delta to uncertain climate change, Wardekkar et al.(2009) identify five options for resilience: (1) homeostasis: incorporation of feedback loops; (2) omnivory: having severaldifferent ways of fulfilling needs; (3) flatness: preventing a system from becoming too top heavy enables more effective


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localized responses, self-reliance and self-organization; (4) buffering: the ability to absorb disturbances to a certain extent and

(5) redundancy: having multiple options routes, supply chains, etc so that if one fails, others can be used. Theresilience frame opens the opportunity to think in terms of nonlinear and non-deterministic futures and, in doing so, to displace practices in probable futures withplausible and preferable futures. The resilience frame also invites attention to realizing transformation, rather thanfuture proofing of established structures, identities and values. It invites consideration of the

uncertainty as irreducible and inherent, going beyond the lack of knowledge andencompassing ambiguity and ignorance.

Black Swans events that have major effects and are yet unpredictable are ignored by the affirmatives. They ignore the intuition of theunpredictable events that we experience every day and that we haveempirically observed in history.Hansson, 5[Sven Ove; Professor- Department of Philosophy and the History of Technologyat the Royal Institute of Technology in Stockholm, Sweden; The Epistemology ofTechnological Risk Techn: Research in Philosophy and Technology, Volume 9, Winter 2005http://scholar.lib.vt.edu/ejournals/SPT/v9n2/hansson.html //AC]

We therefore need criteria to determine when the possibility of unknown dangersshould be taken seriously andwhen it can be neglected. This problem cannot be solved with probability calculusor other exactmathematical methods. The best that we can hope for is a set of informal criteria that can beused to support intuitive judgment.The following list of four criteria has been proposed for this purpose.(Hansson 1996) 1. Asymmetry of uncertainty: Possibly, a decision to build a second bridge betweenSweden and Denmark will lead through some unforeseeable causal chain to a nuclear war.Possibly, it is the other way around so that a decision not to build such a bridge will leadto a nuclear war.We have no reason why one or the other of these two causal chainsshould be more probable, or otherwise more worthy of our attention, than the other. On the other hand, theintroduction of a new species of earthworm is connected with much more uncertainty than the option not to introduce the new

species. Such asymmetry is a necessary but insufficient condition fortaking the issue of unknowndangersinto serious consideration. 2. Novelty: Unknown dangers come mainly from new and untested phenomena. Theemission of a new substance into the stratosphere constitutes a qualitative novelty, whereas the construction of a new bridgedoes not. An interesting example of the novelty factor can be found in particle physics. Before new and more powerful particleaccelerators have been built, physicists have sometimes feared that the new levels of energy might generate a new phase ofmatter that accretes every atom of the earth. The decision to regard these and similar fears as groundless has been based onobservations showing that the earth is already under constant bombardment from outer space of particles with the same or

higher energies. (Ruthen 1993) 3. Spatial and temporal limitations: If the effects of a proposed measure areknown to be limited in space or time, then these limitations reduce the urgency of thepossible unknown effects associated with the measure. The absence of such limitationscontributes to the severity of many ecological problems, such as global emissions and thespread of chemically stable pesticides.4. Interference with complex systems in balance: Complexsystems such as ecosystems and the atmospheric system are known to have reached sometype of balance, which may be impossible to restore after a major disturbance. Due tothis irreversibility, uncontrolled interference with such systems is connected with a highdegree of uncertainty.(Arguably, the same can be said of uncontrolled interference with economic systems; this is anargument for piecemeal rather than drastic economic reforms.) It might be argued that we do not know that thesesystems can resist even minor perturbations. If causation is chaotic, then for all that weknow, a minor modification of the liturgy of the Church of England may trigger a majorecological disaster in Africa. If we assume that all cause-effect relationships are chaotic,then the very idea of planningand taking precautions seems to lose its meaning. However,such aworld-view would leave us entirely without guidance, even in situations when weconsider ourselves well-informed. Fortunately, experience does not bear out this pessimistic worldview.Accumulated experienceand theoretical reflection stronglyindicate that certain types of influences
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on ecological systems can be withstood, whereas others cannot. The same applies totechnological, economic, social, and political systems, although our knowledge about their resiliencetowards various disturbances has not been sufficiently systematized.


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Sub-Point B) Collapsability

The 1AC addresses only a narrow field of possibilities determined by asupposedly predictable and exclusive link chain. They offer one plausiblescenario, but without a holistic analysis of the systemic problems inherent

in the status quo, they cannot prove that their particular link chain is themost probable of all the possibilities. Systemic effects can mutate theaffirmatives link chain because they evaluate it with tunnel vision. Thismakes voting aff inherently dangerous because it is unpredictable.Ramalingam, 11[Ben Ramalingam -Senior Research Associate at the Overseas Development Institute Theglobalization of vulnerability http://aidontheedge.info/2011/01/11/the-globalisation-of-vulnerability/ //AC]in the face of the global financial crisis a number of developing countries have proven to be remarkably resilient if judgedpurely in terms of economic growth. At the same time, it appears that the burden of coping has been borne disproportionately by

poor and vulnerable people. This reality is poorly understood (emphases added) In fact, much work on vulnerability hasbeen traditionally undertaken in disciplinary silosin highly specialised ways which are often inisolation from each other. Environmental vulnerability is assessed by the climatologists, nutritional vulnerability bythe food security experts, market vulnerability by the economists, disease vector vulnerability by epidemiologists, and so on.

The precise nature of vulnerability is often also heavily debated, leading to differenceswithin the silos. The gap between this stove-piped understanding and multi-facetedreality becomes heightened when one considersthe number of ongoing global crises. Thefinancial crisisis just one of a number of global trends (that we currently know about) which are interacting and impactingon the lives of poor and vulnerable people. To take another example, the 2010 World Disasters Report focused on

urbanisation, and found that a high proportion of this urban growth is in cities at risk from the increased frequency andintensity of extreme weather events and storm surges that climate changeis bringing or is likely to bring. Along similarlines, the global food system is showing signs of strain once again. Work done during the last upswing in prices in 2008 suggestedthat a key requirement was better monitoring and anticipation of future bubbles. Unfortunately anticipation has not led topreventative action. All the signs are that environmental disasters - driven by climate change - and a growing speculative bubblein commodities driven partly by changing investor patterns in the wake of the financial crisis - are pushing the world into a new

foodprice crisis.In the face of these trends and shocks, there is a slowly growing recognition that vulnerability itselfhas become globalised. Interestingly this insight has not come from within the aid sector but from organisations such asthe World Economic Forum, whose Global Risk Report 2010 shows that like the world economy vulnerabilities are now tightly

interconnected. Global shocks and stresses have multiple, unpredictable effects andincreasingly demandbut do not always trigger diverse responses at the local level. As recent research indicates,employing language which Aid on the Edge regulars will recognise: Cause and effect in global systems isdistinctly nonlinear. Inputs and outputs may not be proportional: a cause with ever-so-slightly different parameters thanthe previous instance might result in a wildly different effect. Additionally, systems and their component sub-systemsinteract to produce feedback loops thatcan either amplify or stabilize resulting effects. Feedbacks blur theline of what is cause and what is effect. The global system is characterised by varioussizes and degrees of complexitycombined into a tangled and heaving mass of interdependent actions. Despitethese shifts in the nature of vulnerability, international aid policy and practice are stilldominated by narrow, parochial approaches.Take for examplethe findings ofa reporton chronicvulnerability in Africa which found thatmuch of the analysis undertaken by international agencies did notexamine root causes and tended to divide vulnerability into immediate and structural

issues. The agencies then focused their efforts on the immediate issues, allowing the structural issues to be largely ignored. By contrast, the reality of vulnerabilityfor most poor people was found to be complex andnuanced vulnerability can be influenced by gender, ethnic group and generation issues, and by contemporary and historicalsocial processes that are often not analysed and not explained. (emphasis added) It would seem that it is only after things goseriously wrong that the inter-relationships between the key drivers of vulnerability become of importance to internationalagencies. To cite one prominent and very current example, the densely urban population in Port-Au-Prince was up until January2010 experiencing high levels of vulnerability and multiple climactic shocks. It was only after the 12 January earthquake that aidagencies became sensitive to this interconnected reality, by which time it was already too late for many in Haitian population. Asone satirical headline put it at the time: Massive earthquake reveals poor country called Haiti to the world.
http://aidontheedge.info/2011/01/11/the-globalisation-of-vulnerability/http://www.ifrc.org/Docs/pubs/disasters/wdr2010/WDR2010-full.pdfhttp://www.srfood.org/images/stories/pdf/otherdocuments/20102309_briefing_note_02_en.pdfhttp://www.weforum.org/pdf/globalrisk/globalrisks2010.pdfhttp://www.weforum.org/pdf/globalrisk/globalrisks2010.pdfhttp://www.srfood.org/images/stories/pdf/otherdocuments/20102309_briefing_note_02_en.pdfhttp://www.ifrc.org/Docs/pubs/disasters/wdr2010/WDR2010-full.pdfhttp://aidontheedge.info/2011/01/11/the-globalisation-of-vulnerability/


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Complexity is an inevitable byproduct of adaptation policy. Moderatepolicies only make small changes to variables but these same variables aresubject to the small initial changes that create massive unpredictableeffects later on that is guaranteed by the definition of complexity systemssuch as ecological, meteorological and economic systems. We only become

less able to manage complexity as we try to ignore its systemic risks. Thus,even the slightest increase in complexity pushes us closer to anunpredictable existential brink.Tamming and Petrov, 9[Chaos and Order: A Breakpoint for the Global Monetary System, Financial SenseEditorials, http://www.financialsensearchive.com/editorials/petrov/2009/0112.html, 10/12/12//CC]Let's take a look at history. The Roman Empire was in steadily in decline for a couple of centuries it wasa nation of consumers, ran significant fiscal and trade deficits, a corrupt senate taxed and lootedthe people, and the imperial military was overstreched just like modern-day America.Its economic decline andweakness was challenged by various barbarian tribes eager for a big slice of the Roman pie. The empire had to eitherrestructure its economy and military or face defeat. It ended defeated and destroyed.Much later, thefeudal age collapsed from its own internal contradictions,but humanity did not return to the Stone Age; insteadits collapse gave birth to a qualitatively different economic system known today as capitalism, gave

birth of modern banking in Italy, and revived science, culture, and art during the Renaissance. More recently, at thebeginning of World War II, Japan was at peace, but nevertheless prepared for war. The Japanese economy waschoking under the ever dwindling supplies of oil that were vital for the development of its military.The critical point was reached when the Americans cur off a vital source of oil supply in 1941. Without oil,Japan had literally two optionseither suffer economically and abandon militarization or strike back and declare war.The fateful decision was to strike Pearl Harbour and the rest is history.We can similarly view thedevelopment of the economic and political system. As complexity rises and the current institutional andregulatory framework cannot cope with internal disorder, the breakpoint is typically reached withthe eruption of an economic crisis; this usually leads to social chaos, revolution, social andeconomic re-engineering, and qualitative jumps in development. The crisis causes either the system tocollapse or brings about progress. Crisis should bring hope, like the crisis in Zimbabwe today, butunfortunately the reality is not that simplecrises cause an uncountable suffering and death, yetthe outcome is far from clear.With rising social confusion and system entropy, the system becomes

increasingly uncertain and unpredictable. It is quite unclear which way it will swing.


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EXTENSIONS

Moderate policymaking is no longer sufficient for addressing these systemicimpacts- thatsis an internal link to dedev DA.

Wilkinson, 12[Cathy Wilkinson, urban spatial planning at Stockholm Resilience Centre, Stockholm University, Social-ecological resilience: Insights and issues for planning theory Planning TheoryMay 2012 vol. 11 no. 2 148-169 //AC]In the USA, two Long Term Ecological Research Network urban projects, in Baltimore and Phoenix, are grappling with how tomake analysable a linked social-ecological system (SES). The difficulty of establishing a strong cross -disciplinary theoreticalbasis or research agenda for coupling nature and human systems is recognized by scholars involved in this project (Redman etal., 2004) who acknowledge that standard ecological theories are insufficient to address the com plexity of human culture,behaviour, and institutions (Grimm and Redman, 2004: 13 as summarized in Evans, 2011: 228).How does this relate to the wayplanning theory conceptualizes humannature relations?Issues of humannature interaction are central to the very process ofhuman settlement, urbanization and well-being. Ever since the establishment of the very first permanent settlements

following the shiftfrom nomadic to agrarian-based living, ecosystem services have beencritical to the capacity of those settlements to survive and indeed thrive(Daily, 1997; Redman,1999). Access to fresh water, reliable food and energy sources, and construction materialshas been essential. Yet archaeology reveals repeated examples of urban civilizationsexceeding the limits of accessible ecosystem services.Among the more severe human-inducedenvironmental impacts are those associated with

ancient urban societies, whose dense populations,rising rates of consumption, and agricultural intensification led to regional degradation soextreme that cities were abandoned and the productive potential of entire civilizationswas underminedto the point of ruin. (Grimm et al., 2000 : 572) It is not surprising therefore that there are well-knownand established bodies of research exploring humannature relations in and of cities, from disciplines including geography,history, archaeology and of course planning. Indeed, there is a long history of attention to human nature relations through designand planning practice. Since the emergence of town planning as a discipline, humannature relations have been highlightedthrough the Chicago School of planning, the early British town planners such as Ebenezer Howard (1850 1928), Patrick Geddes(18541932) and his influence on Lewis Mumford and later on through more detailed practice-based attention of how to design

with nature (McHarg, 1969). From the 1970s, environmental planning emerged as a sub-discipline (Slocombe, 1993). Morerecently this relationship is explored through the sustainability discourse(e.g. Owens andCowell, 2002; Rydin, 2010) and emergence of climate change.However, when attention is turned totheplanning theory literature per se, there is arguably minimal attentionto the implications of ecologicalconsiderations as a primary concern. This is not to say that these issues havent been dealt with at all, but that contributions

seem to be limited compared to the extensive focus on the trajectory of planning theories from rationalist and critical through tocollaborative and post-positivist. Areas where planning theory has specifically taken up matters of humannature relations regardenvironmental ethics and political ecology. In addition, in relatively recent years increasing attention is being paid to what arelational understanding of social-ecological processes means for planning theory (e.g. Hillier, 2007; Swyngedouw, 2010). Environmental ethics is of import for planning theory because it critically informs the difficult choices and tradeoffs society mustmake to address serious environmental problems (Beatley, 1989; Jacobs, 1995). It is not suggested that planners be the ones todecide what the morally correct or ethical environmental decision is, but that they are cer tainly in a position to put forth, andcause to be considered, key questions in arriving at an environmental ethic (Beatley, 1989: 26). Some of these issues are takenup in brief by subsequent planning theorists. For example, Healey (1997: 164) raises the issue of moral responsibilities forthosewho cannot speak for themselves, other species and future generations and Wilson and Piper (2010: 120) suggest that climatechange radically extends attention to the longer-term future at the same time as throwing into greater relief the problems of

ensuring equitable outcomes of plans and planning decisions both now and in the future.Political ecology isrelevant for planning theory because society must consider the environmental crisis asone of ideological and political as well as ethical and moral origins(Harrill, 1999: 68). From thisperspective, it is argued that a progressive or radical form of planning is required in order to

transform the social and political structures hindering sustainability(Harrill, 1999: 72). Thistransformation must occur in spite of the very present risk that as economic conditions decline so does the capacity to negotiatesustainable development gains, including ecological outcomes (Davoudi et al., 2009; Rydin, 2010) and in face of the systematicdepoliticization of social-ecological governance (Swyngedouw, 2010). In an insightful piece in Ashgates most recent ResearchCompendium to Planning Theory, Swyngedouw (2010: 31214) urges that planning intervention be seen as irredeemably violentengagements that re-choreograph socio-natural relations and assemblages and as such must be accompanied by democracticagonistic struggle over the content of socio-ecological life, struggles he argues are being replaced by techno-managerialplanning, expert management and administration.


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Policies exist within chaotic systems, those characterized by big changesdue to small adjustments in initial conditions, conditions which cannot beremade and whose effects are long since unpredictable.Peat, 8 [Non-Linear Dynamics (Chaos Theory) and its Implications for Policy Planning,http://www.fdavidpeat.com/bibliography/essays/chaos.htm, 10/12/12//CC]

Let us examine specific ways in which non-linearities can frustrate an attempt at policyplanning.i. Butterfly effectsIt may not always be possible to pin down a system exactly. There may be, for example,certain unknown or uncertain factors. The boundary to a system may not be well defined orthe very act of observation and measurement may introduce uncertainties. To give atechnical example, B. Mandelbrot has pointed out that the distribution and number ofweather stations has a "lower fractal dimension" than that of any real weather system.This means that, in principle, we can never gather sufficient information to characterizethe world's weather. A tiny degree of uncertainty in a linear system does not really matter--it simply results in a small degree of uncertainty in its future. But for some non-linear systemsthese uncertainties can increase exponentially; such systems are infinitely sensitive to their

initial conditions so that the smallest initial fluctuation soon swamps the system. Othersystems may be infinitely sensitive to externalities-- the butterfly effect - so that a tinyfluctuation or perturbation arising in some nearby system will swamp the system. Anotheraspect of the butterfly effect is that a small periodic effect, operating over a long enoughtime, may end up dominating the system while large external "shocks" are damped out. Notonly will the future of such systems be uncertain but attempts at control or correctivemeasures will give unpredictable results.ii. Sudden changesNon-linear systems are characterized by having "bifurcation-points",regions where thesystem sits on a knife edge, as it where, and may suddenly change its qualitative behavior.A system that has been well behaved for a long period may suddenly act erratically.Acompany that has been growing steadily for several years may unexpectedly enter a

period of uncontrolled oscillations of its economy. Other systems may become self-organized and settle down into a relatively stable period of well defined economic behavior.Attempts to steer this behavior into new directions during this period will be surprisinglydifficult. Over its life, a non-linear system can enter a series of quite different economicregimes and behaviors. And, it must be stressed, these changes need not always be theresult of external perturbations or "shocks" but are the natural unfolding of the internaldynamics of the system. Policy makers would therefore have to take into account that asystem may, at one time, be insensitive to control, and at another infinitely sensitiveandthat major changes in a system may not always be the result of external factors for anapparently negligible effect may, given time, swamp the behavior of the system.iii Exogenous or Endogenous Change?When a system, steered by a particular policy, undergoes a sudden dramatic change one

normally looks for some external cause.Has something changed in its environment, hassome unforeseen demand surfaced, or is it the result of the development of a newtechnology? But what if this major fluctuation or qualitative change has nothing to do withexternal circumstances but is endogenous - the result of purely internal dynamics? A smallregular, periodic internal fluctuation can suddenly swamp the system; and the iteration ofan output into the next cycle will, in time, result in qualitatively new behavior. It is ofobvious importance to be able to distinguish endogenous from exogenous factors.iv Chaotic behavior


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Systems sometimes enter regions of highly erratic and chaotic behavior. In such cases itbecomes impossible to predict the future behavior of the systemeven when based on itsentire past history. From moment to moment the system jumps violently in its behavior,moreover, it may be infinitely sensitive to any external change of fluctuation.But is a chaoticsystem totally devoid of order? A chaotic system appears totally unpredictable in its behavior,moreover its behavior may be impervious to corrective measures. But scientists are now

finding that what is called "deterministic chaos" exhibits certain regularities. For example,erratic swings, while entirely unpredictable, may nevertheless be confined to a particularlimited region -- called a chaotic or strange attractor. So while the moment to momentbehavior of the system is unpredictable, uncovering the geometry of the strange attractorsgive information about the overall range of behavior. It is also a matter of debate as towhether a chaotic system should be spoken of as totally devoid of any order, or as exhibitinga highly complex and subtle order.Moreover such systems may also exhibit "intermittency",periods of simple order which emerge again and again out of chaos.When faced with thealternation of order and chaos one may ask: "Does this represent a break down of goodorder, a failure of policy?Or is the order itself a temporary breakdown of a more generalchaos - or infinite complexity of behavior?"That there can be order within chance can beseen in the following way: Suppose someone has tossed ten "heads" in a row. Most people

would bet that the next throw must be tails. But knowing that the system is truly randomindicates that there is a 50:50 chance that the next throw will be "heads". In this way anexperienced gambler will, on the average, win over a gullible opponent. In a similar fashion,knowing the range of chaotic behavior enables one to hedge policy bets and come outmarginally ahead over a long period of time.v Self similarityChaotic systemshave much in common with fractals, indeed their strange attractors have afractal structure. Likewise there may be detailed fractal patterns in their dynamics thatrepeat at different scales of time. Having knowledge of such patterns would make it possibleto, on the average, make better micropredictions. I.e.one computer analysis of stockmarket data suggests that there are self-similar patterns at 14, 5 and 2 yr. periodsand in5 month periods and that the same patterns may be present within each day.

vi FeedforwardWhere two or more products compete for a given market a process of feedforward takesplace. The effect of a tiny initial fluctuation may cause one particular product toeventually dominate the market. An example of this is the competition between VHS andBetamax videocassettes.


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Since the only predictable feature of these systems is their irregular andsporadic behavior, the entirety of the affs solvency mechanism comes intoquestion. Ultimately, they can offer only momentary, short-term andprobably unreliable solutions to the problems they identify.Levy 03[Applications and Limitations of Complexity Theory in Organization Theory and

Strategy, Universityof Massachusetts Boston,http://www.faculty.umb.edu/david_levy/complex00.pdf, 10/12/12//CC]A. Long-Term Planning Is Impossible.Chaos theory has demonstrated how smalldisturbances multiply over time because of nonlinear relationships and feedback effects.As a result, such systems are extremely sensitive to initial conditions, making their futurestates appear random.Networks, even when in the ordered regime, are subject toperturbations from external influences, which sometimes cause substantial, thoughunpredictable reconfigurations. Forecasting is particularly difficult in systems that neverapproach a stable equilibrium state. The traditional approach to understanding theinfluence of industry structure on firm behavior and competitive outcomes has been derivedfrom microeconomics, with its on comparative statics and equilibrium. Even the mostcomplex game theoretic models are only considered useful if they predict an equilibrium

outcome. By contrast, chaotic systems do not reach a stable equilibrium; indeed, they cannever pass through the same exact state more than once.Organizations wander the shiftingterrain of fitness landscapes on infinite journeys. Industries might reach some temporary,relatively stable pattern, but this is likely to be short lived. Endogenous change, due tocorporate decisions to enter or exit the market or to develop new technologies, shifts thefitness landscape and the attractors in a system. Industries are subsystems of largereconomic and social structures, which themselves are complex dynamic systems unfoldingin unpredictable ways.Stacey (1995) relates this coevolution to Giddens's (1984) concept ofstructuration, in which the decisions and actions of agents change institutions, and theseinstitutions in turn constrain and condition the behavior of individual agents. Formulating along-term plan is clearly a key strategic task facing any organization. People involved inplanning have always known that models are simplified representations, that forecasts are

uncertain, and that uncertainty grows over time.Nevertheless, our conventionalunderstanding of linear models suggests that better models and a more accurate specificationof starting conditions would yield better forecasts, useful for months if not years into thefuture. Complexity theory suggests otherwise; the payoff in terms of better forecasts frombuilding more complex and more accurate models may be small. Meteorologists canimprove their models by using more terrestial observations and dividing the atmosphere into agreat many small interacting units of analysis; despite the application of successively morepowerful computers, the accuracy of forecasts still falls off very rapidly after 3 or 4 days.Similarly, we cannot learn much about the future by studying the past: If history is thesum of complex and nonlinear interactions among people and nations, then history doesnot repeat itself. Concerning urban planning, Cartwright (1991) has noted that we have toacknowledge that "a complete understanding of some of the things we plan may be beyond all

possibility." Stacey (1996: 187) concluded that though short-term behavior might bepredictable, "members of an organization, no matter how intelligent and powerful, will beunable to predict the specific long-term outcomes of their actions." How long is the longterm? Many discussions of complexity avoid this critical issue. For the weather, it is clear thatmore than 5 days is long-term forecasting. For biological evolutionary systems. the timeframe might be miilions of years. For firms and industries, the relationship betweenuncertainty and time is less clear; businesses have traditionally developed strategic plans for3 or 5 years, though many companies also attempt to predict major technological trends over


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In-round impacts and shit, cut itSil and Katzenstein, 10[Rudra and Peter, Sil is an Associate Professor of PoliticalScience at the University of Pennysylvania while Katzenstein is a Professor of InternationalStudies at Cornell, Analytic Eclecticism in the Study of World Politics: ReconfiguringProblems and Mechanisms across Research Traditions, part of UPenn articles collection,http://www.polisci.upenn.edu/faculty/RSEclectic2010.pdf //AC]Analytic eclecticism does not constitute an alternative model of research. It is an intellectualstance a researcher can adopt when pursuing research that engages, but does not fit neatlywithin, established research traditions in a given discipline or field. We identify analyticeclecticism in terms of three characteristics that distinguish it from conventional scholarshipembedded in research traditions. First, it proceeds at least implicitly on the basis of apragmatist ethos, manifested concretely in the search for middle-range theoretical argumentsthat potentially speak to concrete issues of policy and practice. Second, it addressesproblems of wide scope that, in contrast to more narrowly parsed research puzzles designedto test theories or fill in gaps within research traditions, incorporate more of the complexityand messiness of particular real-world situations. Third, in constructing substantive argumentsrelated to these problems, analytic eclecticism generates complex causal stories that forgo

parsimony in order to capture the interactions among different types of causal mechanismsnormally analyzed in isolation from each other within separate research traditions. This is notthe first call for something resembling eclec-ticism. In addition to Lindblom and Cohen,numerous scholars have issued pleas for a more practically useful social scienceor, followingAristotle, a phronetic social scienceoriented more toward social commentary and politicalaction than toward inter-paradigm debates.3 In international relations, prominent scholars,some even iden-tified with particular research traditions, have acknowledged the need forincorporating elements from other approaches in order to fashion more usable and morecomprehensive forms of knowledge. For example, Kenneth Waltz, whose name would becomesynonymous with neorealism, argued in his earlier work: The prescriptions directly derivedfrom a single image [of international relations] are incomplete because they are based uponpartial analyses. The partial quality of each image sets up a tension that drives one toward

inclusion of the others . . . One is led to search for the inclusive nexus of causes.4 An ardentcritic of realist theory, Andrew Moravcsik, would have to agree with Waltz on this point: Theoutbreak of World Wars I and II, the emergence of international human rights norms, and theevolution of the European Union, for example, are surely important enough events to meritcomprehensive explanation even at the expense of theoretical parsimony.5 Similarly, in animportant symposium on the role of theory in comparative politics, several prominentscholars emphasized the virtues of an eclectic combination of diverse theoreticalperspectives in making sense of cases, cautioning against the excessive sim-plificationsrequired to apply a single theoretical lens to grasp the manifold complexities on the ground.6As far as programmatic statements go, these views are all consistent with the spirit ofanalytic eclecticism. Whether these positions are readily evident in research practice, how-ever, is quite another matter. For the most part, social sci-entific research is still organized

around particular research traditions or scholarly communities, each marked by its ownepistemic commitments, its own theoretical vocabulary, its own standards, and its ownconceptions of progress. A more effective case for eclectic scholarship requires more thanstatements embracing intellectual pluralism or multi- causal explanation. It requires analternative understanding of research practice that is coherent enough to be distinguishablefrom conventional scholarship and yet flex-ible enough to accommodate a wide range ofproblems, con-cepts, methods, and causal arguments. We have sought to systematicallyarticulate such an understanding in the form of analytic eclecticism, emphasizing itspragmatist ethos, its orientation towards preexisting styles and schools of research, and its
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distinctive value added in relating academic debates to concrete matters of policy andpractice.


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Butterflies are beautiful, cut itKissane, 7[Dylan Kissane, assistant dean at the Centre d'Etudes Franco-Americain deManagement, lecturer at the University of South Australia, PhD from the University of SouthAustralia in International Relations theory The possibility for theoretical revolution ininternational politics,http://works.bepress.com/dylankissane/16 //AC]The butterfly effect - in reality just the popular name for the more correct 'sensitivedependence on initial conditions' - suggests that it is possible that the flutter of a butterfly'swings in Beijing can be responsible for producing a hurricane in South America (Thietart andForgues 1995, 21). This sensitive dependence on initial conditions is common to all chaoticsystems, being found everywhere from meteorology to economics and political science tophysics (Lorenz 1963; Brock et al 1991; Richards 1993; Reinhardt 1997). Chaotic systemsderive their variety from this sensitive dependence and, as a result, are largely unpredictablelong-term. A related element of chaotic systems is the importance of unit or individual unitevents to have wide- ranging effects on the wider system. Interactions, even those limited tojust two primary units, can and do affect all other units in the system. However, although weknow it is possible for such unit level effects to have significant system level impacts, it iseither impractical or impossible to collect and analyse such data. In effect, our models are

never truly complete and, therefore, never truly correct (Justan 2001). However, theimportance of such unit level events on the wider system should not be overemphasised. Ashas been argued elsewhere: ...not every butterfly creates a distant storm every time it movesfrom flower to flower. Should this be the case then there would be no stability at all withinthe climatic system and even short-term predictions - for example, the likelihood of raintomorrow - would become impossible. Thus, it should be noted, that just as these smallevents can impact on the wider system in significant ways, they could also not impact on thesystem in significant ways. There is no compulsion implied, only possibility which, in turn,ensures that the chaotic system is sometimes driven by these tiny events and, at other times,does not react at all, despite being faced with perhaps millions of such small interactions at atime (Kissane 2006,95). Chaotic systems may not seem chaotic. To the observer or analystthey may appear stochastic or even cyclical; indeed, some systems, which were previously

thought to be linear or cyclical, have since proved chaotic upon closer study (Gleick 1987,315-316). It is the argument of this paper that the widely assumed anarchy of theinternational system can also be considered another misinterpretation of a chaotic system.The fact that there is no overarching authority in the system may make the system anarchicby definition, but it does not exclude the possibility that it is actually chaotic. It might besaid that whereas in an anarchic system nobody is in control, in a chaotic system everyone isin control and - in effect - nobody seems to be in control. This is more than a semanticdifference - indeed, as the structure of a chaotic international system is outlined in thefollowing section it will become clear that this difference between anarchy and chaos is whatprovides the chaotic theory with its explanatory edge.
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