Parson Game

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THE PARSONS GAME:THE FIRST SIMULATION OF TALCOTT PARSONS' THEORY OF ACTION

by Stan Rifkin

B.S., Business Administration (Quantitative Methods), School of Business &Economics, California State University at Northridge, 1968

M.S., Computer Science, School of Engineering & Applied Science,University of California at Los Angeles, 1972

A dissertation submitted to:

The Faculty of theGraduate School of Education and Human Development

of The George Washington Universityin partial fulfillment of the requirements

for the degree of Doctor of Education

January 30, 2005

Dissertation directed by:

Dr. David Schwandt, Professor of Human Resource Development, andDirector, Center for the Study of Learning and

Executive Leadership Doctoral Program,Graduate School of Education and Human Development,

The George Washington University

Committee:

Dr. Walter Andre Brown, Assistant Professor of Higher Education Administration,Graduate School of Education and Human Development,

The George Washington University

Dr. Robert Hanneman, Professor of Sociology,College of Humanities, Arts, and Social Sciences,

University of California at Riverside

1.0 7 Dec 2004
http://www.chass.ucr.edu/http://www.chass.ucr.edu/


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Copyright 2004 Stan RifkinAll rights reserved


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ContentsAbstract............................................................................................................vAcknowledgments.......................................................................................... viI. Introduction................................................................................................1

How this study differs from its predecessors.............................................4Novelty of results.......................................................................................5Conceptual framework...............................................................................7Problem....................................................................................................16Research question....................................................................................17Significance..............................................................................................17Limitations...............................................................................................21

II. Literature review.....................................................................................25Theory, model, and simulation................................................................25The theory of action.................................................................................25Tension management and learning..........................................................26

Place of Parsons' theory of action in sociology.......................................27The bad news...........................................................................................29Locating this work within all of Parsons'.................................................29Models......................................................................................................30Formalization...........................................................................................32Time.........................................................................................................34Process.....................................................................................................36Simulations of social systems..................................................................38Discrete event simulation.........................................................................39

III. Methods....................................................................................................43Research overview...................................................................................43Research methods....................................................................................43Delimitations............................................................................................52

IV. The model and simulation........................................................................55Why simulate? .........................................................................................55Model construction..................................................................................56Basic concept...........................................................................................57Model of tension and learning.................................................................58Operation of the simulation.....................................................................63Rules........................................................................................................67Assumptions.............................................................................................69Mapping the model to theory...................................................................71

V. Results......................................................................................................76Example...................................................................................................76Base cases................................................................................................80Extension..................................................................................................84

VI. Conclusions and recommendations for further study..............................87Review of purpose and research question................................................87Review of findings...................................................................................87Discussion................................................................................................88


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Implications..............................................................................................91Recommendations for further study.........................................................93In sum.......................................................................................................95

Epilogue.........................................................................................................96References......................................................................................................99

Appendix Attestation of an Expert...........................................................114Appendix Simulation Program Listing.....................................................115

FiguresFigure 1.Sastrys "simplified causal diagram of the punctuated change theory." .............4Figure 2. The components of action systems. ..................................................................12Figure 3. The action system in relation to its environment. .............................................14Figure 4. Interchange media (whose paths are represented by arrows) in the general

theory of action................................................................................................15Figure 5. Phases in the relationship of a system to its situation. ......................................16Figure 6.Flow from theory to action. ...............................................................................18

Figure 7. Relationship among process, event, and state (notional)...................................37Figure 8.Intersection of the theory of action and system simulation. ..............................43Figure 9.Classification of social systems simulators, indicating the position of this

research in bold................................................................................................46Figure 10.Thorngates one-armed clock. .........................................................................21Figure 11.Evolution of computer simulations of organizations. .....................................22Figure 12. Structure of the three-parameter hyperbolic learning curve model. ...............61Figure 13. I llustration of a negative exponential distribution as a "forgetting" function..62Figure 14. User view of dedicated Excel spreadsheet.......................................................64Figure 15. User view of the simulation.............................................................................65Figure 16. User display for example with long window...................................................78Figure 17. Energy for the long window example..............................................................79Figure 18.Energy for the short window example.............................................................79Figure 19. Base case for affect vs. affect-neutrality..........................................................81Figure 20. Pattern of internal energy following external with a strong culture. ...............82Figure 21. Pattern of internal energy following external with a weak culture..................83Figure 22. Pattern of internal energy following external energy with very weak culture.84Figure 23. Simulation after two energetic events per year, both with affect. Illustrates

queuing effects.................................................................................................85Tables

Table 1. Works by Parsons, his supporters, and his critics................................................2Table 2. Additional delimitations of the study..................................................................22Table 3. The system dynamics modeling process across the classic literature. ..............57Table 4. Rules of the simulation........................................................................................67Table 5. Assumptions made in the simulation...................................................................69Table 6. Map of the theory to the model...........................................................................72Table 7. Correspondence between what was required and what was developed.............88


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ABSTRACTTalcott Parsons was perhaps the best known American sociologist of the 20th

Century. He postulated a general theory of the structure and function of social systems,one at all levels of analysis and all levels of abstraction. The center of his theory is action,which he defined in his own terms of situation, conditions, ends, and norms.

For those familiar with Parsons' work, the creation described here simulated usinga digital computer a very small subset of Parsons' theory of action, including his frame-work of four functions or functional prerequisites, one of the four pairs of pattern vari-ables, the cybernetic hierarchy, and interchange media. The simulation was meant to be aproof-of-concept, a toy demonstration of the feasibility of modeling such a complete andrichly described social action theory.

Most simulations of social systems use a modeling technique called systemdynamics, a way of characterizing flows and accumulations over time. Other researchershave tried to simulate the theory of action using system dynamics but have failed. Onecontribution of this research is the application of a different technique, discrete eventsimulation, to social systems. There are only two published applications of discrete event

simulation applied to social systems. Accordingly, this work offers some insight into howto incorporate time ordering into reasoning about social systems.Simulations were executed to demonstrate consistency with outcomes predicted

by the theory. One finding was that Parsons neglected to take into account the dispositionof (motivational) energy transiting through a system or organization when the energy isblocked by having to wait for the processing of predecessor energy. The effect of thisoversight can be a very long wait for the availability of a prerequisite function and noguidance on whether, for example, the energy decays, dissipates, waits, interrupts, or ischanneled elsewhere.


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ACKNOWLEDGMENTS"We shape our models and then our models shape us."

- Michael Schrage. (2000). Serious play: How the world's best companies simulate to innovate,Harvard Business School Press, p. 3.

Several fellow students in the Executive Leadership Program (ELP) cohort havesustained my enthusiasm, including, but not limited to, Dr. Betty Beene, Dr. BrendaConley, Linda Hodo, and Dr. Ted Willey. Dr. Margaret Gorman has been a steady forcemoving me ahead and she has been a safe harbor for my administrative challenges. Ialways feel like Margaret treats me as a distinctive student, a gift she has for making eachone of us feel special. And her dissertation was breath-taking.

I am grateful to Laura Reid of Simul8 Corporation for attesting to the veracity ofthe technical operation of the simulation described in this dissertation and along the wayhelping me to improve its operation and correctness. I am also grateful for those whocame before me in the application of computation methods to organizational problems, in

particular Profs. Rich Burton at Duke, and John Kunz and Ray Levitt at Stanford, for per-sonally helping me to see that engineering tools such as discrete event simulation couldbe beneficially applied to social systems. Profs. Kathleen Carley at Carnegie Mellon andAnjali Sastry at MIT were also instrumental in personally inspiring me to try to applyengineering methods to the questions of social systems.

Dr. Chris Johnson gave me the courage to undertake the study of Talcott Parsons.Dr. Johnson is a Parsons scholar and his energy and enthusiasm about Parsons are conta-gious and set the bar high. He is very, very busy and I am especially grateful that he hastaken on three roles: expert who attests to the mapping of the theory of action to thesimulation model, an outside reader for the dissertation defense, and a friend and col-league.

I consider myself an adequate researcher, but it took me too long to find Prof.Tom Fararo, a professor in the School of Sociology at the University of Pittsburgh andanother Parsons scholar. Prof. Fararo, besides being an inspiration in his writing andinterpretation of Parsons, has been a ready and energetic reader of my manuscripts. I amgrateful for his generous expenditure of time and energy on my behalf.

Professors Walter Brown and Robert Hanneman, members of the dissertationcommittee, have been generous with their time and energy. They have in their uniqueways given me important, stimulating feedback.

Prof. Dave Schwandt has been my close mentor throughout this long journey. Heis the person who spoke to me at the very beginning about joining ELP. I was struck im-mediately then by his boundary spanning, openness to people not in his field(s), and how

gentle he was with people like me who knew nothing of human resource development. Afew years ago he introduced me as, "This is Stan. He is the only person I know who hasthe whole dissertation in his head!" Prof. Schwandt has been so generous with his timethat I feel guilty. It should not have taken all of this prodding to get me to finish, but I amslow and Dave has been a patient, steady, and exacting influence. He, too, is a Parsonsscholar and has not been put off by my excursions into what I felt might be important,while he kept me focused and fixed. He has the gift, too, of making each one of his stu-dents feel special and unique, and I am forever grateful for his friendship and guidance.


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All doctoral work is a family effort. My wife, J an, from the very first moment wespoke about the Program and the time it would mean away from her, has cheered me on,even during the lonely days and evenings she spent as I studied and wrote. Everyoneloves Jan and she, too, has made friends among my ELP colleagues and leaders. She hasmade this long journey worthwhile and possible. She also proof-read this final version, a

sacrifice well beyond the pale. I am responsible for any remaining errors, faults, failures,oversights, defects, and misinterpretations.I thank all of the people above for their gently persuading me to finish.


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I. INTRODUCTION"All models are wrong. Some are useful." - George E.P. Box

Creating a computer program to simulate Talcott Parsons general theory ofaction has proved elusive. Two researchers who have had considerable success simulat-

ing social systems (e.g., J acobsen & Bronson, 1985; Jacobsen & Bronson, 1987;Jacobsen, Bronson, & Vekstein, 1990) have written that they were unable to construct acomputer program that would simulate Parsons theory (Jacobsen & Bronson, 1997). Thepurpose of this dissertation is to describe a proof of the concept that it is possible to cre-ate such a computer program.

Many simulations of social systems cast those systems in terms of rates of changeof key constructs (Hanneman, 1988). They are systems of differential equations, even ifsomewhat disguised. The current research framed organizations in Parsons terms ashaving a significant time-ordering of events, not in terms of rates of change. Time-ordering, directly according to Parsons words, was expressed as "before," "then," "next,""cycles," "phases," etc. Using a time-ordering style of simulation yielded a toy or proof of

concept that was animated inside a digital computer and used to ask and answer a new setof questions about the theory, and might serve as a basis for the construction of a highfidelity simulation.

Social scientists have long sought a test bed for their ideas, concepts, and theories.Typically "the scientific method" applies to the "hard" sciences, where researchers con-sult a theory, postulate a question or hypothesis, enter a laboratory where they controlenvironmental factors, and put together an apparatus to generate some phenomena andmeasure the outcomes (Kuhn, 1970). "Normal" science laboratories do not exist in thesocial sciences, primarily because environments cannot be controlled or, more accu-rately, controlling the environment changes it, so normal science cannot be applied. As aresult, there is some appeal in attempting to create an environment inside of a digitalcomputer where the structure and function of a social system could be mirrored. Com-puter simulation, if appropriately validated, has offered a means to instantiate and exer-cise richly described social systems (Hanneman, 1988).

In order to instruct a computer to simulate (that is, "act like," in a reifiedcontext) a social system to bring the social system to life it was required to have a"sufficient" description of the (static) structure of the constructs along with a descriptionof the (dynamic, time-varying) functioning of the static constructs. While no one knowswhat the definition of "sufficient" is a priori, Parsons theory of action was a candidate atleast from a volume perspective because Parsons himself wrote thousands of pages aboutit, supporters have written thousands, and critics another thousand or so (seeTable 1below). It remained to read the contributions to the theory of action and extract itsdescriptions of salient structure and function to see if they were sufficiently detailed tosimulate a social system resembling the one described by Parsons. The main purpose ofthis dissertation is to document the extraction and resulting simulated social system.

It is useful to note that there are detractors as well as supporters of Parsons' work.Clearly there is not universal agreement on the meaning and importance of his model. Afew of the areas of disagreement are described at the end of "Place of Parsons' theory ofaction in sociology," in the Literature Review chapter, p.27.


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Table 1.Works by Parsons, his supporters, and his critics

Works by Parsons Works by supporters Works by criticsParsons, 1951-1978b;Parsons & Bales, 1953;

Parsons, Bales, & Shils,1953a; Parsons, Bales, &Shils, 1953b; Parsons &Platt, 1973; Parsons &Shils, 1951; Parsons &Smelser, 1956

Alexander, 1983; Alexander& Sciortino, 1996; Barber

& Inkeles, 1971; Bluth,1982; Boudon &Bourricaud, 1989;Bourricaud, 1981;Brownstein, 1982; Etzioni,1975; Hills, 1968;Holmwood, 1996, 1983;Lackey, 1987; Loubser,Baum, Effrat, & Lidz,1976a, 1976b; Park, 1967;Rocher, 1975; Turner, 1999

Black, 1961; Camic, 1996;Camic, 1998; Dubin, 1960;

Habermas, 1981; Kolb,1962; McGowan, 1998;Savage, 1981; Selznick,1961

Constructing a model of time-variation, especially of mathematical equations,inside a computer is not new and is used often in the "hard" sciences. Jacobsen and Bron-son (1985) point out:

Generally, models can be classified as one of three types: iconic, analog, orabstract. An iconic model is one that looks identical to the system it represents.An example is a wood and paint mockup of an automobile shell. From a distance,the mockup appears to be an automobile, but as the mockup has no engine or inte-rior, it is not a complete representation of an automobile. Y et if the purpose of themodel is to determine the aerodynamic characteristics of the system it representsby subjecting it to wind tunnel tests, then this iconic model is quite adequate. An

analog model is one that does not look like the systems it represents but has corre-sponding behavior. Engineers often build electrical systems as analog models ofmechanical systems. By measuring the current in an analogous electrical systems,they can predict the motion in a mechanical spring system. An abstract model is aset of statements about the structure of a real system. If these are formulated asmathematical equations, they may be solved and used to predict the behavior ofthe real system. It is this last type, abstract mathematical models, which form thebasis of continuous simulation. (pp. 57-58)

By applying this kind of modeling to the study of social systems, a researcher canwatch the interaction of social forces reveal themselves with time slowed down or

speeded up inside a computer and can obtain a very detailed understanding of the contri-butions of structure and of function to the specific observed behavior of the social sys-tem.

Also, the replication of theory inside a computer is not a new idea, not even fortheories of organization, as illustrated in early histories provided by Hanneman (1988)and Garson (1994). The first comprehensive simulation of an organization was probablyA Behavioral Theory of the Firm(Cyert & March, 1963). This work was a tour de forceintegration of microeconomics (that is, the setting by a firm of output level and product


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price) with organizational goal-setting, choice, and rational decision-making. While theunit of analysis was the description of a single firm among competitors, it could beexpanded to the description of aggregates of firms and to non-business organizations,and to the normative analysis of a single firm and of economic policy. Incidentally, whilenot citing Parsons' constructs, there are many references to them without acknowledg-

ment.

1

The replication of theory inside a computer is experiencing recent interest in thesocial sciences as more researchers come to the social sciences from other, hard scienceareas (e.g., computer science, mathematics, psychology) (Burton & Obel, 1995; Carley &Prietula, 1994; Coleman, 1965; Conte, Hegselmann, & Terno, 1997; Gilbert & Conte,1995; Gullahorn & Gullahorn, 1963; Hanneman, 1988; Ilgen & Hulin, 2000; Jacobsen &Bronson, 1995; Jacobsen & Bronson, 1987; Jacobsen & Bronson, 1997; Phelan, 1995;Prietula, Carley, & Gasser, 1998; Samuelson, 2000). The normal course of research incomputational and mathematical organization theory is to wringstructureand functionfrom a theory, operationalize or animatethem, and then make changes in the simulatedenvironment or the structure/function and watch the computers results for interesting,

informative patterns, including validation with respect to the underlying theory. To "ani-mate" in this context means to bring to life graphically on a computer screen.For example, Sastry for her Massachusetts Institute of Technology doctoral dis-

sertation, redacted in Sastry (1997), took a detailed, simulation-oriented look at the struc-ture and operation of how Tushman and Romanelli (1985) explained strategic change.She was able to show inconsistencies in their explanation, a more parsimonious explana-tion, and to more clearly reason about cause and effect. She showed, among other things,that there were loops that reinforced positive or negative feedback, thereby speeding upor retarding the change, respectively. The lines inFigure 1, below, represent flows ofinformation, and the noun phrases (e.g., "Strategic orientation required") represent eitherinputs or accumulations of values. By simulating the operation of strategic change at theorganizational level, Sastry was able to identify which postulated stores (accumulations)would be a priority to measure in the real world because of their dominant effects andwhich would be a lower priority because they may have only secondary effects.

1 The particular constructs, the four functional prerequisites, are explained later in the text, on p. 11. In Cyert & March(1963, chap. 6, pp. 114-127) "A summary of basic concepts in the behavioral theory of the firm," there are goals,expectations, and choices. Regarding organizational goals, e.g., "... we have argued that organizational goals changeas new participants enter and old participants leave the coalition [making the decisions]." p. 115. This is latentpattern maintenance. Organizational expectations are based on "search," an analog to environmental interface, theadaptation function. p. 116. And as to organizational choice, "the standard decision rules are affected primarily bythe past experience of the organization and past record of organizational slack," which are references to patternmaintenance and integration functions, respectively. p. 116.


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Figure 1.

Sastrys "simplified causal diagram of the punctuated changetheory." (Sastry, 1997)

Sastry accomplished her task by reading the Tushman and Romanelli article(1985) and coding each passage as applying to a definition, a structure (i.e., staticrelationship), dynamic behavior, or not applicable for her study. She collected the state-ments about structure, for example, and derived constructs consistent with her modelingchoice (system dynamics in that case) and training as a system dynamicist. She con-structed a computer replica of the static and dynamic components and animated it byhaving information from the simulated environment flow along the lines of the diagram.She then graphed the changes in accumulations and how well the strategic orientation

tracked the required one. She made changes in the flow rates and accumulation rules asexperiments. Her article essentially reports the patterns she observed based on varyingwhat she postulated were independent variables. In conclusion she observed by simula-tion six novel ways that managing strategic change failed (Sastry, 1997).

The approach of this study was to construct a high fidelity replica of the essentialaspects of the theory of action, so the replica mirrored the elements of action that Parsonsdescribed as indispensable: the situation, conditions, ends, and norms (Parsons, 1968a, p.44). As well, it modeled time because Parsons theory described time-varying behavior:action by its definition and nature is dynamic.

How this study differs from its predecessorsSastry (1997) and Jacobsen and Bronson (1985) both applied system dynamics

(Hanneman, 1988), a symbolic representation of systems of differential equations, toorganizational and social studies, respectively. Jacobsen and Bronson (1997), in a papersummarizing their 15 years of social system simulation, note, "A ... theory we tried tomodel was Parsons' General Theory of Action. We chose it for its renown and because ofthe controversies around it. We soon found that it could not be modeled at all because ofthe unclarity and inconsistencies in Parsons' use of concepts." (p. 98 ) Their challengewas to translate elements of Parsons theory of action into the standard system dynamicsform of information flows among accumulations. They tried having material flow (the


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kind that is physical and is allocated as part of Goal Attainment) be a model of roles orresources. They tried modeling the way of acting and the method of giving meaning toactions, but were left wondering where the next generation arose. They tried having threeof the functions concentric around one of them, but that would contradict Parsons' dia-gram that shows them all interconnected. They tried a causal loop diagram among the

four functions, but it traveled in the opposite direction that Parsons envisioned. They triedusing the four functions as "valves" or controls on the stock of loyalty, power, order, andgoods. They considered pattern variables as "the ranges on which the other conceptscould be measured." In the end they abandoned their modeling effort. (Jacobsen, personalcommunication, October 31, 2000).

Parsons (1953a) writes, referring to his theory of action, "Since we are dealingwith processes which occur in a temporal order, therefore we must treat systems and theprocesses of their units as changingover time." (p. 167) [italics in original.] "The firstimportant implication is that an act is always a process in time. The time category is basicto the scheme." (Parsons, 1968a, p. 45). Jacobsen and Bronson can justify their (failed)approach by these statements (alone) because they sought to replicate the theory in terms

of time-varying constructs. The present research took a (slightly) different approach andapplied the iconic model, per Jacksons advice to construct a high-fidelity model(Jackson, 1983, pp. 4-5)2, not the abstract mathematical one of system dynamics. Thisway there was no need to guess what in Parsons theory corresponded to the systemdynamics constructs of flows and accumulations (which Jacobsen and Bronson had to).Instead, in this research there was a more literal translation between the elements of Par-sons theory and the simulation though the translation was not total, as many, many bitsof the theory were left out. For example, Parsons' posits four pairs of "pattern variables"and this research only models one of them, the one dealing with affect vs. rationality.

In particular, this research will concentrate on the "temporal order" aspect of Par-sons descriptions.

The idea of a mathematical model astheory in mathematical formbegan to takehold [in the 1950s]. Writers of variant interests all agreed that such models per-mitted the logical derivation of falsifiable claims about some class of phenomena.This differentiated mathematical models from curve-fitting and data analyticreduction methods. (Fararo, 1984, p. 152)

Indeed, this dissertation relies on a "cousin" of mathematical models, simulation,and therefore is not of the curve-fitting or data analytic reduction variety. There are nocorrelations, no Cronbach's alpha, no significance tests. In fact, there are almost no sta-tistics at all because, in great part, it deals with a theory at the analytic level.

Novelty of resultsResults were sought that are important, significant, but what might be the defini-

tion of those terms? Should "novel," "useful," "interesting" or "surprising" be added? Inthe spirit of propounding testable hypotheses, Parsons' theory of action does not predict

2 Not all models seek fidelity. One operational measure of fidelity is correspondence: for every important construct inthe world there is a (corresponding) construct in the model. Another term for correspondence might be requisitevariety: for every variation in input there is a corresponding control or regulation such that the output matches thevariation (Ashby, 1956, chap. 11). Some researchers deliberately translate what they sense into frameworks that arenot mirrors of the originals, thereby not seeking correspondence or requisite variety.


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what would happen in an organization that faced a high frequency of changes in its envi-ronment, too much for it to absorb in the interval in which the changes could be madesense of an acted upon (so called "permanent white water" (Vaill, 1996)). Would thechanges accumulate, be discarded, decay, or queue? Perhaps a computer acting like asystem of action could shed some light.

What is surprise, what is novelty? Van Fraassen (2002) argues that if science isobjective, then when a scientist sets up an experiment he/she anticipates that the values ofmeasured parameters will fall within certain bounds; the experimental setup is establishedto measure just those parameters and just at those levels. This, after all, is the orthodoxyof the science being invoked. So what can be regarded as novel that would be sensedduring such an experiment? In part it might be that the objectively measured resultswould not match those anticipated by the theory, even though the experimental apparatuswere established within the theory in the first place.

And van Fraassen (2002) reminds us that Kuhn (1970) has struggled with thesame dilemma and concluded that novelty, when it can be sensed, may yield a change inthe orthodoxy incidentally, still in terms of scientific methods that imply objectivity

if not the facts of the particular theory; there would be no resort to mythology or religion(because that would alter the method). So, novelty in van Fraassen and Kuhn's views ispossible and admissible.

Shackle (1969) postulates a calculus of surprise by introducing the notion ofpotential surprise.

A man cannot, in general, tell whatwill happen, but his conception of the natureof things, the nature of men and other their institutions and affairs and of the non-human world, enables him to form a judgement as to whether any suggested thingcanhappen. In telling himself that such and such a s thing 'can' happen, he meansthat its occurrence would notsurprisehim; for we are surprised by the occurrenceof what we had supposed to be against nature. (p. 67) [italics in original]

Shackle first divides a spectrum into extremes: perfect possibility would not sur-prise a person and impossibility would engage the absolute maximum degree of surprise(p. 68). Between them are degrees of possibility with their corresponding inverse degreesof surprise. While not important for the research here, Shackle posited that the dispersionof degree of possibility and corresponding degree of surprise is not a probability distribu-tion, but rather is non-distributional, that is, is not a function. One can have many eventsthat are not a surprise and their probability would not sum to unity.

To summarize, Shackle relates the degree of belief inversely with the degree ofsurprise: we are surprised by that which we believe cannot happen.

What might surprise look like in the research to be described here? First, thereader would have to think it was impossible to achieve. To a small subjective degree,

this has happened. When this researcher mentioned to other members of his school cohortwhat he is trying to do many of them expressed doubt that it would be possible. Further,Jacobsen and Bronson tried it and failed, so there is a hint of impossibility. "Some peopledon't believe that models of human behavior can be developed." (Sterman, 2000)

Second, the method of inquiry, a computer simulation, is far less restrictive of anexperimental setup than a traditional laboratory so some behavior might be observed thatwas not within expectation, not predicted by the orthodoxy, and therefore would be sur-prising within the ambit described by van Fraassen and Kuhn.


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There are perhaps two more reasons that surprise might be expected, both becauseParsons has written so much. First among these is that it is predictable that there might becontradictions or gaps in there somewhere, the precise nature of which might generatesurprise.3 And second among these is that so many people have already vetted Parsons'theory that anything new would be unexpected at this late date.

Conceptual frameworkThe fundamental framework that informed this research is that of systems. A sys-temis a collection of elements and interactions whose structure and function can beunderstood by looking at the whole, the summation, the interaction of elements. Thisdescription highlights a tension in systems study. Some scholars infer qualities of thewhole by studying the parts (methodological reductionism, typical in normal science),others claim that that one can never appreciate the whole by dissecting the parts (holism)(Honderich, 1995, pp. 750, 372); (Sibeon, 1999).

The approach in this study was somewhere in the middle: the whole was studiedby understanding its parts, but not separately, rather as they interacted and collaborated inpatterns to define the whole. Thus, the emphasis was on how the parts were connected,

what flowed along those connections, and how the interplay of connections and flowsdefined an organic whole.Parsons (1968b) wrote:Action systems have properties that are emergent only on a certain level of com-plexity in the relations of unit acts to each other. These properties cannot be iden-tified in any single unit act considered apart from its relation to others in the samesystem.They cannot be derived by a process of direct generalization of the prop-erties of the unit act. (p. 739) [emphasis in original]

The termenergyused in this research denotes the material in the environment ofthe system that is external to it and that can be sensed by the system. That is, energy isthe term used to label the elements in the world external to the system under study thatcan be used to stimulate the system, that can energize and activate the system to respondto the environment. Sometimes Parsons refers to this energy as motivation (Parsons et al.,1953a). Concretely, the energy could be news, ideas, or information, for example. News,of say an invention or a move by a competitor, could stimulate the system (in our case anorganization) to evaluate the content and respond to what it sensed in the external world.One important point is that the term energy used here is not the same as that used inphysics; in physics energy is conserved, that is neither consumed nor created, but in theuse here (social) energy may be infinitely created and transformed and possibly evenconsumed. Parsons postulated a law of conservation for motivational energy, which in itscentral part would claim that motivational energy is exchanged for changes in the system(Parsons et al., 1953a, p. 168). Alas, the merits of such a law of conservation of social

energy is beyond the ken of this research.If one considers a unit act to begin with the importation of exogenous energy,

then the social system presented by this research will follow the trajectory of that energyas it transits the replica of an organization. In order to imagine what the emergent proper-

3 Brownstein (1982) has found contradictions and gaps by converting a portion of the theory of action into a set of

logic statements and showing the inconsistencies therein.


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ties could be possible it is necessary to understand at least the rudiments of Parsons'theory of action.Parsons' theory of action

Talcott Parsons, perhaps the best known American sociologist of the 20th century,attempted to construct a theory that explained organizations at all units of analysis. He

was attracted to and influenced by the systems view

4

, among many other influences, andnoted that organizations are structured in specific ways, not randomly. He noted thatstructure and function interplayed, that the functions of an organization were executed byelements of its structure. He noted that the execution also was not random, that itresponded to normative pressures that could be applied exogenously and endogenously.5

He sought to understand the patterns of structure and function. His view was notreductionist, he was trying to see organizations at their highest levels of abstraction. Inorder to construct a high-level framework, Parsons (1960) defined the atomic unit, theunit act, to which everything else would refer:

The unit act involves therelationship of an actor to a situation composed ofobjects. The unit act, however, does not occur independently but as one unit in

the context of a wider system of actor-situation relationships, referred to as anaction system. Action is thus viewed as a process occurring between twostructural parts of a system actor and situation. (p. 467) [italics in original]

While the unit act is the atomic level, the social system describes social interac-tion, behavior. Behavior that directly concerned the "cultural level" Parsons called action.Said another way, relying on Weber, which Parsons often did, particularly related toaction:

Interpretive understanding of social actions is a prerequisite for the causal analy-sis of social structures and processes. In modern form, we can put it this way:there is an actual world ofeventsandsomeevents are behaviors. Behaviors aretreated asactionswhen they are analyzed relative to cultural frames of reference,according to which the behavior means one or more things to the producer of thebehavior and to the situational interpreters of the behavior. (Fararo & Skvoretz,1984, p. 148) [italics in original]

Action includes four generic types of subsystems (that is, collections at which unitacts occur): organism (atomic level, the individual), social system (generated by theinteraction among individual units), cultural systems (patternings of meaning, such asbeliefs and ideas), and personality (the learned patterns of social and cultural interaction)(Parsons, 1977b, p. 178). We might re-phrase these units of analysis, in order from small-est to largest, in terms of the sciences that usually describe and study them: biology, theorganism's physics and chemistry, its "atomic" structure; psychology, the individual's

learned behavior and decisions; sociology, the collective structure and action of individu-als; and anthropology, the national or religious influence.

4 "System seems to me to be an indispensable master concept ." (Parsons, 1977b, p. 101).

5 The non-randomness is the subject of an entire work, Parsons, Bales & Shils (1953b), according to Parsons (1960, p.195).


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Parsons described his theory, in the terms most important for this research, usingseveral constructs: pattern variables, functional prerequisites, interchange media, and thecybernetic hierarchy. Parsons theory was much larger than these constituents, but theywere the ones replicated in this research. It was an untestable (and therefore not falsifi-able) assumption of this research that the axes mentioned are the core of the theory of

action. Or stated more positively, if one can simulate these elements then the theory ofaction can be simulated.Pattern variables.

Robert Bales, a student of Parsons', was studying small group interaction. Bales'method of primary research was observation: he would watch actual groups deal with realsituations. He came to see patterns, broadly tasks and emotions. And he saw in groupsthat questions about tasks and emotions were asked and answered. He subdivided thepatterns into what he called four problem areas: expressive-integrative social-emotivepositive and negative reactions, and instrumental-adaptive task area questions andanswers. The modern depiction of this is illustrated in Bales (1999, figure 6.1, p. 165).

In a few words, Bales observed small groups and saw patterns in the interactions

among the participants. He saw questions and corresponding answers, he saw attention tothe work or tasks of the group, he saw positive and negative emotions, he saw reactionsto external and internal stimuli, he saw planning of tasks and work processes, and he sawsetting of norms and expectations and the response of performance to them, amongothers.

Parsons adopted Bales' framework and adapted it to describe the patterned struc-ture and function of organizations. He called the original five, later reduced to four, pairspattern variables (Parsons, 1960):

Each variable defines one property of a particular class of components. In the firstinstance, they distinguish between two sets of components,orientationsandmodalities. Orientation concerns that actor's relationshipto the objects in hissituation and is conceptualized by the two "attitudinal" variables of diffuseness-specificity and affectivity-neutrality. Modality concerns the meaningoftheobject for the actor and is conceptualized by the two "object-categorization" vari-ables of quality-performance and universalism-particularlism. It refers to thoseaspects of the object that have meaning for the actor, given the situation. (p. 468)[italics in original.]

The purpose of the classification was to suggest propositions about action systemsin terms of the components and the type of act their combination defines and controls. Inthis section pattern variables are described, then their patterned movement is described,and finally the patterned movement is structured to yield what becomes in the sectionafter this one the four functional prerequisites.

At base, action is grounded in motivation and emotion or its polar opposite, disci-pline. The emotional pole is calledaffectand the discipline or deferred gratification poleis calledaffect-neutral. The affect pole is considered an expressive action and the affect-neutral pole is considered a rational or cognitive pole. Fararo (2001) illustrates the differ-ence: "In the judge-defendant social relation in American society, in the public trialsituation, the judge is expected to restrain herself from expressing feelings of liking ornot liking the defendant. This constitutes a specific aspect of socially responsible actionexpected of a judge." (p. 150)


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Parsons averred based on Bales' small group interaction observations thatcognitive standards were expressed in a more general form that transcended any particu-lar group, while emotional or "appreciative" standards were applied to more particularcollections. The polar opposites then became theuniversalism-particularismpattern vari-able. Fararo (2001) illustrates the difference: "A judge is expected to apply the same body

of law toanydefendant before her. Socially responsible action defined by this universal-ism means transcendence of the particular relationship to the specific defendant beforeher." [italics in original] (p. 151)

The outcome of social action can be characterized either by the result of interac-tion or by the role-status of an actor or actors. The pair of opposites is variously calledquality-performanceor ascription-achievement. Fararo (2001) illustrates the difference:"To be appointed as a federal judge, a person must satisfy certain performance orachievement criteria pertaining to education and experience. The judge is evaluated byreference to performance, not according to race or gender." (p. 152)

In social action each actor may focus attention on a specific social object or in a"plurality" of social objects. The pair is called thespecificity-diffusenesspattern variable.

Fararo (2001) illustrates the difference: "A judge is expected to confine her interest in thedefendant to trial-related matters." (p. 152) That is, the judge would have a specific focus,not a diffuse interest in the affairs (that is, social actions) of the defendant.

Before relating these pattern variables to each other, it is worth mentioning thateither separately or in the combinations to be described next the values of the each pairrepresents in each social situation what is acceptable, the norm, the expected, the institu-tionalized pattern of appropriate orientation. In this sense, as Fararo reminds us (2001,p.149), the value of pattern variables acts as part of a (yet to be described) control mecha-nism to stabilize social action. When the values are the expected ones, then there is rein-forcement; when the values are not the expected ones then the social system responds toset the value right.

Parsons unlinked and then re-linked the pattern variables, each orientation witheach modality, this way: universalism with specificity, particularism with diffuseness,performance with affectivity, and quality with neutrality. While not evident at this pointin the exposition, the re-linking corresponded (Parsons said "converged," (1960, p. 468))to the classification of functional problems or prerequisites that Bales had earlier formu-lated (Bales, 1950).

The researcher asserts that in order to demonstrate the feasibility of simulatingParsons' theory, only one pattern variable needed to be selected. As will be explained onpage46, below, affective and affective-neutrality were selected. The affective orientationis that the actor responds to the situation emotionally, and its opposite, the affective-neu-tral orientation, is that the actor responds rationally, cognitively, not emotionally. (Heise,1979) states "Events cause people to respond affectively." Clearly, Heise is not going toagree with Parsons on this issue! This would have been important if Heise's work on af-fect, situated action, affective reactions, events, and social processes (op. cit.) were goingto inform the work reported here. Instead, Heise notes in his comprehensive and accessi-ble work that his framework is incommensurate with Parsons' (Heise, 1979).


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An action system is not characterized solely by the actor's orientations andmodalities; it is also a structured system with analytically independent6 aspects that thepattern variable combinations cannot take into account. That is, pattern variables are anecessary but not sufficient categorization. In particular, in a structured system both actorand object share norms (Parsons, 1960, p. 468); this is one definition ofinterpenetration.

Four functional prerequisites.Starting with the pattern variables and after a set of steps that consumed hundredsof pages in Parsons (1960), Figure 2, below, the components of action systems, was ulti-mately offered; it is not necessary to understand everything in the figure. At its heart arefour major quadrants at the intersections of external-internal and instrumental-consum-matory. These correspond to the four functional problems that Bales identified and Par-sons refined. Internal and external refer to inside and outside of the organization, endoge-nous and exogenous, respectively. Instrumental applies to means and consummatoryapplies to ends. The names of the major quadrants, starting in the upper left corner andmoving clockwise, are Adaptation, Goal Attainment, Integration, and (Latent) Pattern-Maintenance (AGIL). These four are imperatives, prerequisites for any organization, in

fact any organism, to address in order to survive, that is, in systems terminology tomaintain its boundary.7 They are also the functions performed with respect to socialactions.

6 "Analytically" is used in the sense of Kant (1896), namely that it is true by definition or logic or deduction, not byexperience (which would be synthetic, inductive, empirical). At one point, Parsons writes (1968a, p. 34), "It is thesegeneral attributes of concrete phenomena relevant within the framework of a given descriptive frame of reference to which the term'analytical elements' will be applied." [italics in original.]

7 "The difference between system and environment has two especially important implications. One is the existence andimportance of boundaries between the two. Thus, the individual living organism is bounded by something like a'skin' inside of which a different state prevails from that outside it. The second basic property is that in somesense they [organisms] are self-regulating. The maintenance of relative stability, including stability of certainprocesses of change like growth , in the face of substantially greater environmental variability, means that theremust be 'mechanisms' that adjust the state of the system relative to changes in its environment." (Parsons, 1977b, p.101)


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Figure 2. The components of action systems. (Parsons, 1960, p. 470)

The Adaptation (A) function imports and filters energy from the external world,the environment, and, based on the external and internal norms, attaches symbolicmeaning to it. The Goal Attainment (G) function sets goals (that is, ends) and allocatesresources in the service of those goals, based on the symbolic meaning of achieving them.Integration (I) aligns the structure and function of the organization to the goals in accor-dance with the resources allocated. Latent Pattern-Maintenance (L) establishes and thenmaintains the internal norms. "Latent" is used to refer to something unseen, the oppositeof manifest, and the pattern being maintained is what lay persons call organizational cul-ture. Parsons (1977b) says:

"The most importantsinglecondition of the integration of an interaction system isashared basis of normative order. Because it must operate to control the disrup-

tive potentialities (for the system of reference) of the autonomy of units, as wellas to guide autonomous action into channels which, through reinforcement,enhance the potential for autonomy of both the system as a whole and its memberunits, such a basis of ordermustbe normative." (p. 168) [italics in original]

Figure 2also illustrates a collateral point: Parsons set out to develop a grand uni-fied theory that could be applied up and down the units of analysis, from individual tocollective to culture. Accordingly, each of the four functional prerequisites can be sub-


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divided into four more functional prerequisites, and so on infinitely. The figure shows thefirst two divisions, one at the systems level and then the next at the level of each func-tional prerequisite. Note that the lower right quadrant, the one corresponding to Integra-tion, contains the four functions in the same order as the square containing it. This illus-trates the importance and centrality of Integration, as indicated by the quotation in the

paragraph above. And it also illustrates that the diagrams can be used to designate differ-ent levels of abstraction or granularity.The conceptualization of the pattern variables potentiated Parsons' understanding

of the four functional prerequisites because they all fit together so harmoniously.Cybernetic hierarchy.

Figure 3is the same asFigure 2in the sense that it contains the same 16 patternvariable combinations (listed in the upper right hand corner of each box), but the rowsand columns are arranged differently; it is not necessary to understand everything in thefigure. The rows (i.e., functional prerequisites) are now in the order L-I-G-A, and thecolumns in the order L-I-A-G. Note along the left edge that there is a direction of controland a direction of limiting conditions. These are thecybernetic hierarchy of control. The

organization is controlled, first and foremost, by its internal norms. The norms even con-trol which energy is imported and the sense is made of it; which particular energy is im-ported and what particular sense is made of it depends upon thevalueascribed to thenorm. Therefore, L is the most controlling and A the least.

Each cell categorizes the necessary but not sufficient conditions for operation ofthe cell next about it in the column, and in the opposite direction, the categories ofeach cell control the processes categorized in the one below it. For instance, thedefinition of an end or goal controls the selection of means for its attainment(Parsons, 1960, p. 477).


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Figure 3. The action system in relation to its environment.(Parsons, 1960, p. 476)

Interchange media.Parsons next postulated the means by which the 2 x 2 quadrants intercommuni-

cated. Each quadrant is a function and, to form a system, it communicates to and is com-municated from each other one. As one can see inFigure 4there are 12 such paths (lines

with arrowheads to and from each of the four functional prerequisites); it is not necessaryto understand everything in the figure. He called the paths interchange mediaand alongthem pass symbols, not (usually) physical objects. That is, each function produces andconsumes symbols, and that is how each function intercommunicates. One particularlysalient depiction of the interchange media isFigure 5, in which a cycle or phase move-ment is illustrated; note the (clockwise) sequence 1, 2, 3, and 4 among the functional pre-requisites in AGIL order. It is not necessary to understand everything in the figure, onlythe order in which the phases occur with respect to the situation of the organization.


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Adaptation

Latent Pattern

Maintenance

Integration

Goal

Attainment

Figure 4. Interchange media (whose paths are represented by arrows) inthe general theory of action. (Adapted from Parsons & Platt, 1973, p.

435); see also Parsons, 1977c, p. 263).

The intuition is that the Adaptation function scans and senses the external envi-ronment and might find some information there that could be imported as energy andpassed along (via the interchange medium) to the Goal Attainment function. The GoalAttainment function then might use that information either to change its goals or tochange its resource allocation. These changes, expressed symbolically as new goals ornew resource budgets, would travel along an interchange medium to the Integrationfunction. The Integration function would then decide how best to arrange the elements ofthe organization in order to achieve the goals in light of the resources. One can imagine,for example, goals around improved quality and productivity and these would get trans-

lated by the Integration function into organizational entities (e.g., VP of Quality or theQuality Improvement Department), job descriptions, new methods of rating job and unitperformance, new methods of incenting the desired behavior, new methods of recruit-ment and advancement, and new training. In turn these new structures and functionswould activate the Latent Pattern Maintenance function via an interchange medium andthe L function would respond, principally by trying to reset the organization to the statusquo in ante. L communicates via interchange media connected to the other three func-tions.

The L function works internally by manipulating a construct calledtension, whichis the difference between what the organization aspires (expressed by goals and resourceallocation, that is, the Goal Attainment function) and what it achieves. When achieve-

ment is low with respect to aspiration and the environmental situation, the L function ismore controlling, it tries to track more closely the energy being imported so that it canmatch the organization to the environment. Symmetrically, when there is little differencebetween aspirations and achievement, that is, when tension is low, then the L function isless controlling, more "quiet."


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Figure 5. Phases in the relationship of a system to its situation.(Parsons et al., 1953a, p. 182)

Recapitulation.To recapitulate the structure of the theory of action, the 16 possible combinations

of the four pairs of pattern variables gave rise to the 2 x 2 arrangement at the next higherlevel, the so-called AGIL framework that captures the functional prerequisites that everyorganization has to address to establish and sustain itself. The quadrants communicate viainterchange media and there is a priority of control in that communication, in accordancewith the cybernetic hierarchy.

As stated in SectionI, Introduction, no one knows a priori how much or little isneeded to simulate a particular social system. The researcher speculated that in order tosimulate the theory of action there must be at least representatives of the pattern vari-

ables, functional prerequisites, interchange media, and cybernetic hierarchy.Problem

The interface between description of systems and social action was informed bysoft systems methodology (Checkland, 1999; Checkland & Scholes, 1999). Checklandrealized that many "hard" engineering projects fail because they do not take into accountthe "soft" factors that humans introduce, such as the power structure around the project.He offered a step-by-step method for integrating hard systems and soft ones. His was a


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pioneering effort to integrate social and engineered systems, and was a source of inspira-tion for this research.

However, present computer simulations require specific details about the structureand behavior of variables and the interactions they animate. In addition, much of thework in social systems is limited in detailed description, what Checkland calls "rich

description." (Checkland & Scholes, 1999, p. 45). Thus, one of the problems is that eithersufficient data for detailed description or a comprehensive and appropriately complextheory (e.g., that with requisite variety (Ashby, 1956)) needs to be found, and then oneneeds to see if it is sufficient for a computer simulation to be constructed and operated.

More specifically, can Parsons large body of descriptive text be understood? Canthe salient factors (structure and function) be extracted? Finally, is it possible to instanti-ate, make concrete, those salient factors so that a high fidelity representation of thedescriptive theory of action can be constructed?

Even if the questions could be answered, one is left with: Are there any novelinsights? Is there anything useful to be learned? Can anything significant be predicted?Can the simulation predict something on which Parsons is silent? Is it possible to obtain

enough confidence in such an undertaking that it could function as "the right answer"?Asked a different way, "Is it possible to develop a laboratory replica of the theory ofaction, and if it is then can anything interesting be inferred from operating it"?

In addition, there is no published attempt that successfully simulates any part ofParsons theories. Also, there are few published applications of discrete event simulationto social systems. Therefore, this contribution is an early and humble set of results in theuse of that tool to be added to the existing scarcity.

Research questionThe question guiding this research was "What is the minimum set of structures

and related functions that can simulate Parsons theory of action to some criteria ofvalidity?" That is, what was the most parsimonious selection of theory of action con-structs that, when animated, achieved a given level of fidelity? Can the theory of actionbe simulated using only the functional prerequisites, (one pair of) the pattern variables,(four of) the interchange media, and the cybernetic hierarchy of social control.

SignificanceThis study contributes to the three areas traditionally addressed by social science

research: Theory building This work may enrich Parsons description by making con-

nections that Parsons did not, for example between the frequency of changesin the environment and the rate at which change can be sensed and incorpo-rated by an organization. In addition it may identify gaps in description, atleast gaps needing to be filled in order to simulate. In addition, this study willcontribute to the evolution of applying Parsons theory to additional contexts,following a long tradition (Black, 1961; Etzioni, 1975).

Methods This work may add methods of translating theory statements intostructure and function constructs. These constructs can in turn act as testablehypotheses amenable to a range of theory validation techniques. It also mayhelp to make the case for additional study of time-varying research.


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Theory (of science) This work may add a brick in the discussion of wheresimulation fits into the practice of science: it is a tool of theory understanding,a tool for theory building, and/or a tool for theory testing.

The reason "game" appears in the title of the dissertation is that there is somethingof a game that the user of the simulation described in this research can play by varying

the inputs and seeing what an execution will produce.8

SimulationThe conceptual framework for constructing a simulation from descriptive text

emanates from the flow from theory to action, Figure 6.Theory

Model

Constructs

Variables

Data

Analysis

Action

Figure 6.Flow from theory to action. (David Schwandt, personal communication)

Theories are our ontologies, they are the bases for our beliefs about what we canknow for sure (epistemology) and what constitutes valid activities to seek certainty(methodology). We extract from theories various features and organize them, calling thatorganization a model, which is the theory with some parts left out (that is, the translation

from the theory to the model is incomplete). The features and organization are at a levelof abstraction, usually the highest, the one with the largest blocks and thickest linesbetween them. Sometimes collections of the blocks and connections are named orrenamed. The thing renamed is called a construct. For example, we use the term "orienta-tion" to identify the performance and learning perspectives of Parsons theory of action.We invent the term "orientation" to be used in that sense. Constructs in turn are com-posed of variables, factors that take on different values, that is, that eponymously vary.The collection of values is called data, which are analyzed so that inferences aboutactions can be obtained.

The description of Parsons' theory of action forms the theory referred to inFigure6. The model in that figure is the same theory but only with certain (not all) elements and

connections and is the subject of this research. As stated above, one should at least beable to discern in the model to be presented the pattern variables, four functional prereq-uisites, interchange media, and cybernetic hierarchy because they are the cornerstones ofthe descriptive theory.

8 Using the terms described in the Conceptual Framework section, the "game" is to see whether latent patternmaintenance will follow the input energy.


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The goal of any simulation is to animate the elements, to put the time-varyingelements onto a "canvas" or work space where there "movement" through time cansomehow be visualized. In this research the canvas is a computer screen with a drawingresemblingFigure 5on it and "behind" the picture, in a way not seen by the user, thecomputer simulates the path of energy entering the organization and transiting in turn

through the AGIL cells. Details are provided in Chapter III.The simulation represents a set of choices and inventions.9 Explicating whatchoices are available and what choices were made and why is the subject of this sub-section. Farraro and Hummon (1994, pp. 29 ff), mirroring Fararo (1989, ch. 2), provide aconceptual framework for presenting the choices and for making clearer which parts ofthe simulation are provided by Parsons and which are provided by the researcher. Thereare six "key menus" that have to be selected and explained (these are categories and theirscales):

i. State space: categorical or continuousii. Parameter space: categorical or continuousiii.Time domain: discrete or continuous

iv.Timing of events: regular, incessant, or irregularv. Generator: deterministic or stochasticvi.Postulational basis: equations or transition rulesThe state space is the cross product the combination of all valid values of all

variables, including how the "boxes" are connected and what flows among them. In theinstant case the space is made up of category values, not continuous ones. For example,the Adaptation function is connected to the Goal Attainment function; both of thesefunctions are categories, as is "connected." Parameter space is the cross product of allfixed properties of the system. In this case, parameters include, but are not limited to:

The magnitude of energy entering the system A small integer, ordinal scale. Energy threshold; value that has to be compared and if true then the energy passes

into the system Same units as the magnitude of energy. Sense of the comparison test Category: >, >=, =,


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The time domain is described in discrete units. Parsons did not indicate whatreasonable time values were, so the researcher assumed that the basic unit was one day.Accordingly, one day passed for every click of the simulated clock, and all clicks occurin integer multiples: time is discrete, not continuous. The timing of events was irregularand depended upon what has happened before. In fact, the simulation clock did not click,

rather it moved ahead to the time of the next event and in general that interval cannot beknown a priori. And the state variables will only be defined for the discrete, integer timeunits.

By thegenerator of the process, Fararo and Hummon (1994, pp.30-31) signify themeans or mechanism by which the system produces changes in its state. The two mecha-nisms are by rolling the dice or determinism. Rolling the dice, or having the transition beprobabilistic, can be accomplished in discrete event systems; in fact, any probability dis-tribution can be imitated. Deterministic means that there is certainty (probability =1) thata state changes from the current one to the next. In the research described here, the tran-sitions were deterministic, there was no randomness to selecting the next state.10

Bypostulational, the authors mean the mechanism by which transition to the next

state is specified. Typically, in discrete event simulation the next state depends directlyupon the current state and the transition rules. For the research described here, the pri-mary transition rule was: when it is time for energy to move from one functional area tothe next, the system attempts the move; if the next functional area is already occupiedthen the energy is moved to a corresponding queue instead, otherwise it moves the energyto the (empty) functional area.

Which of the foregoing has been described by Parsons and which wasinvented/created by the research? The categorical state space has been specified in Par-sons, Bales and Shils (1953a) and so has much of the parameter space, though the actualvalues of the parameter space was assumed in the research; without loss of generality anyuser of the simulation can change any of the parameter values, so this invention does noviolence to the structure of the theory. That the time domain is discrete is a computationalconvenience and is not suggested one way or the other by Parsons. The timing of eventsas irregular is consistent with Parsons, Bales and Shils (1953a) and the other two options(regular and incessant) would not be. The deterministic generation of next states is im-plied in Parsons, Bales and Shils (1953a) because there are no probabilities mentioned orsuggested. And the postulational basis is clearly not equations, so transition rules are im-plied.

Therefore, to create a model to represent the dynamics of Parsons' scheme wedeveloped a system that managed energy in discrete units and moved those bundles ofenergy through the processes in accordance with the AGIL framework and governed bythe feedback and control hierarchy. Specifically, we envisioned a concrete organizationthat processed inputs from its environment, though perhaps Parsons would have arguedfor the generality of the processes at every level of analysis.

10 Here is an example of a probabilistic transition. Imagine a simulation of a retail store, such as a grocery. A shopperwould select a random number of items to purchase and that number would put the shopper into the cashier line forthe appropriate number of items, such as the regular line or 15 or less. It would be impossible to know in advancehow many shoppers ended up on the 15 items or less line because the selection is random and generated during theexecution of the simulation.


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LimitationsThe limitations of a study are those characteristics of design or method that set

parameters on the application or interpretation of the results; that is, the constraints ongeneralizability and utility of findings that are the result of the devices of design ormethod that establish internal and external validity. In a quantitative study the most

obvious limitation would relate to the ability to draw descriptive or inferential conclu-sions from sample data about a larger group.There are two viewpoints that both properly identify this first attempt at simulat-

ing Parsons theory of action:1. Thorngate (1976), in attempting to describe the range of explanatory power of theory,

drew the one-armed clock inFigure 7. He stated that a particular model or theory can-not simultaneously be general, simple, and accurate. Rather, the researcher must tradeamong those outcomes. Clearly, the research described here was simple, so it wasneither general nor accurate. Accordingly, the results will have to be used with greatcare (not general) and will not apply to any actual social system (not accurate).

General

SimpleAccurate

Figure 7.Thorngates one-armed clock.(Adapted from Thorngate, 1976, p. 406)

2. Thomsen, Levitt and Kunz (1999) suggested that simulations go through stages,Figure 8. The first stage is to build a "toy" to see if the simulation can even be builtand whether it will have interesting properties. Again, clearly that was the stage of thesimulation presented here. Accordingly, the results are vigorously disclaimed as amodest first attempt, really a toy, that may not be applicable to any set of facts, butrather should be seen as a foundation to be enhanced and expanded. Indeed, someelements of the simulation were given arbitrary values in order to achieve simplicityand the arbitrariness detracts from the significance of the outcome (Fararo &Hummon, 1994).

This theoretical approach to models [theory in mathematical form] included theidea of "successive approximation" articulated in sociological theory first byComte, then by Pareto and the later stressed by Homans. Models were notexpected to be correct in every detail nor to cover the entire potential scope ofinterest in a class of phenomena. They were to be modified and generalized (in aformal sense) over time. Even though such a model might include entities andprocesses not presently observable, the logical connections among ideas in a con-ceptual network assured that the theory was testable. (Fararo, 1984, p. 152)


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Figure 8.Evolution of computer simulations of organizations.(Thomsen et al., 1999)

As stated in the Introduction, the purpose of this dissertation was to report on afirst attempt to simulate Parsons theory of action. Accordingly, the study did not seek tooperationalize or transform into constructs everything Parsons wrote on the subject, but

rather it functioned as a starting point of a single working simulation. Even applying thatworking simulation will leave much for future research. It was necessary to select the fewconstructs that formed the kernel of this simulation from all of the possible candidates.

At the outset these additional limitations have been identified inTable 2.Table 2.Additional limitations of the study

Origin of limitation Limiting action

Parsons never intended his description ofthe theory of action to be granular enoughto support simulation. He stated that his

theory was not at the logico-deductivestage yet (Parsons, 1961c, p. 321). Therehave been other attempts to identify propo-sitions in Parsons work and to test whetherthey form a set that is logical in the sensethat conclusions can be deduced from thosepropositions (Brownstein, 1982). Thoseother attempts have found gaps in Parsons

It is not known why Parsons theory cannotbe simulated unless and until there hasbeen an attempt. On the other hand, Jacob-

son and Bronson (1997) reported failure,and they are experienced, published soci-ologists and modelers. Also, in fairness,Parsons (Parsons, 1968a, pp. 77 ff) contra-dicted his own observation by providingsome formalization that could have beeninterpreted as a beginning of a logico-deductive base.


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reasoning that Parsons acknowledged anddoes not apologize for because the theorywas never intended to be "logical" yet.

Parsons was a prolific writer. He has beenroundly criticized for being difficult to

understand (Selznick, 1961)11; (Kolb,1962)12; (Bressler, 1961)13. One reason forthe criticism is that Parsons would write asentence and then in the next use differentterms for what appeared to be the samethought. Was Parsons restating the previ-ous sentence but in a different way aimedat increasing our understanding throughredundancy or repetition or was he sayingsomething that was (slightly) different thanthe first sentence?14 Parsons writing style

confounds understanding, which was aproblem because the study sought a deep,detailed understanding so that it illustratedthe theory by replicating the understandinginside a computer.

Identify a single work (Parsons et al.,1953a) and acknowledge the implications

on generalizability.

One never knows when to stop trying toincrease the fidelity of a simulation. This isa problem with all simulations. It isequivalent to the question of validation:when is the computer simulation suffi-ciently like the Real World to be trusted?

One can always try one more interestingcase, one more tweak that will increasefidelity.

Use the heuristic: can the computer simu-lation serve as a foundation for furtherresearch work where only incrementalenhancements would be needed, notwholesale simulation changes. The simula-tion constructed here has instances of many

of the important structures and functions,so that additional structures and functionscan be based on those already represented.

It is tempting to label simulation as reduc-tionist, an especially unfortunate moniker

Keep the unit of analysis at the system,structure, and function levels. Do not per-

11 "It is a case of the Emperor's clothes. Is his [Talcott Parsons'] complexly textured raiment really there? Or is it all (or

largely) an illusion, a conjuration, a bad and costly joke?" p. 932 "The problem of arriving at a reassured assessmentof Parsons' thought is greatly complicated by a remarkable obscurity of structure and style. Even those accustomedto abstract philosophical discussion find it a considerable chore to decide what is being said on any page, let alonealso to assess its intellectual worth. I suspect that a great many sociologists, otherwise sympathetic to the need forgeneral theory, have simply abandoned the effort." p. 932

12 "The essays ... establish beyond question ... the difficulty of understanding his [Parsons'] work at any but the mostgeneralized level." p. 590 "... [T]here is concern with the obscurity of Parsons' language, the shifting meaning ofsome of his terms, ..." p. 591

13 ""His detractors have chided Parsons for a linguistic style which reads like pure hardtack." p. 149

14 For example: "This conception of the orbit of the action-process is integral to that of phase movement which willfigure prominently in our subsequent discussion. It is applicable both to the unit and to the system as a whole, thelatter distinction being a matter of points of reference, not of the concrete structure of processes." (Parsons et al.,1953a, p. 164) In the second sentence to what does "It" apply? Orbit? Phase movement? Subsequent discussion?


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when applied to a holistic theory as Parsonspurported his to be. The challenge was tomaintain the holistic nature of the theory ofaction and simulate something that iswhole. The next level down of this chal-

lenge is that Parsons described the func-tional components of the theory of action interms that looked like tokens that travelalong wires (media of interchange) amongnodes (functional prerequisites). Therefore,the simulation can have the appearance ofrats in a maze because at some level thatresembles Parsons description.

mit manipulation or reporting at the atomic(what Parsons calls the unit) level. This isconsistent with Parsons' view that the unitact cannot be viewed by itself but rather ina much, much larger context.

Simulation often postulates a sequence ofstates through which the system passes.Simulation, then, presents the states that

were encountered, but not all of the possi-ble states.15That is, simulation cannot givethe richness that a grammar or contingentapproach could (Fararo, 1984, p. 146).

Noted as the nature of simulation vs. a pro-duction system (i.e., grammar) orientation(see Fararo & Skvoretz (1984) for an

example of the production systemapproach, described above beginning on p.32).

It may be worth mentioning that a significant limitation is that elements outside ofParsons' theory are outside of the simulation of it.

15 This is the same distinction in biology between ontogeny (an individual instance seen in nature) and phylogeny (allpossible instances for a species), between genotypes (the expression of genes found in an instance) and phenotypes(everything that is possible genetically).


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II. LITERATURE REVIEWThe review of the literature is divided into parts. The first part examines the ques-

tion of what is a theory, what is a model, and how does simulation interact with them.The theory to be simulated is reviewed next, with an eye on a particular articulation fromParsons himself. The salient features are identified, as they formed the basis of the selec-

tion of the subset of all constructs that shape the simulation. The review then shifts to theart and science of computer simulation applied to social science theories.Theory, model, and simulation

Simulation-building and theory-building are identical in their notional steps (thesteps are from Hanneman (1988)):

1. Define boundaries of the system.2. Define the elements of the state space and partition the state space into

subsystems.3. Describe the connectivity of the state space elements, and the forms of

relations among the states of the system.4. Define the dynamic aspects of the relations among state space elements.

Simulation is a not the real thing, it is an imitation. In the instant case it is very farremoved from anything real because the research here is a simulation of a theory and thattheory has never been asserted to be related to reality: Parsons' theory is a frame of refer-ence. "In a certain sense, all theories about social action and interaction are simulations theories are designed to mimic (albeit in highly selected and abstract ways) characteris-tics of real social action." (Hanneman, 1988) Baudrillard (1995) has coined the termsimulacra for a copy without an original. One committee member remarked that this dis-sertation was likeThe Matrix, a popular movie that incorporates much of Baudrillard(1995), especially the question of simulacra, in it, where it is difficult for the viewer totease out what is real and what is simulated.16 In fact, simulation is also the name of asocial theory that addresses the problem that so much of the culture of developed coun-tries is simulated, not real, put there by advertising and other media (Cubitt, 2001). Thisdissertation does not use simulation in the sense of a stand-in or substitute, but rather inthe sense of an animation or reification, a coming to life of something inanimate (in thiscase a theory). Again, the simulation is not the real thing, the real thing is Parsons' theoryof action.

The theory of actionParsons traced the history of the development of the theory of action in Parsons

(1977a). He came to sociology from economics, starting in about 1930. "It graduallybecome clear to me that economic theory should be conceived as standing within somesort of theoretical matrix in which sociological theory was also included." p. 24. Parsonsstudied and tried to find the common threads among Alfred Marshall, a dominant Englishneoclassical economist (one of his students was John Maynard Keynes); Vilfredo Pareto,an Italian economist and sociologist; Max Weber, a German scholar who had ideas on thenature of modern capitalism and how to organize for economic gain; and Emile Durk-heim, a French scholar who, among many other subjects, wrote about the division oflabor. Parsons' effort culminated in 1937 in the two-volume work (Parsons, 1968a;

16 One sight gag is when the protagonist, Neo, gives some contraband diskettes to "clients." He hides those diskettes ina hollowed out edition of Baudrillard (1995).


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Parsons, 1968b). "The most immediate interpretative thesis was that the four and theydid not stand alone had converged on what was essentially a single conceptual scheme.In the intellectual milieu of the time this was by no means simple common sense."(Parsons, 1977a, pp. 25-26)

The conceptualization that Parsons created flowed from his observation that the

theories of Marshall, Pareto, Weber, and Durkheim had in common an action system,first suggested by Weber and then elaborated by Parsons; the result of the conceptualiza-tion was Parsons theory of action (Parsons, 1968a). That is, what these seemingly dispa-rate writers described in common was a system of actions, human actions that had pat-terns that could be described in accordance with a framework. Parsons has said thatscientists of his era were informed by the progress in the conception of systems usingmechanics and physico-chemistry (Parsons, 1977a, p. 27). In those disciplines one startsat the atomic level and defines what is meant by a "unit."

Accordingly, Parsons started by defining the "unit act." (Parsons, 1968a, pp. 43ff):

(1) It implies an agent, an "actor." (2) For purposes of definition the act must have

an "end," a future state of affairs toward which the process of action is oriented.(3) It must be initiated in a "situation" of which the trends of development differin one or more important respects from the state of affairs to which the action isoriented, the end. This situation is in turn analyzable into two elements: thoseover which the actor has no control and those over which he has such control.The former may be termed the "conditions" of action, and latter the "means."Finally, (4) there is inherent in the conception of this unit, in its analytical uses, acertain mode of relationship between these elements. That is, in the choice ofalternative means to the end, insofar as the situation allows alternatives, there is a"normative orientation" of action. (p. 44)

Tension management and learningOne of the functions of Latent Pattern Maintenance is tension management. Ten-

sion is the diffe

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