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Subject:

Fwd: Theory and Simulation

From:

Nigel Gilbert <[log in to unmask]>

Reply-To:

Nigel Gilbert <[log in to unmask]>

Date:

Thu, 13 Nov 2003 23:44:43 +0000

Content-Type:

text/plain

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> ----------
> De:   Nigel Gilbert[SMTP:[log in to unmask]]
> Enviado:      viernes 14 de noviembre de 2003 0:44:43
> Para:         [log in to unmask]
> Asunto:       Fwd: Theory and Simulation
> Autorreenviado por una regla
>
Begin forwarded message:

> From: "Barry Markovsky" <[log in to unmask]>
> Date: Thu Nov 13, 2003  5:44:27  pm Europe/London
> To: <[log in to unmask]>
> Subject: Theory and Simulation
>
> This post was rejected, perhaps because it was sent via an account
> different from the one I subscribed with. Could you please post it for
> me?
>
> Thanks,
>
> Barry
>
> =========================================
>
> I want to expand on Alan Penn's comments (below) because I think there
> are some common misunderstandings and misuses of simulations in
> sociology that we need to battle.
>
> Say you start with a typical discursive sociological theory, and you
> want to write a simulation that is in some sense designed to reflect
> the
> claims and explanatory mechanisms of that theory. Invariably, you are
> forced to make numerous judgments and choices along the way in order
> to
> make the simulation run, especially in regard to which factors
> mentioned
> by the theory are needed and which are not, and the functional forms
> that will relate those factors to one another in the simulations.
> Moreover, writing the simulation almost certainly will reveal logical
> gaps in the theory that must be filled in order to make the simulation
> work.
>
> In the end, the simulation embodies a set of logical assumptions (or
> axioms or propositions or postulates or premises--whatever you choose
> to
> call them), and the simulation's output represents a set of logical
> derivations (or conclusions or theorems or deductions or
> consequences...). How does this relate to the original theory? At
> best,
> VERY loosely. The simulation introduces functional relationships that
> the theory does not specify, and usually specifies gap-filling
> assumptions that the theory never made. This breaks the logical
> connection between theory and simulation. They become distinct logical
> entities. That there may be some shared terms, and perhaps some
> correspondence in the directions of some specified functional
> relationships, still is insufficient to establish a consistent logical
> connection between the theory and simulation.
>
> If there is not a consistent logical connection between simulation and
> theory, then the output from the simulation has no bearing whatsoever
> on
> the theory and cannot in any sense be a "test" of the theory. To see
> this another way, it may help to realize that when writing "tight"
> simulations inspired by "loose" theories, there are many degrees of
> freedom in specifying assumptions of the simulations. If different
> people wrote different simulations based on the same theory, they
> would
> obtain different output patterns because of this. There may be some
> loose similarities in those outputs, but they literally will be
> mutually
> contradictory. And the looser the original theory, the greater the
> chance that some of the simulations will even contradict even the most
> basic general predictions the theory makes.
>
> So, if it is possible to have multiple, mutually contradictory
> simulations "from" (or inspired by or "built on top of") the same
> theory, then such a theory is logically worthless. (Remember
> elementary
> logic? If you can derive a contradiction from a given argument, then
> that argument is invalid.) The simulation or simulations represent
> improvements over the original theory, and if there are multiple
> simulations with mutually contradictory derivations, they are all
> improved versions of the theory (at least from a logical standpoint)
> and
> may be adjudicated by empirical testing.
>
> By this view, every simulation provides an explanation: Their
> statements
> and functional relationships constitute the explanations for the
> patterns of output they generate. Certainly Sugarscape accomplishes
> this
> (as Mike points out below), and so do countless others. A reader may
> feel that such an explanation flawed or insufficient, but then the
> burden is on the reader either to show how the simulation fails to
> account for the phenomenon it intended to explain, or to provide an
> alternative theory or simulation that provides a superior account.
>
> Barry Markovsky, Chair
> Dept. of Sociology
> University of South Carolina
> [log in to unmask]
>
>
> -----Original Message-----
> From: News and discussion about computer simulation in the social
> sciences [mailto:[log in to unmask]] On Behalf Of Michael Sellers
> Sent: Thursday, November 13, 2003 7:36 AM
> To: [log in to unmask]
> Subject: Re: Simulation and Explanation
>
>
>
> Alan Penn wrote:
> "Can we broaden the question - can anyone think of excellent examples
> of
> simulation providing explanation in any field (let alone sociology).
> It
> seems to me that simulations (at their best) are built on top of
> pre-existing explanatory theory, they may act as tests of those
> theories, but in a true Popperian sense, can do little to confirm only
> perhaps help falsify them."
>
> --
>
> If this is true of simulations, it would seem to be true of any social
> investigations.  Simulations are no less (and often more) capable of
> setting up falsifiable hypotheses than are _in situ_ investigations,
> especially given the lens of explanatory pedagogy through which all
> social research is necessarily viewed.
>
> And it is not the case, I think, that simulations are limited to being
> built on top of pre-existing explanatory theory; this is the "magic"
> of
> emergent phenomena.  For example, in the simplest of simulations of a
> grid of blue dots and red dots, there's no way to predict in advance
> that the two simple rules that "dots of the same color like to be
> beside
> each other, but will not move away from dots of the other color" will
> generate strongly segregated populations: but they do.  This is
> perhaps
> the simplest and most direct example of social emergence that I know
> about.  This isn't a case of the end being "built in" from the
> beginning; it is instead a simple but dramatic example of how very
> simple distributed (no centralized authority or director) behaviors
> can
> result in _en masse_ (i.e. societal) changes.
>
> I mentioned the Sugarscape work earlier.  While this is still a fairly
> simple simulation, Epstein and Axtell were able to show a great many
> emergent phenomena such as the emergence of trade, culture, wealth
> accumulation, etc.  And they were able to make explanatory statements
> such as why decentralized trade increased *both* the polarization of
> wealth accumulation (the rich get richer) AND the overall carrying
> capacity of a society.  That is, the more a central authority tries to
> enforce equality, the fewer people the society can support.  That may
> sound paradoxical, but their simulation shows this clearly -- and it
> is
> not simply "built in" from the start.
>
>
> Mike Sellers
> Online Alchemy
>
>
>
________________________________________________________________________
__
Professor Nigel Gilbert, FREng, AcSS, Pro Vice-Chancellor and Professor
of
Sociology, University of Surrey, Guildford GU2 7XH, UK. +44 (0)1483
689173

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