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Carlos,
There was no contradiction between what Tim wrote and what I wrote:
nobody could possibly write all there is on any given subject when it comes
to human intellectual interaction with the world.
Measurement is not only a technological activity. All observations
are forms of measurement, having been "encoded" into perceptions which are based
on sensory input by our various combined powers of detecting some of these
emanations from the world around us (the "ambience"). Observations further
become "formalized" measurements as they are translated (encoded) into some sort
of record via a particular language. So, for example: as soon as you write
down a description of some observation you've made, you've created and encoded a
measurement or an entire set of measurements. The description may be simply a
prose-based chronological account of what you observed; or it may be a
visual representation as your eyes/mind saw it (a painting or sketch); or it may
be represented in a more traditional scientific language such as via
numbers...
These all represent ways of recording information about an
observation-- and it's worth noting that each of these ways of
encoding will record different information-- different aspects of the
observation. We have created technologies to perceive and measure all
sorts of things that our own natural senses can't detect, like radiation or
certain wavelengths of light, sound, etc. However, any mode of measurement is
going to do a few things: 1) It's going to leave information about the
system out. 2.) It's going to create new information, pertaining to the
observer/measurer and possibly about other aspects of the measurement mode (the
way of encoding information) which will become an innate aspect of
the measurement itself. In other words, all modes of encoding/measuring
will add information to the measurement that doesn't actually pertain to the
system. Some modes of measuring/observing create more new information than
others in any given situation or context. Some modes leave more information
out than others, depending on the situation and context. And some
modes actually destroy that which they measure, which creates vast amounts
of new information as part of "the measurement" (E = MC2 comes to
mind).
Clearly, one of the skills of science is to know about this
aspect of measurement and to assess the modes at one's disposal so that one
is able to make intelligent choices about which modes to apply in any
given situation and so forth. Science often records the measurement mode as
well as the measurement, but often this aspect of measurement/recording is
forgotten or ignored. This is why it is so important not to equate the
actual system with any set of measurements of it. In other words, any formalized
version we create of a natural system is going to be incomplete and it may also
be contaminated with new information that does not pertain to the system,
itself. Another skill that science has to develop, according to Robert Rosen, is
the ability to assess the nature of the system we want to learn about and to
know what sorts of measurements to take and which modes of
measurement are appropriate-- for the type of system under study.
His view was that we need to be able to assess the organizational type, before
we can make any other choices, and we need ways to measure the nature
of relational aspects in order to do that. He suggested several ways he had come
up with for achieving this and he pointed out avenues for many more
ways to be developed. We have discussed quite a few of them on the list, in
fact.
This is a critical issue, because complex systems require entirely
different scientific treatment than simple systems do and they also require
different modeling techniques.
A model is a collection of various measurements of all sorts,
reassembled into a new system that is intended to be analogous to the original.
What my father did was to analyze what this process is actually intended to do:
to recreate the entailment patterns of the system (at least,
insofar as they are part of the aspects being modeled). So, his analysis of the
process of creating a good, working model that will commute with the system
being modeled was the diagram that you are describing:
RR wrote: "The crucial ingredients are the
arrows 2 and 4, which
I call encoding and decoding, respectively. (I have discussed the anomalous features of these arrows in more detail in Life Itself, section 3H.) They do not fit entirely inside either the object system or the model; they do not represent entailments, nor are they themselves entailed. They manifest what Einstein (with Infeld; 1938:33) once called "free creations of the human mind," on which he believed science depends. They introduce an obvious further semantic element into the model, over and above what semantic (e.g., nonformalizable) features may already be present in the model." He is pointing out that any effort to model a natural system is
going to have to go through this process. The part of the process that creates
the model is the encoding process. The part of the process that tests
the model against the original system to see if it "commutes" is the
decoding process. Are you with me, so far?
Now this is where the arrows in his diagram come into play:
Step 1.) First, think about the various well-known models employed
by science and medicine and industry... maybe it's the use of the laboratory rat
as an experimental model of a human being... maybe it's the use of actuarial
tables for use in the life insurance industry to predict how expensive you're
going to be to insure, based on their predictions of when you're going to die...
maybe it's the weather system models, which all disagree with one another on the
evening news...
Step 2.) The encoding arrow: None of these models tell us
how they were created or decided upon. In fact, it would take a lot of detective
work to find out and sometimes it's just impossible. but it may be critical
information. However, that's not information we can get from the model; it has
to come from the modeler/s. Similarly, no natural system tells us how to best
model it. That is information that is not in the natural system. We've developed
that on our own, as a means to an end; namely to try and learn more about a
system by recreating its entailment patterns. "They manifest what
Einstein (with Infeld; 1938:33) once called "free creations of the human mind,"
on which he believed science depends." And so, the process of encoding
that is used to generate a model is one that is not entailed by the system and
not entailed by the model.
Once we achieve the creation of a model, we want to use it
to learn more about how the actual system will behave, IF....
; In other words, we want to predict future causality, by running certain
exercises through our model.
Step 3.) The decoding arrow: This situation, again, refers
to testing the model against the original system. The process for doing
so is not information that is part of the model, nor is it part of the
actual system. In other words, neither the model nor the actual system ENTAILS
the decoding process; the decoding process is another "free creation of the
human mind".
Encoding and decoding pertain to science. Science is a human
creation. Do you see what I'm getting at? It's not that the encoding and
decoding arrows are not entailed at all, it's that they are not entailed in the
diagram-- not entailed by either the system or the model.
Does he believe that the act of measurement is a "free
creation of the human mind" and "introduce an obvious further semantic element into the model, over and above what semantic (e.g., nonformalizable) features may already be present in the model"? Suppose I want to calculate the translational kinetic energy of a body, using the simple formula Et = 1/2m*v^2. Is Rosen suggesting the measurement instrument I use in order to determine the mass of a body introduce "an obvious further semantic element"? You bet. He most certainly IS suggesting that it introduces a
further semantic element into the model or the measurement. It absolutely
does. "The measurement instrument" and the measurement process, and the aspects
of the system you have chosen to measure that will give you a number
that you label "mass"....., these are ALL semantic elements that are not part of
the system itself. These tell us as much about the science involved as they
do about the system.
Judith
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