Science or Mush

[From Bruce Abbott (950629.2200 EST)]

Dag Forssell (950629 1500) --

Dag, when I was visiting Gary Cziko I had the opportunity to view one of
your videos; you do a very nice job of presenting PCT to the business
community. I don't know what Gary has against you, but he thought we look a
bit alike. (;->

I continue to appreciate and enjoy the discussion of reinforcement
theory. A great number of differences have been clarified. The
discussions are important since the basic notions of Reinforcement
Theory is engrained in the minds of not only psychologists, but
most lay people as well. You are playing the role of interpreter
and devil's advocate well, Bruce. So well, that I often have to
pinch myself to recall your stated objective, which as I understand
it is to merely offer arguments that are to be expected from those
with a reinforcement point of view.

Let there be no confusion: I am no fan of reinforcement theory. In fact on
several occasions I've complained about being asked to play the role of
resident reinforcement theorist (computing epicycles and such) but then I'm
asked to develop reinforcement models and defend them. I'm in a no-win
situation: if I do then I'm covertly trying to convince everyone that
reinforcement theory is correct and if I refuse then I'm admitting that the
theory can't handle data which I firmly believe it can. Yet it is my view
that it is possible to build strong bridges between the PCT and EAB camps,
but to do so it is first necessary to explore the relationships between the
two sets of concepts and the experimental findings to which they relate.

One of the best ways to do this is to construct models based on both views
that apply to the same experimental situations, compare them, and tease out
their implications. I believe that in many cases the two theories are
simply using a different vocabulary to talk about a common set of phenomena.
The analyses are different, and because of this the constructs do not
translate directly one into the other, but at least there are points of
contact.

For example, in EAB food deprivation is said to be an "establishing
operation" that confers a certain level of reinforcing value on a food
pellet (as, by the way, perceived by the organism; value is not conceived as
something that exists objectively in the food); in PCT we would say that
food deprivation creates an error in a system controlling nutrient level.
In both views the result is that behavior which tends to put food in the
mouth is expected to be vigorously executed ("highly motivated"). When
someone in EAB asks me to explain relationships such as the effect of
deprivation on rate of lever-pressing on, say, a VI schedule of
reinforcement, I'd like to be able to explain clearly how PCT constructs
like controlled variable, disturbance, reference level, and error relate to
those phenomena.

I think the exercise is also worthwhile in that I'm getting a better grasp
of the real weaknesses of the reinforcement view. This comes from
attempting to construct specific models to deal with specific situations.
The weakness are not so much that reinforcement theory cannot account for
certain data, but that it is not sufficiently developed to do more than make
educated guesses as to how it might apply. For example, on what basis does
one adopt a model for a specific effect of reinforcement on response
strength? For a quantitative model, one has to do more than simply state
that reinforcement strengthens the response that produces it. Different
theorists have offered different answers: reinforcement "theory" is not one
theory but a whole family of competing views built around a common core.

Your statement above -- "Well, these guys aren't reinforcement
theorists, they're just humble experimentalists reporting their
data." -- offered with an apparently straight face is a sad comment
indeed. Surely these are psychologists with PhD's??? Was this
research report reviewed by a committee of expert peers before
publication? If so, did they not understand either?? Is
Reinforcement Theory so obscure and convoluted that a division of
labor as you indicate is called for? It comes across as a giant
cop-out in a way that I think unthinkable in the physical sciences.

Skinner believed that the empirical work of parametric manipulation would
provide a secure base on which a sound theory of behavior would eventually
be constructed, and much of the experimental work in EAB continues in this
tradition. The idea was that the explanation could wait until the phenomena
to be explained had been described in detail; the observations were primary,
and what any theory would have to explain. This empirical attitude still
permeates EAB.

Skinner's view was a reaction to the disaster that befell the field of
learning when, during the 40s, most research being conducted on learning and
behavior was aimed toward testing Hullian theory against competing views.
Most of this research required setting up rather special conditions; when
the theory fell, the data were no longer of any interest and the research
became wasted effort. Skinner felt that research aimed at discovering
well-defined functional relationships would produce data that would continue
to be of lasting value regardless of the status of any theory which
attempted to explain them. So, what you do is vary the ratio requirement
systematically, and report how behavior changes with the ratio. You get
Motheral's curves, and those curves present a set of findings any adequate
theory will have to explain. Theory is secondary.

In a sense these researchers are like naturalists going out into the rain
forest to collect specimens. They come back with something new, and note
that it doesn't seem to fit easily into the current taxonomy. They just do
the research--fixing the taxonomy is somebody else's problem.

But this is not to say that the field lacks its theorists. We just haven't
been talking about them.

Bruce, you have claimed that you are a PCTer, but claiming it does
not make you one. Please save me from having to pinch myself
bloody by following through on your promise to Rick two weeks back:

One thing at a time. At the moment I'm interested in looking carefully at
these ratio data, from _both_ the PCT and reinforcement perspectives, to see
what I can learn.

I will welcome some posts from you where you
show in-depth understanding of PCT, not just Reinforcement Theory.

Wait 'till you see my PCT model of the ratio data. I hope Bill doesn't
preempt me by presenting his first. And by the way, this won't be the first
time I've developed a PCT model. What kind of proof are you looking for?

Regards,

Bruce

[From Dag Forssell (950630 1855)]

[Bruce Abbott (950629.2200 EST)]

  Let there be no confusion: I AM NO FAN OF REINFORCEMENT THEORY.

    In fact on several occasions I've complained about being asked
    to play the role of resident reinforcement theorist (computing
    epicycles and such) but THEN I'M ASKED TO develop reinforcement
    models and DEFEND THEM. I'm in a no-win situation: if I do
    then I'm covertly trying to convince everyone that
    reinforcement theory is correct and if I refuse then I'm
    admitting that the theory can't handle data WHICH I FIRMLY
    BELIEVE IT CAN. Yet it is my view that it is possible to build
    strong bridges between the PCT and EAB camps, but to do so it
    is first necessary to explore the relationships between the two
    sets of concepts and the experimental findings to which they
    relate. [CAP emphasis Dag's]

Bruce, thanks for your reply. I have no quarrel with your models,
arguments, or beliefs and I appreciate your intentions. I am just
impatient. Seems to me that if you firmly believe that
Reinforcement Theory (whatever it is -- you have suggested that PhD
EAB researchers don't know :slight_smile: ) can handle data, it is only
natural that you volunteer (you have not been asked as far as I
know) to defend the reinforcement models you develop. To say that
you are no fan of Reinforcement Theory signifies that you have some
vague, perhaps mild problems with it -- I guess. PCTers are likely
to read into your statement their own more fanatic interpretation:
Reinforcement Theory is worse than useless. When you subsequently
do not appear to think that Reinforcement Theory is worse than
useless, PCTers do not take you seriously when you claim that you
are a PCTer.

  Skinner believed that the empirical work of parametric

    manipulation would provide a secure base on which a sound
    theory of behavior would eventually be constructed, and much of
    the experimental work in EAB continues in this tradition. The
    idea was that the explanation could wait until the phenomena to
    be explained had been described in detail; the observations
    were primary, and what any theory would have to explain. This
    empirical attitude still permeates EAB.

This is interesting. A major problem with this approach is that
some theoretical construct automatically is incorporated into the
supposedly objective observations. If the naive, underlying theory
is backward, then all the empirical observations become useless.

  Skinner felt that research aimed at discovering well-defined

    functional relationships would produce data that would continue
    to be of lasting value regardless of the status of any theory
    which attempted to explain them... ... Theory is secondary.

I understand that Skinner said this. Yet, since we construct our
own perceptions using existing, perhaps unspoken, understandings,
that understanding/theory is primary. Theory, even in the form of
unspoken, vague hunches, determines what and how we observe.

  In a sense these researchers are like naturalists going out

    into the rain forest to collect specimens. They come back with
    something new, and note that it doesn't seem to fit easily into
    the current taxonomy. They just do the research--fixing the
    taxonomy is somebody else's problem.

This is no way to develop serious science, as you apparently agree.

  Wait 'till you see my PCT model of the ratio data. I hope Bill

    doesn't preempt me by presenting his first. And by the way,
    this won't be the first time I've developed a PCT model. WHAT
    KIND OF PROOF ARE YOU LOOKING FOR?

It is relatively easy to develop a technical understanding of PCT
and HPCT. A fair number of people have done so and moved on. It
is another matter to internalize the concepts and recognize the
implications. The latter is what I am looking for.

Towards end of the foreword to _Stations of the Mind_ (available on
the PCTtexts disk and WWW in the file GLASSER), Bill writes that he
has never seen anyone grasp and internalize PCT in less than two
years. (I would nominate Bill Leach as an exception.) I think
HPCT shows us why this is so. The new concept is so basically
different that once it has been understood at a superficial,
technical level, problems crop up -- some of them severe. As you
experience life and consider the explanations you were taught and
internalized long ago, you find that they do not fit with the new
explanation. Something has to give, and it seems a majority take
the easy route to stay with the familiar. It takes a lot of time
to work through your inventory of old (mistaken) convictions and
one by one replace them with new clarity courtesy of HPCT. It
takes uncommon dedication to do this. You have demonstrated plenty
of staying power so far and I for one appreciate you for that.

I would urge you to read the file EPIPHANI.ES on the same disk (or
at the WWW address) for a further discussion of the problems of
"getting" PCT, if you have not already done so.

It seems to me that the small fraternity of people who "get" PCT
find it compelling and come to "feel it in their bones." Everything
you experience and think about is illuminated in a new way when you
"get" PCT. This is why PCTers can come across as fanatics. We
are. But (unlike religious fanaticism which looks similar) this
reflects a conviction based on experience and tests that anyone can
replicate in their own experience. Any mechanical engineer who
understands Isaac Newton's three laws of motion is confident in the
same way, but does not come across as a fanatic since there is no
institutionalized misunderstanding in that field any more. There
is no need to tilt against windmills of institutionalized
misunderstandings in the field of engineering. There is in the
life "sciences". The fact that the principles of PCT and to a lesser
extent HPCT can be replicated 100% in tests at any time puts it in the
camp of physical science. Reinforcement Theory as you describe it
does not belong among the physical sciences at all. To me it is not
science.

This makes it hard to build bridges: The concept is opposite --
really alien and uncomfortable -- and practitioners of
Reinforcement Theory by and large are not trained in the physical
sciences. Therefore they have not experienced explanations that
describe functional mechanisms. I believe they see all phenomena
as magic, as when you turn the key to the ignition in your car and
the motor starts.

The vast majority of lay people do not care to understand the
multiple mechanisms behind the motor starting in a car. They are
apparently satisfied that it starts as if by magic. It becomes
difficult to separate an explanation that invokes magic from an
explanation that offers functioning mechanisms if you have never
studied functional mechanisms in some detail. In this way I
presume most EAB people are lay people, incapable of distinguishing
a theory that invokes magic -- Reinforcement Theory -- and "works"
some of the time at best, from a theory that offers testable
functional mechanisms -- PCT and HPCT -- and works 99+ % of the
time. We are comparing apples and oranges in the worst way. (I
would be pleased to be shown that my prejudices are mistaken, but
I have little indication that physical science is a prerequisite
for the study of psychology. Psych is a "fuzzy" comfortable
subject, not a demanding "techie" one). Note that the rigorous
application of statistics does not make it into a physical science.
The abuse of statistics has been thoroughly discussed on CSGnet.

I agree that it is highly desirable to explain PCT to EABers and
Reinforcement Theorists, but think that Thomas S. Kuhn shows us
that they are unlikely to A) be interested B) "get" it, and that
HPCT shows us why. Once you have been taught principles and
systems concepts and decided to believe in them, you control by
them. Any statement to the effect that what you believe is wrong
is only a disturbance which is resisted. Seems to me that the
control all of us exercise in defense of what we already believe in
(no matter what it is) is incredibly strong.

This is why I personally do not try to reach people trained in this
field. I prefer to avoid them in order to save my strength and
resources for a (hopefully) more receptive audience. I think PCT
and HPCT will ultimately prevail for sure. I believe the
successful route will prove to be an end run around the existing
behavioral "sciences", but support and applaud your work with Bill
and Rick to address the EAB community head on.

Now you know more of where I am coming from. I hope we can meet at
the conference in 1996, if not sooner. Shall we shave face to face
with a pretend mirror as they do in commercials? Wouldn't that be
a fun control experiment?

Best, Dag

[From Shannon Willyams (951103)]

Bruce Abbott (951102.1115 EST)--

If the cat lacks the capacity to reason it out, to develop and test
hypotheses, what other mechanism might lead to a workable solution?

My guess would be some kind of "coincidence detector."

Maybe. But (I think) learning is only evolution. The mechanism for
learning needs to follow the same general principles as other evolution
mechanisms. A small nub of knowledge/theory begins and then grows.

In any case there is no way to test the "coincidence detector" concept yet.
You need to atleast determine a method by which a coincidence is
identified, and then determine if this method is used.

Hans Blom (951101) has already proposed a mechanism similar to the one I
have just described:

In my view, the cat was trying to solve a
problem; to gain control, one might say, over its situation. Then
suddenly, unexplainedly, the solution was there and, moreover, was
immediately recognized as such. A far more important event, I think,
than "the door simply fell open by itself". So important, maybe, that
some internal mechanisms made something of a "snapshot" of the situ-
ation, not only of the door falling open but of everything else that
happend at/around that moment too. Now I am theorizing ;-).

Superimpose a number of those "snapshots"
that were taken when solutions occurred, kind of like averaging, and
a pattern might present itself: a more or less reliable and signifi-
cant connection between the door opening and some action. No certain-
ty yet, but at least a possible way to a solution that ought to be
given a higher priority over other ways.

If you can figure out how to recognize if there is more than one
"snapshot", then this can be partially tested.

The only mechanism that I can visualize begins when our neurons first
start connecting, before we are born. The mechanism is only random inputs
that affect basic drives (hunger, pain, curiosity, etc.) which initially
cause random outputs. And one by one a complicated structure of control
loops develop, where the output of one control loop is usually the input
to another. And a series of control loops, can effectively become one
control loop.

I cannot yet visualize the mechanism by which control loops develop, but
call it mechanism X.

When the cat is in the box, he already has a working set of control loops
at his disposal. All of these loops have their own assessment of the
situation. Each loop has an (some) associated output. One by one the
cat tests these outputs, and then retests them... When the door opens,
mechanism X is invoked which begins the formation of another control loop.
Each time that the door opens, mechanism X is invoked which optimizes the
new control loop. Eventually, as soon as the state of being caged is
recognized, the cat will have developed a control loop for handling the
situation.

Depending upon what inputs that the cat uses to recognize his situation,
the cat now applies his new control loop to other situations. For
example, if the defining input for his new loop is "I do not want to be
enclosed", then anytime he is enclosed, he will activate this control loop.
If the defining input is "I need to move that obstacle between me and the
outside", then anytime something is between him and his goal, he will
activate this control loop.

The testable part of this theory is the conglomerate control loops. We
should be able to determine if these exist.

-Shannon

[From Bruce Abbott (951203.1645 EST)]

Dag Forssell (951128 1420) --

It seems to me that before we can determine whether anyone's work falls
within the realm of science, we have to develop criteria. We can then apply
those criteria to any given example and decide whether the work (or its
product) qualifies.

"Science" is sometimes defined as an organized body of knowledge obtained
through the use of the scientific method. This fits the literal meaning of
the term, which is "knowledge," while restricting the term to knowledge
obtained in a specific way.

"Science" is also defined as the process through which scientific knowledge
is accumulated. In this sense the terms "science" and "scientific method"
are synonomous. "Scientists" are people who use the scientific method to
build an organized body of knowledge about a subject.

The key, then, to whether a given activity qualifies as science or not is
whether it employs the scientific method to build an organized body of
knowledge. Thus, to develop our criteria, we must know what the scientific
method is. The scientific method comprises several interlocking elements.

The most basic element is _observation_. All scientific knowledge rests on
it. An _empirical_ question is one that can be answered through
observation; if a question is not empirical, it cannot be addressed through
science. This is what puts philosophical questions like "does God exist?"
or "how many angels can fit on the head of a pin?" out of bounds for science.

But not all observations would qualify as scientific. The observations must
be _systematic_ (carried out by adhering to a well-defined plan) and they
must be demonstrated to be _reproducable_. Systematic observations usually
involve measurement, so that quantitative relationships can be established
among variables, although simple classification is often used as well. The
reliability (reproducability) of observations is established through
systematic _replication_.

An observation is accepted as scientific if it is obtained through
systematic observation and can be replicated.

A second essential element of the scientific method is the development of
hypotheses and theories. Here I will use the term "hypothesis" to mean a
statement of a relationship among two or more variables and "theory" as a
set of assumptions about varibles and their relationships (including
variables not directly observable) from which hypotheses may be derived. To
be considered scientific, a new theory must be consistent with the
established "facts" of the discipline, or if not, give reason for believing
those facts to be in error (in the light of the theory).

A third essential element of the scientific method is testing. Withoug
testing, hypotheses and theories are just assertions, even though they may
appear reasonable in light of available evidence. Testing involves setting
up (or finding in nature) conditions under which the hypothesis (or specific
predictions from theory) can be assessed. If the relationship specified by
the hypothesis (or prediciton from theory) is confirmed by the test, then
the hypothesis or theory is supported; otherwise the hypothesis or
prediction is disconfirmed, and so, technically speaking, is the theory from
which the hypothesis or prediction was derived. [However, practical
problems such as incomplete control over extraneous variables, limits to the
precision of measurements, and perhaps ambiguity in the theory or in how to
apply it to a particular case, may limit the researcher's certainty as to
whether a given disconfirmation is actually the fault of the theory or a
result of experimental error or misapplication. In this regard, the more
"rigorous" the theory, the easier it is to determine that a given outcome
has actually disconfirmed a prediction of the theory. The most rigorous
theories are specified mathematically and yield quantitatively precise
predictions.]

Theories that fail to correctly predict some outcome (when the reliability
of this finding has been established) are revised in the light of this
result so as to be consistent with established scientific fact _and_ the new
finding (if the theorist can figure out a way to do this!) or discarded. As
Kuhn notes, even theories known to have problems (and thus known to be
wrong!) are usually retained if they have demonstrated usefulness in
organizing the data and making correct predictions in other areas, so long
as there is no better theory to replace them. Newton's conception of the
universe is fundamentally wrong, makes incorrect predictions under certain
conditions, and is _still_ in use for most practical work, even though, in
this case, better theories are available; in cases where there _are_ no
better theories, even poor theories (imprecise and/or known to make
incorrect predictions even within a limited domain) may continue to be used
while researchers look for something better, because they organize the data
and help to guide further research (heuristic value).

To be considered scientific, a theory must be "testable" in this way. That
is, it must be capable of disproof. There must be some empirical test of
the theory to which the theory can be submitted, which if failed will
disprove (disconfirm) the theory. Looser theories (those that do not make
precise quantitative predicitons) are more difficult to disconfirm than
tighter theories. Even those that do make precise quantitative predictions
may be difficult to test if the variables involved cannot be controlled
and/or measured with precision, as then the experimental error is too wide
to assess the accuracy of the prediction with any confidence. Even so, it
may be possible to reject a prediction if the observed function has the
wrong _form_. For example, if the theory predicts that two observable
variables will be linearly related and what is observed is a parabola, the
theoretical prediction is incorrect.

A Dispute about Criteria

Dag, it seems to me that our dispute is a dispute over criteria. I would
hold that anyone engaged in any part of the activities I have listed above
is doing science. This would include making systematic observations under
carefully defined and noted conditions (and validating those observations
through replication), systematizing the observations by developing
well-defined categories (and perhaps hierarchies of categories) and sorting
the observations into them, developing theories and hypotheses consistent
with established scientific knowledge on the subject, and systematically
testing those theories and hypotheses through properly designed
manipulations and further observations. I hold that most of what goes on in
conventional psychological research falls into one or more of these
activities and therefore qualifies as scientific work.

Your criteria apparently are different. For you, science seems to involve
the following set of activities:

  1. Developing a structural model based on physical elements whose reality
      can be determined (at least theoretically) by looking for them (e.g.,
      signals, transducers, comparators within the physical system being
      studied), and whose functional properties are mathematically specified
      in the model. By specifying these properties and the linkages among
      these elements, one defines a system whose behavior can be deduced
      by appropriate mathematical techniques or by simulation. The elements
      and their connections must be consistent with what is known about the
      layout of the physical system being modeled.

  2. Testing the model against data collected under conditions under which
      the model would be expected to apply.

  3. Modifying the model in the light of discrepancies between the observed
      behavior and that predicted by the model, until model and observations
      agree within a small margin of experimental error.

  4. Exploring the physical structure to determine whether the elements and
      connections of the modified model correspond to elements and connections
      of the physical structure.

I hope I haven't left out anything, or misstated your criteria. Assuming
that this is correct, I agree that this is certainly "high science," the way
science should be done whenever the goal is to identify the mechanism
beneath the observations. A good mechanism (one consistent with both the
observations of physical structure and with observable behavior) provides a
powerful means of prediction and (possibly) control, not to mention
"understanding." Any science that can achieve this clearly deserves the
name "science." My only question for you is whether it is possible that
something less than this should qualify as science, if it follows the
methods I outlined earlier.

Before going off to graduate school to become an experimental psychologist,
I worked for five years at the Owens-Illinois Glass Company's Technical
Center as a technician. I worked in Glass Science, a department within
Corporate Research that employed about a dozen engineers and Ph.D. chemists.
Their job was to develop new knowledge about glass which the company could
exploit to produce new products. I don't know for sure, but I suspect you
count physical chemistry among the "hard" sciences. Do you know how I spent
my time? Doing emprical studies of the properties of various mixtures of
chemical compounds which, when heated sufficiently, tend to produce a glass.
So far as I am aware, not once did any of these Ph.D. researchers begin with
a model of the physical structures (molecules, in this case), hypothesize
linkages among them in the mixture, and come up with a precise quantitative
prediction about the properties (behavior) of the resulting glass. The
situation may have improved since 1973 (when I left O-I), but at that time
an expert in physical chemistry could not even predict whether a given
mixture would _form_ a glass, based on its composition and the temperatures
to which the mixture would be exposed. In fact, one could say that the
whole point of the research was to find a model from which such predictions
could be made. So we did empirical studies, varying the composition and the
specific temperatures to which the mixture would be exposed in a systematic
way and then measuring the physical characteristics of the resulting glass
(if indeed you got a glass) along a large number of dimensions.

Now I still think we were doing science, there in Glass Science, back in
1973. By your criteria we were doing mush. But if this is mush, where does
the knowledge come from that eventually allows one to construct the precise
mathematical models that are the sine qua non of an advanced science? It
would seem to me that there have to be quite a few "mushists" at work
providing the foundation so that the "real" scientists can come along and do
the real science.

Goals of Science

Philosophers of science usually say that there are three goals of the
scientific enterprise: understanding, prediction, and control. As I have
already indicated, a model that specifies a physical mechanism and has been
validated empirically can be said to provide a deep understanding of those
phenomena of relevance to the theory, allows precise prediction, and may
make excellent control of the (real) system's behavior possible. Who would
want less, if this is possible? Yet even when there is as yet hardly a clue
as to how a model can be constructed of a given system, it is still possible
to go a fair way toward reaching those scientific goals, although
necessarily the results will be much more limited. For many decades local
meterologists predicted the weather based on a knowledge of relationships
among locally-measured variables -- temperature, barometric pressure,
relative humidity, wind direction and speed, type and amount of cloud cover
-- and the dynamic changes in those variables. The empirical relationships
among these variables did not permit quantitatively precise predictions of
the weather, even over so short a term as six hours, but the predictions
made were certainly better than what had been available before these
variables had been systematically measured and the relationships among them
discovered. One can also say that having knowledge of such relationships
provided a certain level of understanding. Why is it raining? Well, the
wind swung around to the east, the barometric pressure dropped, the humidity
was rising, and the cloud cover was increasing. It's raining because rain
usually follows such changes. Today we might offer a "better" explanation:
it's raining because a cold front is passing through, or because a "low"
bearing considerable moisture is passing over the state. Such knowledge
even permits a degree of control. If it's going to rain, I'll reschedule my
picnic. Just discovering empirical relationships (especially the ones
labeled "causal") and developing a quantitative model of them can be of
practical value even though one does not yet possess a model of the
mechanism, but only of the behavior of the mechanism as seen under certain
specifiec conditions.

The laws of physics which lie beneath the ebb and flow of the weather are
well-understood, yet even the best computer models cannot predict the
weather in, say, Fort Wayne, Indiana, with a high degree of accuracy, even
over the short term. Physics is science, but meterology, evidently, is mush.

Much of what goes on in psychology is aimed at discovering stable
relationships that might permit some degree of prediction and (perhaps)
control. The models developed for these situations are limited and may not
generalize very far beyond the conditions within which the model was
originally designed to function. Researchers get interested in addressing
certain phenomena, and try to identify the conditions under which those
phenomena occur (and do not occur) as part of the effort to understand what
is going on. People get angry, as indicated by a certain constellation of
changes in their actions toward other people, themselves, or in some cases,
inanimate objects. What are the necessary conditions that bring about this
state? In the most general terms, how does behavior change? What are the
consequences of the resulting actions? Can we predict what will make a
person angry? Can we predict what the person will probably do when in this
state? To try to answer these questions, researchers develop hypotheses,
manipulate variables, assess whether the hypotheses are supported by the
results, revise their thinking in light of the outcome. The physical
mechanism beneath these relationships remains mostly unknown and
unspecified, but some useful information about the variables involved and
their relationships has been developed, and this information may prove very
useful for guiding the devopment of a physical model. Meanwhile, more of
practical value is known (scientifically established) than was available
before the research was done (which may have been nothing more than myths
and aphorisms). Even when "common sense" notions are confirmed, what was
just common sense is now part of scientifically established knowledge.

Science, Mushy Science, and Mush

Perhaps what we need is to recognize that there is a continuum between what
you call science and the pure mush of unconfirmed speculation, untestested
(and unstestable) theory, and anecdotal evidence. Much of what goes on in
normal, everyday scientific work is not the testing and refinement of
quantitative physical models, but it is still science in that it employs the
methods of science to establish a body of knowledge. During the early
stages of a new science, most of the work will necessarily be directed
toward establishing a body empirical phenomena, identifying the variables at
work in those phenomena and the relationships among the observables, and
developing and testing hypotheses about how the system functions. Only when
sufficient knowledge has been accumulated can one begin to develop and test
a quantitative physical model, and even then one has to understand what is
possible.

In this regard, there is a reason why the model known as control theory
developed first within electrical engineering and not psychology, in
addition to the one proposed by Bill Powers (use of IV-DV methods).
Electrical engineers had not only the proper formal mathematical training,
but were dealing with a system of elements of known structure and function,
which they could manipulate at will simply by wiring them up in whatever way
interested them. Already possessing some basic laws (e.g., Ohm's), they
could write the proper equations describing the functional relationships
expected (within experimental error) of each component (reisistor, inductor,
etc.), work out what is to be expected when one feeds back a portion of a
differential amplifier's output to one of its inputs, then build the
physical circuit and compare prediction to the system's actual behavior.
Piece of cake! All it took (besides the right training) to come up with the
answer was a practical problem that got the right guy thinking about how to
solve it.

Meanwhile, here are all these researchers in psychology, facing a system of
enormous complexity and lacking a means to anything more than manipulate
variables and observe the result. Nevertheless, they succeed in building an
empirical model (reinforcement theory) that seems to work well in a lot of
situations under investigation, based on a selectionist principle borrowed
from evolutionary theory. Research keeps on turning up difficulties for the
theory, and soon there are numerous proposals on modifications to, or
elaborations of the theory in order to account for these anomalies. I don't
know about you, but this doesn't sound like an untestable theory to me. If
it's untestable, why does it keep getting into trouble? But it remains
useful in that it has provided a guide to further research (heuristic value)
and has had success in certain applications, and the hope remains that the
right set of additional assumptions will be found to make it work
successfully in all cases. (Not MY hope, by the way; I have a better theory
to go on.)

Probably the single most important reason why psychology has not attempted
to develop a purely mechanistic (as opposed to descriptive) account of
behavior is the belief that such an account is not possible given the
current state of our knowledge regarding the structure of the brain.
Psychologists have from time to time attempted to construct such models, but
they have been based on an erroneous conception of the nervous system (S-R
reflex; Pitts-McCulloch neurons; digital computer) or have involved
structures presumed (from theoretical considerations) to exist (perhaps in
distributed fashion) which carry out inferred functions (e.g., memory
storage and retrieval) in ways for which there is insufficient knowledge to
posit a physical organzation to do the job. What results is speculative
enough for you to define as mush, and unsatisfactory enough for most
psychologists to avoid them. As a result, psychologists have learned to
keep their speculations restricted within narrow areas of research and to
depend mainly on discovery of empirical relationships in the belief that
eventually there will be enough known to begin building the foundation from
which the descriptive science's relationships can be deduced.

Please note that I am not defending this state of affairs, although I think
I understand how it came about, nor am I arguing that descriptive theories
(like Kepler's) are on a par with mechanistic ones (like Newton's). There
has been a whole series of events in the history of psychology which has
prevented it from moving from descriptive and quasi-mechanistic theory to
physically-grounded mechanistic theory, even though the information needed
to move from the former to the latter has been around for a long time. But
I am arguing that much of what scientists do in most fields is not
restricted to building and testing such models; where you see this kind of
activity most in evidence is within the applied fields of well-developed
sciences for which the required foundation of basic theory already exists.
In those areas the question is not so much trying to understand new
phenomena for which existing theory fails as in seeing how to apply existing
theory to specific cases. For engineers used to doing only the latter,
anything less may seem like mush. What you may not understand is the amount
of effort by scientists doing the kind of work you would not define as
scientific that had to be completed before the magnificant theories you see
as the only product to true science could be conceived and tested.

Finally, I want to correct an impression you left of my view in your post.
I do not accord the term "science" to a person's work because that person
"tried hard." A person's work is "science" if it followed the methods of
science. Whether the person's theoretical analysis stands the test of time,
only time will tell, and in many cases what seemed on the best evidence
available at the time to be a valid explanation has turned out to be
fundamentally wrong. Even Newton was wrong (even though under most
conditions the results given by his analysis are correct to twenty decimal
places), but that fact does not convert Newton's work from science to mush.
I will hold Thorndike's work as science even though his explanation did not
provide a physical mechanism, and even though it has proved to be wrong,
simply because it was based on systematic observation, was consistent with
the data and the then-current theories of physiology, and yielded testable
predictions. The fact that, given the information available, Thorndike
could not construct a physical model that might be found to have a physical
reality within the brain, does not disqualify Thorndike's work from the ream
of the scientific, in my view.

Regards,

Bruce

[From Dag Forssell (951209 2110)]

[Bruce Abbott (951203.1645 EST)]

You chose to not answer my post [Dag Forssell (951128 1420)].
Perhaps there was something wrong with my post from your
perspective. I have noted that skilled debaters simply change the
subject rather than concede the point when they find themselves
cornered. OK, I'll answer yours.

   It seems to me that before we can determine whether anyone's

     work falls within the realm of science, we have to develop
     criteria. We can then apply those criteria to any given
     example and decide whether the work (or its product)
     qualifies.

I think this makes sense. You offer two sets of criteria, your own
and mine (which involve structural models). I have no quarrel with
your portrayal of the criteria. Let us examine Reinforcement
Theory against your own criteria to see if it qualifies as science
on your own terms. I shall add emphasis by capitalizing some of
your words.

   "Science" is sometimes defined as an organized body of

     knowledge obtained through the use of THE SCIENTIFIC METHOD.
     . . ."Science" is also defined as the process through which
     scientific knowledge is accumulated.

   The key, then, to whether a given activity qualifies as

     science or not is whether it EMPLOYS THE SCIENTIFIC METHOD to
     build an organized body of knowledge. Thus, to develop our
     criteria, we must know what THE SCIENTIFIC METHOD is. THE
     SCIENTIFIC METHOD comprises several interlocking elements.

Bruce, I think you leave out as a criterion that the "scientific
method" must be appropriate to the nature of the subject matter
under study. To me, this is major. If the "scientific method"
were appropriate to the subject under study, the rest would follow
naturally and yield useful results.

I have heard before that psychologists are proud of and put great
stock in the "scientific method". This is a major justification
for considering psychology science, I agree. However, PCT shows
and I think it has been amply demonstrated to you on CSG-L that the
"scientific method" as commonly applied to inert matter is applied
in an inappropriate way when used by life scientists to study
individual living organisms. By mis-applying the scientific method
in the customary way, psychologists learn everything about the
properties of the environment around the organism (an environment
the scientists have themselves created and carefully control), but
nothing about the properties of the organism. Already, psychology
fails to qualify as science.

This is tragic for mankind. Never mind the status of psychologists
as scientists or not. Educators, parents, leaders, politicians,
counselors and anyone who tries to serve his fellow man has been
sold a bill of goods: misleading falsehoods. The world is WORSE
off with contemporary psychological "science" than it would be if
these "scientists" had the insight (which many do) and the
intellectual honesty as well as intestinal fortitude (which they
don't) to simply say: "We don't know".

   The most basic element is _observation_. All scientific

     knowledge rests on it. . . . .An observation is accepted as
     scientific if it is obtained through systematic observation
     and can be replicated.

Your own (like Thorndike's) descriptions of various observations
are not merely observations. You habitually include a vast number
of assumptions and interpretations contained in your language and
descriptions. When the unstated assumptions prove false, as most
do when pointed out and examined, the overwhelming majority of
psychological observations by yourself and others fall.

   A second essential element of the scientific method is the

     development of hypotheses and theories. . .

You have had an incredibly difficult time to explain just exactly
what the theory of reinforcement is. You have demonstrated that
EAB types don't know themselves. Recent contributions by Samuel
Saunders and Chris Cherpas make it clear that there is a great
multitude of such "theories" and that they are made up on the fly,
ex post facto, as needed to "explain".

   A third essential element of the scientific method is testing.

     Without testing, hypotheses and theories are just assertions,
     even though they may appear reasonable in light of available
     evidence. Testing involves setting up (or finding in nature)
     conditions under which the hypothesis (or specific predictions
     from theory) can be assessed.

Rick is challenging you to come up with a test at long last.
Apparently there have not been any attempts to falsify
Reinforcement Theory to date. It appears that this is because
there really is no such thing as Reinforcement Theory. This again
disqualifies EAB as science.

   Theories that fail to correctly predict some outcome (when the

     reliability of this finding has been established) are revised
     in the light of this result so as to be consistent with
     established scientific fact _and_ the new finding (if the
     theorist can figure out a way to do this!) OR DISCARDED. . .

   To be considered scientific, a theory must be "testable" in

     this way. THAT IS, IT MUST BE CAPABLE OF DISPROOF. There
     must be some empirical test of the theory to which the theory
     can be submitted, which if failed will disprove (disconfirm)
     the theory. Looser theories (those that do not make precise
     quantitative predictions) are more difficult to disconfirm
     than tighter theories.

So far, reading and skimming the great number of posts on
Reinforcement Theory, Ex-EABers have made it very clear that
discarding Reinforcement Theory is not an option. All you need to
do is to ignore any problems and reword the verbal statements. It
emerges that Reinforcement Theory is not capable of disproof. If
an apparent disproof shows up, it is set aside, as you do in the
following:

ยทยทยท

--------------------------------
[From Dag Forssell (950629 1500)]

Bruce Abbott (950628.2020 EST)

Bill Powers (950628.0945 MDT) --

Bruce Abbott (950628.0900 EST)

However, these authors felt that these results might be

     explained by the complex interaction between running rate and
     postreinforcement pause observed in the data. The overall rate
     would result from the combination of these two factors.

  This is a pretty feeble comment on an observation that goes

     directly against the fundamental assumptions behind
     reinforcement theory itself.

   Well, these guys aren't reinforcement theorists, they're just

     humble experimentalists reporting their data. I give them
     credit for perceiving and pointing out the apparent problem
     for reinforcement theory; apparently they felt less than
     comfortable going much further. Their objective was to
     discover what relationships occur in this situation, and
     that's what they did. They were willing to leave the
     theorizing to someone else.

. . .

Your statement above -- "Well, these guys aren't reinforcement
theorists, they're just humble experimentalists reporting their
data." -- offered with an apparently straight face is a sad comment
indeed. Surely these are psychologists with PhD's??? Was this
research report reviewed by a committee of expert peers before
publication? If so, did they not understand either?? Is
Reinforcement Theory so obscure and convoluted that a division of
labor as you indicate is called for? It comes across as a giant
cop-out in a way that I think unthinkable in the physical sciences.
The obvious implication is that the experimentalist accepts no
responsibility for the theory; the theoretician accepts no
responsibility for the experiment. The theoretician can pick and
choose what experiments he or she wishes to comment on, free to
select only those that support the theory for further comment.
Experiments not supportive of theory, in fact disproving it, die a
quiet death. This charade hardly qualifies Reinforcement Theory or
EAB as a science. It cannot be taken seriously. From a PCT
perspective we know that by misleading armies of well-meaning
students of psychology for many decades, it has actually done
mankind an enormous disservice.
. . . .
--------------------------------

Bruce, you never commented on this. Here, clearly, is an instance
of what looks like disproof. You duck, look the other way and
continue the discussion with the next subject. There is something
intellectually dishonest about this. The name of the game is
denial. This time you disqualified your peers as scientists by
your own criteria.

A more recent exchange shows that Reinforcement Theory is not
capable of disproof because of the way it is defined:

----------------------------------------

[Bill Powers (951206.1500 MST)]

Chris Cherpas (951206.0851 PT) --

  Please understand that "reinforcement" is _defined_ as what

     increases the probability of behavior. Period.

   I was trying to give the benefit of the doubt. This way of

     defining reinforcement means that you can have no basis at all
     for predicting whether something will be reinforcing. You have
     to wait for the results of the experiment, and THEN you can
     decide. This pretty much takes the wind out of the sails of
     reinforcement theory as an explanation of behavior, doesn't
     it?
---------------------------

So, the definition of reinforcement disqualifies reinforcement
theory as science.

Just yesterday, Samuel Saunders offered compelling commentary that
further illustrates the hopeless confusion that reigns in the EAB
camp and that Reinforcement Theory is not subject to disproof:

[Samuel Saunders (951208:21:57:10)]

   It doesn't really matter if it is true that reinforcement can

     account for all these things or not; it is true that the EABer
     on the street is likely to _think_ that it can, and PCT will
     have no alternative until a PCT approach is developed.

Back to your post, bruce.

   A Dispute about Criteria

   Dag, it seems to me that our dispute is a dispute over

     criteria. I would hold that anyone engaged in any part of the
     activities I have listed above is doing science. . . . I
     hold that most of what goes on in conventional psychological
     research falls into one or more of these activities and
     therefore qualifies as scientific work.

By your own criteria, I disagree with your conclusion.

   Your criteria apparently are different. For you, science

     seems to involve the following set of activities:

Your statement of my criteria is good enough. These apply to
modern physical science.

   Before going off to graduate school to become an experimental

     psychologist, I worked for five years at the Owens-Illinois
     Glass Company's Technical Center as a technician. I worked in
     Glass Science, a department within Corporate Research that
     employed about a dozen engineers and Ph.D. chemists.

. . . .

   Now I still think we were doing science, there in Glass

     Science, back in 1973. By your criteria we were doing mush.
     But if this is mush, where does the knowledge come from that
     eventually allows one to construct the precise mathematical
     models that are the sine qua non of an advanced science? It
     would seem to me that there have to be quite a few "mushists"
     at work providing the foundation so that the "real" scientists
     can come along and do the real science.

As I see it, you were doing Alchemy. As I have said before,
Alchemy works. You work with physical ingredients, following
recipes that are carefully recorded and with experiments that are
replicated -- in mass production, no less. The results are subject
to description in the form of physical measurements, not just free-
wheeling subjective interpretation in words alone, as when you
"describe" the struggles of cats or geese.

Most significantly, the basic scientific method, the same one used
by behavioral scientists and laid out in your book (as I understand
it from Rick's review) IS APPROPRIATE for the study of inert
matter, such as glass. Therefore, I have no quarrel with your
Glass Science.

When the basic scientific method is appropriate, as in Glass
Science, you make headway.

When the basic scientific method is inappropriate, as in
conventional psychological "science", you make mush.

   Goals of Science

This is getting too long and taking too much time. In this section
you continue to apologize for the failures of by saying:

   Who would want less, if this is possible? Yet even when there

     is as yet hardly a clue as to how a model can be constructed
     of a given system, it is still possible to go a fair way
     toward reaching those scientific goals, although necessarily
     the results will be much more limited.

You refuse to draw the uncomfortable conclusion that the limited
results tell you nothing about what you purport to study, but only
reflect the experimental setup. This is what you get from using
the scientific method INappropriately.

   Science, Mushy Science, and Mush

   Perhaps what we need is to recognize that there is a continuum

     between what you call science and the pure mush of unconfirmed
     speculation, untested (and unstestable) theory, and anecdotal
     evidence.

Yes, there is such a continuum in Alchemy, for example.

   Much of what goes on in normal, everyday scientific work is

     not the testing and refinement of quantitative physical
     models, but it is still science in that it employs the methods
     of science to establish a body of knowledge.

No, your statement applies to psychological science, and it does
not employ methods of science appropriately -- it cannot establish
a valid body of knowledge with which one can form a continuum.

   Meanwhile, here are all these researchers in psychology,

     facing a system of enormous complexity and lacking a means to
     anything more than manipulate variables and observe the
     result.

It is of enormous complexity only because they are ignorant of 20th
century developments and refuse to accept new ideas which are at
variance with what they already believe -- a perfectly
understandable control phenomenon, but tragic in its consequences
for mankind.

   Nevertheless, they succeed in building an empirical model

     (reinforcement theory) that seems to work well in a lot of
     situations under investigation, based on a selectionist
     principle borrowed from evolutionary theory. Research keeps
     on turning up difficulties for the theory, and soon there are
     numerous proposals on modifications to, or elaborations of the
     theory in order to account for these anomalies. I don't know
     about you, but this doesn't sound like an untestable theory to
     me.

__ A) You have been unable to explain what it is.
__ B) It is untestable because it is a moving target.
__ C) It fails all the time, you just refuse to face it.
__ D) Your own failure to offer any kind of definitive test
          contradicts you.
__ E) All of the above.

   Probably the single most important reason why psychology has

     not attempted to develop a purely mechanistic (as opposed to
     descriptive) account of behavior is the BELIEF that such an
     account is not possible given the current state of our
     knowledge regarding the structure of the brain.

I believe you are right in this. (Agreement for once :slight_smile: )

   Please note that I am not defending this state of affairs,

     although I think I understand how it came about, nor am I
     arguing that descriptive theories (like Kepler's) are on a par
     with mechanistic ones (like Newton's).

But you do nothing but defend it in post after post. You also
insist on respect for this state of affairs and suggest that the
results of EAB research should be respected and can serve as
starting points for proper (PCT) analysis.

   There has been a whole series of events in the history of

     psychology which has prevented it from moving from descriptive
     and quasi-mechanistic theory to physically-grounded
     mechanistic theory, even though the information needed to move
     from the former to the latter has been around for a long time.

I don't know about a whole series of events. Lack of a proper
concept stands out as a key reason. Another is control for
prestige, an emphasis on BEING RIGHT as befits famous scientists
and esteemed professors, as opposed to the much humbler, and much
more scientific, emphasis on UNDERSTANDING CORRECTLY. I do think
that the overwhelming majority of life scientists are content to
strive to BE RIGHT (they don't know any alternative; there are many
equally useless and untestable theories competing) where PCTers on
CSG-L challenge them to UNDERSTAND CORRECTLY. As Bill P. has
lamented in one of his lucid essays on science (I can't pinpoint it
right now), he has met very few scientists who place emphasis on
UNDERSTANDING CORRECTLY.

   But I am arguing that much of what scientists do in most

     fields is not restricted to building and testing such models;
     where you see this kind of activity most in evidence is within
     the applied fields of well-developed sciences for which the
     required foundation of basic theory already exists. In those
     areas the question is not so much trying to understand new
     phenomena for which existing theory fails as in seeing how to
     apply existing theory to specific cases. For engineers used
     to doing only the latter, anything less may seem like mush.
     What you may not understand is the amount of effort by
     scientists doing the kind of WORK YOU WOULD NOT DEFINE AS
     SCIENTIFIC THAT HAD TO BE COMPLETED before the magnificent
     theories you see as the only product to true science could be
     conceived and tested.

Again, an apology for misguided EAB research. I am sure there has
been a lot of gruntwork in the physical sciences before today's
magnificent theories were created in the minds of clear thinkers.
You can count all of mankind's experience since the dawn of time in
this category. But once the clear theories are developed, tested
and found to work, the old efforts are laid aside and forgotten.
Reinforcement Theory is not something that had to be completed
before PCT could be conceived and tested. Reinforcement Theory is
a misleading aberration. It will be forgotten, and the sooner the
better.

   Finally, I want to correct an impression you left of my view

     in your post. I do not accord the term "science" to a person's
     work because that person "tried hard." A person's work is
     "science" if it followed the methods of science.

I appreciate this. Unfortunately, the "methods of science" you
refer to are not used in a way that is appropriate for the study of
living organisms (control systems).

It sure seems to me that the overwhelming evidence shows that
Reinforcement Theory and its EAB application do not live up to
Bruce Abbott's criteria for science, and that the mis-application
of the scientific method itself further disqualifies them.

Science or Mush? It is an open and shut case. Case closed.

Best, Dag