In article <6hdmhg$1nq$1 at fu-berlin.de> cijadra at zedat.fu-berlin.de writes:
> Stephen Harris <mulcyber at pacbell.net> wrote:
>> >cijadra at zedat.fu-berlin.de wrote:
> >>
> >> You do not perceive the thoughts because you do not know enough.
> >>
> >> I believe there is a lot you'd not understand in Carlos Castaneda's
>> >This sort of stuff appeals to the gullible fairly intelligent.
> >Astrology, Tarot, I Ching, Crystal Chakra healing, are all fake
> >and in the same category. All of it, including C Casteneda is
> >a pile of spiritual hubris. You will never find a fact or evidence.
> >This is what some grownups do instead of believing in Santa Claus.
>> It seems there is a lot that you do not understand.
> And that you are proud of it.
> What Carlos Castaneda writes, is, as he says, a guide to real sorcery.
> But, as I said, he is leaving out key data, without which it is
> unlikely that you understand what he says.
> Sorcery is not meant for all according to many people's opinions; and
> I heard that even for what he wrote he got complaints from many places
> of the world. And I can see why.
> There is data in there which much have taken centuries if not
> thousands of years of research to get at it.
>> That you are too ... to see the incredible value of it is not speaking
> for you.
>> And I do not say that all he says is correct; some is b.s., some is
> dangerous b.s., and in his first books he is going forever after stuff
> that is not so interesting if one is alteady knowing a bit about it
> and is t=not paying attention to some of the stuff that is beyond
> nominal value, so that it is just mentioned shortly but never
> explained deeper. Argh.
>> The point of Tarot is a mental counselling.
> Personally I do not like it, but for some people it is good if they
> stop once a week or more often and look at where they are in life,
> think about that, their past, their future.
> It helps them to go a more steady and content course through life.
>> About Crystal Chakra healing I cannot say anything.
> So far I do not have enough control over the Chakren in the body, nor
> know about all crystals and their effect upon those centers, so I am
> not able to judge.
>> With Astrology I believe that the planets still have effects upon us,
> but not the stars, but that the time of the year y9u are born in plays
> a high role in some cultures.
> In my land in winter it is dark at five and in summer light till after
> eleven. A child born in winter and learning to walk one year later can
> not go out into the snowy land and has other melatonin levels than a
> summer child who one year later might take first steps through the
> garden and look at the flowers and insects...
> That is a very different input and I believe it makes changes.
>> I-Ching I do not know.
>> I believe that you judge things fast without understanding them.
>>
> >This sort of stuff appeals to the gullible fairly intelligent.
> >Astrology, Tarot, I Ching, Crystal Chakra healing, are all fake
> >and in the same category. All of it, including C Casteneda is
> >a pile of spiritual hubris. You will never find a fact or evidence.
> >This is what some grownups do instead of believing in Santa Claus.
Yes - well put.
It will help if an idea of what we mean by 'clinical' and 'actuarial'
judgement is provided. The following is taken from a an early (Meehl
1954), and a relatively recent review of the status 'Clinical vs.
Actuarial Judgement' by Dawes, Faust and Meehl (1989):
'One of the major methodological problems of clinical
psychology concerns the relation between the "clinical"
and "statistical" (or "actuarial") methods of
prediction. Without prejudging the question as to
whether these methods are fundamentally different, we
can at least set forth the main difference between them
as it appears superficially. The problem is to predict
how a person is going to behave. In what manner should
we go about this prediction?
We may order the individual to a class or set of classes
on the basis of objective facts concerning his life
history, his scores on psychometric tests, behavior
ratings or check lists, or subjective judgements gained
from interviews. The combination of all these data
enables us to CLASSIFY the subject; and once having made
such a classification, we enter a statistical or
actuarial table which gives the statistical frequencies
of behaviors of various sorts for persons belonging to
the class. The mechanical combining of information for
classification purposes, and the resultant probability
figure which is an empirically determined relative
frequency, are the characteristics that define the
actuarial or statistical type of prediction.
Alternatively, we may proceed on what seems, at least,
to be a very different path. On the basis of interview
impressions, other data from the history, and possibly
also psychometric information of the same type as in the
first sort of prediction, we formulate, as a psychiatric
staff conference, some psychological hypothesis
regarding the structure and the dynamics of this
particular individual. On the basis of this hypothesis
and certain reasonable expectations as to the course of
other events, we arrive at a prediction of what is going
to happen. This type of procedure has been loosely
called the clinical or case-study method of prediction'.
P. E. Meehl (1954)
The Problem: Clinical vs. Statistical Prediction
'In the clinical method the decision-maker combines or
processes information in his or her head. In the
actuarial or statistical method the human judge is
eliminated and conclusions rest solely on empirically
established relations between data and the condition or
event of interest. A life insurance agent uses the
clinical method if data on risk factors are combined
through personal judgement. The agent uses the actuarial
method if data are entered into a formula, or tables and
charts that contain empirical information relating these
background data to life expectancy.
Clinical judgement should not be equated with a clinical
setting or a clinical practitioner. A clinician in
psychiatry or medicine may use the clinical or actuarial
method. Conversely, the actuarial method should not be
equated with automated decision rules alone. For
example, computers can automate clinical judgements. The
computer can be programmed to yield the description
"dependency traits", just as the clinical judge would,
whenever a certain response appears on a psychological
test. To be truly actuarial, interpretations must be
both automatic (that is, prespecified or routinized) and
based on empirically established relations.'
R. Dawes, D. Faust & P. Meehl (1989)
Clinical Versus Actuarial Judgement Science v243, pp
1668-1674 (1989)
As long ago as 1941, Lundberg made it clear that any argument between
those committed to the 'clinical' (intuitive) stance and those arguing
for the 'actuarial' (statistical) was a pseudo-argument, since all the
clinician could possibly be making his or her decision on was his or
her limited experience (database) of past cases and outcomes.
'I have no objection to Stouffer's statement that "if
the case-method were not effective, life insurance
companies hardly would use it as they do in
supplementing their actuarial tables by a medical
examination of the applicant in order to narrow their
risks." I do not see, however, that this constitutes a
"supplementing" of actuarial tables. It is rather the
essential task of creating specific actuarial tables. To
be sure, we usually think of actuarial tables as being
based on age alone. But on the basis of what except
actuarial study has it been decided to charge a higher
premium (and how much) for a "case" twenty pounds
overweight, alcoholic, with a certain family history,
etc.? These case-studies have been classified and the
experience for each class noted until we have arrived at
a body of actuarial knowledge on the basis of which we
"predict" for each new case. The examination of the new
case is for the purpose of classifying him as one of a
certain class for which prediction is possible.'
G. Lundberg (1941)
Case Studies vs. Statistical Methods - An Issue Based
on Misunderstanding. Sociometry v4 pp379-83 (1941)
A few years later, Meehl (1954), drawing on the work of Lundberg
(1941) and Sarbin (1941) in reviewing the relative merits of clinical
vs. statistical prediction (judgement) reiterated the point that all
judgements about an individual are always referenced to a class, they
are always therefore, probability judgements.
'No predictions made about a single case in clinical
work are ever certain, but are always probable. The
notion of probability is inherently a frequency notion,
hence statements about the probability of a given event
are statements about frequencies, although they may not
seem to be so. Frequencies refer to the occurrence of
events in a class; therefore all predictions; even those
that from their appearance seem to be predictions about
individual concrete events or persons, have actually an
implicit reference to a class....it is only if we have a
reference class to which the event in question can be
ordered that the possibility of determining or
estimating a relative frequency exists.. the clinician,
if he is doing anything that is empirically meaningful,
is doing a second-rate job of actuarial prediction.
There is fundamentally no logical difference between the
clinical or case-study method and the actuarial method.
The only difference is on two quantitative continua,
namely that the actuarial method is more EXPLICIT and
more PRECISE.'
P. Meehl (1954)
Clinical vs. Statistical Prediction:
A Theoretical Analysis and a Review of the Evidence
There has, unfortunately, over the years, been a strong degree of
resistance to the actuarial approach. It must be appreciated however,
that the technology to support comprehensive actuarial analysis and
judgment has only been physically available since the 1940s with the
invention of the computer. Practically speaking, it has only been
available on the scale we are now discussing since the late 1970s with
the development of sophisticated DBMS's (databases with query
languages based on the Predicate Calculus; Codd 1970; Gray 1984;
Gardarin and Valduriez 1989, Date 1992), and the development and mass
production of powerful and cheap microcomputers. Minsky and Papert
(1988) in their expanded edition of 'Perceptrons' (basic pattern
recognition systems) in fact wrote:
'The goal of this study is to reach a deeper
understanding of some concepts we believe are crucial to
the general theory of computation. We will study in
great detail a class of computations that make decisions
by weighting evidence.....The people we want most to
speak to are interested in that general theory of
computation.'
M. L. Minsky & S. A. Papert (1969,1990)
Perceptrons p.1
The 'general theory of computation' is, as elaborated elsewhere,
'Recursive Function Theory' (Church 1936, Kleene 1936, Turing 1937),
and is essentially the approach being advocated here as evidential
behaviourism, or eliminative materialism which eschews psychologism
and intensionalism. Nevertheless, as late as 1972, Meehl still found
he had to say:
'I think it is time for those who resist drawing any
generalisation from the published research, by
fantasising about what WOULD happen if studies of a
different sort WERE conducted, to do them. I claim that
this crude, pragmatic box score IS important, and that
those who deny its importance do so because they just
don't like the way it comes out. There are few issues in
clinical, personality, or social psychology (or, for
that matter, even in such fields as animal learning) in
which the research trends are as uniform as this one.
Amazingly, this strong trend seems to exert almost no
influence upon clinical practice, even, you may be
surprised to learn, in Minnesota!...
It would be ironic indeed (but not in the least
surprising to one acquainted with the sociology of our
profession) if physicians in nonpsychiatric medicine
should learn the actuarial lesson from biometricians and
engineers, whilst the psychiatrist continues to muddle
through with inefficient combinations of unreliable
judgements because he has not been properly instructed
by his colleagues in clinical psychology, who might have
been expected to take the lead in this development.
I understand (anecdotally) that there are two other
domains, unrelated to either personality assessment or
the healing arts, in which actuarial methods of data
combination seem to do at least as good a job as the
traditional impressionistic methods: namely, meteorology
and the forecasting of security prices. From my limited
experience I have the impression that in these fields
also there is a strong emotional resistance to
substituting formalised techniques for human judgement.
Personally, I look upon the "formal-versus-judgmental"
issue as one of great generality, not confined to the
clinical context. I do not see why clinical
psychologists should persist in using inefficient means
of combining data just because investment brokers,
physicians, and weathermen do so. Meanwhile, I urge
those who find the box score "35:0" distasteful to
publish empirical studies filling in the score board
with numbers more to their liking.'
P. E. Meehl (1972)
When Shall We Use Our Heads Instead of the Formula?
PSYCHODIAGNOSIS: Collected Papers (1971)
In 1982, Kahneman, Slovic and Tversky, in their collection of papers
on (clinical) judgement under conditions of uncertainty, prefaced the
book with the following:
'Meehl's classic book, published in 1954, summarised
evidence for the conclusion that simple linear
combinations of cues outdo the intuitive judgements of
experts in predicting significant behavioural criteria.
The lasting intellectual legacy of this work, and of the
furious controversy that followed it, was probably not
the demonstration that clinicians performed poorly in
tasks that, as Meehl noted, they should not have
undertaken. Rather, it was the demonstration of a
substantial discrepancy between the objective record of
people's success in prediction tasks and the sincere
beliefs of these people about the quality of their
performance. This conclusion was not restricted to
clinicians or to clinical prediction:
People's impressions of how they reason, and how well
they reason, could not be taken at face value.'
D. Kahneman, P. Slovic & A. Tversky (1982)
Judgment Under Conditions of Uncertainty: Heuristics and
Biases
Earlier in 1977, reviewing the Attribution Theory literature evidence
on individuals' access to the reasons for their behaviours, Nisbett
and Wilson (1977) summarised the work as follows:
'................................... there may be little
or no direct introspective access to higher order
cognitive processes. Ss are sometimes (a) unaware of the
existence of a stimulus that importantly influenced a
response, (b) unaware of the existence of the response,
and (c) unaware that the stimulus has affected the
response. It is proposed that when people attempt to
report on their cognitive processes, that is, on the
processes mediating the effects of a stimulus on a
response, they do not do so on the basis of any true
introspection. Instead, their reports are based on a
priori, implicit causal theories, or judgments about the
extent to which a particular stimulus is a plausible
cause of a given response. This suggests that though
people may not be able to observe directly their
cognitive processes, they will sometimes be able to
report accurately about them. Accurate reports will
occur when influential stimuli are salient and are
plausible causes of the responses they produce, and will
not occur when stimuli are not salient or are not
plausible causes.'
R. Nisbett & T. Wilson (1977)
Telling More Than We Can Know: Public Reports on Private
Processes
Such rules of thumb or attributions, are of course the intensional
heuristics studied by Tversky and Kahneman (1973), or the 'function
approximations' computed by neural network systems discussed earlier
as connection weights (both in artificial and real neural nets, cf.
Kandel's work with Aplysia).
Mathematical logicians such as Putnam (1975,1988); Elgin 1990 and
Devitt (1990) have long been arguing that psychologists may, as
Skinner (1971,1974) argued consistently, be looking for their data in
the wrong place. Despite the empirical evidence from research in
psychology on the problems of self report, and a good deal more drawn
from decision making in medical diagnosis, the standard means of
obtaining information for 'reports' on inmates for purposes of review,
and the standard means of assessing inmates for counselling is on the
basis of clinical interview. In the Prison Service this makes little
sense, since it is possible to directly observe behaviour under
relatively natural conditions of everyday activities. The clinical
interview, is still the basis of much of the work of the Prison
Psychologist despite the literature on fallibility of self-reports,
and the fallibility and unwitting distortions of those making
judgments in such contexts has been consistently documented within
psychology:
'The previous review of this field (Slovic, Fischoff &
Lichtenstein 1977) described a long list of human
judgmental biases, deficiencies, and cognitive
illusions. In the intervening period this list has both
increased in size and influenced other areas of
psychology (Bettman 1979, Mischel 1979, Nisbett & Ross
1980).'
H. Einhorn and R. Hogarth (1981)
The following are also taken from the text:
'If one considers the rather typical findings that
clinical judgments tend to be (a) rather unreliable (in
at least two of the three senses of that term), (b) only
minimally related to the confidence and amount of
experience of the judge, (c) relatively unaffected by
the amount of information available to the judge, and
(d) rather low in validity on an absolute basis, it
should come as no great surprise that such judgments are
increasingly under attack by those who wish to
substitute actuarial prediction systems for the human
judge in many applied settings....I can summarize this
ever-growing body of literature by pointing out that
over a very large array of clinical judgment tasks
(including by now some which were specifically selected
to show the clinician at his best and the actuary at his
worst), rather simple actuarial formulae typically can
be constructed to perform at a level no lower than that
of the clinical expert.'
L. R. Goldberg (1968)
Simple models or simple processes?
Some research on clinical judgments
American Psychologist, 1968, 23(7) p.483-496
'The various studies can thus be viewed as repeated
sampling from a uniform universe of judgement tasks
involving the diagnosis and predication of human
behavior. Lacking complete knowledge of the elements
that constitute this universe, representativeness cannot
be determined precisely. However, with a sample of about
100 studies and the same outcome obtained in almost
every case, it is reasonable to conclude that the
actuarial advantage is not exceptional but general and
likely to encompass many of the unstudied judgement
tasks. Stated differently, if one poses the query:
Would an actuarial procedure developed for a particular
judgement task (say, predicting academic success at my
institution) equal or exceed the clinical method?", the
available research places the odds solidly in favour of
an affirmative reply. "There is no controversy in social
science that shows such a large body of qualitatively
diverse studies coming out so uniformly....as this one
(Meehl J. Person. Assess, 50,370 (1986)".'
The distinction between collecting observations and integrating it is
further brought out vividly by Meehl (1989):
'Surely we all know that the human brain is poor at
weighting and computing. When you check out at a
supermarket you don't eyeball the heap of purchases and
say to the clerk, "well it looks to me as if it's about
$17.00 worth; what do you think?" The clerk adds it up.
There are no strong arguments....from empirical
studies.....for believing that human beings can assign
optimal weight in equations subjectively or that they
apply their own weights consistently.'
P. Meehl (1986)
Causes and effects of my disturbing little book
J Person. Assess. 50,370-5,1986
'Distributional information, or base-rate data, consist
of knowledge about the distribution of outcomes in
similar situations. In predicting the sales of a new
novel, for example, what one knows about the author, the
style, and the plot is singular information, whereas
what one knows about the sales of novels is
distributional information. Similarly, in predicting the
longevity of a patient, the singular information
includes his age, state of health, and past medical
history, whereas the distributional information consists
of the relevant population statistics. The singular
information consists of the relevant features of the
problem that distinguish it from others, while the
distributional information characterises the outcomes
that have been observed in cases of the same general
class. The present concept of distributional data does
not coincide with the Bayesian concept of a prior
probability distribution. The former is defined by the
nature of the data, whereas the latter is defined in
terms of the sequence of information acquisition.
The tendency to neglect distributional information and
to rely mainly on singular information is enhanced by
any factor that increases the perceived uniqueness of
the problem. The relevance of distributional data can be
masked by detailed acquaintance with the specific case
or by intense involvement with it........
The prevalent tendency to underweigh or ignore
distributional information is perhaps the major error of
intuitive prediction. The consideration of
distributional information, of course, does not
guarantee the accuracy of forecasts. It does, however,
provide some protection against completely unrealistic
predictions. The analyst should therefore make every
effort to frame the forecasting problem so as to
facilitate utilising all the distributional information
that is available to the expert.'
A. Tversky & D. Kahneman (1983)
Extensional Versus Intuitive Reasoning: The Conjunction
Fallacy in Probability Judgment Psychological Review
v90(4) 1983
'The possession of unique observational capacities
clearly implies that human input or interaction is often
needed to achieve maximal predictive accuracy (or to
uncover potentially useful variables) but tempts us to
draw an additional, dubious inference. A unique capacity
to observe is not the same as a unique capacity to
predict on the basis of integration of observations. As
noted earlier, virtually any observation can be coded
quantitatively and thus subjected to actuarial analysis.
As Einhorn's study with pathologists and other research
shows, greater accuracy may be achieved if the skilled
observer performs this function and then steps aside,
leaving the interpretation of observational and other
data to the actuarial method.'
R. Dawes, D. Faust and P. Meehl (1989)
ibid.
see http://www.longley.demon.co.uk/Frag.htm for elaboration.
--
David Longley (check end reply line #)
Longley Consulting London, UK
Behaviour Assessment & Profiling Technology,
Research, Data Analysis and Training Services,
Small IT Systems http://www.longley.demon.co.uk