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Psychology 265
This being the case, why do we speak of an abstract model when its essential
purpose is to integrate with the concrete mechanisms that have to be interpreted
and when in every possible direction that the explanation may take in psychol-
ogy (organicism, social interactions, sequences of behaviour, and so on), we
are faced solely with very concrete factors merely to be expressed - it seems - in
the form of equations in order to arrive at the causality sought? The reason is
that in reality we constantly come up against the need to choose between inter-
mediate multiple variables, which in fact it is a question of inferring, and that
the lack of data, at a point when a fairly precise hypothetical interpretation
would be needed in order to guide subsequent research, makes such a choice
difficult or impossible. Then, the great advantage of the abstract model is that
it defines both the necessary and sufficient conditions in the light of the adopt-
ed assumption and formulates them in a form sufficiently general - because
abstract - for it to be possible to apply them to a number of different concrete
purposes. In other words, the abstract model is by no means extraneous to
the concrete models psychology needs and which it continues to build up as
research progresses. It simply covers a number of possible concrete models,
thus forming a necessary intermediate stage between hypotheses that are too
general, because they are badly formalized or even badly formulated, and partic-
ular hypotheses that subsequent analysis wil make it possible to put forward
and to subject to experimental verification.
11. That being so, the great problem, as regards both the practical utilization of
abstract models and the intepretation that now has to be given of them with
respect to the general trends in psychology, is determining their degree of
objective and so to speak ontological equivalence to the reality that is being
studied. Of course, as far as positivism is concerned, which confines itself to
observables, the abstract model does not attain reality, since the latter is
meaningless without observables. The abstract model therefore merely repre-
sents a convenient idiom, like any logico-mathematical structure, and its con-
venience is marked by its simplicity as regards the subject and by the fact that
it lends itself to forecasting. But then the success of forecasts is bound up with
the experimental laws treated by the model and not with the latter’s capacity to
express the properties of an otherwise inaccessible underlying reality. For those,
on the other hand, who believe in a reality that goes beyond the observables and
in the possibility of causal explanations, the abstract model is only of interest if
it offers glimpses of real but still hidden processes accounting for observables
and if it thus facilitates explanation. Nevertheless, besides explanatory models
of this kind, it is possible to conceive from this second viewpoint models that
simply favour easy and conventional representation, until something better is
found, and because in this case provisional representation has a heuristic value
and leads to more adequate models.
A good example, which shows that this problem of the reality coefficient of
models is a real factor and not just a theoretical epistemological question, is
provided by the very simple instance of the ‘normal’ or Gaussian distribution
curve. It is still not so long ago that psychologists started from the assumption