Operational definition

An operational definition is a demonstration of a process &mdash; such as a variable, term, or object &mdash; relative in terms of the specific process or set of validation tests used to determine its presence and quantity. Properties described in this manner must be publicly accessible so that persons other than the definer can independently measure or test for them at will. An operational definition is generally designed to model a conceptual definition.

The most basic operational definition is a process for identification of an object by distinguishing it from its background of empirical experience. The binary version produces either the result that the object exists, or that it doesn't, in the experiential field to which it is applied. The classifier version results in discrimination between what is part of the object and what is not part of it. This is also discussed in terms of semantics, pattern recognition, and operational techniques, such as regression.

For example, the weight of an object may be operationally defined in terms of the specific steps of putting an object on a weighing scale. The weight is whatever results from following the measurement procedure, which can in principle be repeated by anyone. It is intentionally not defined in terms of some intrinsic or private essence. The operational definition of weight is just the result of what happens when the defined procedure is followed. In other words, what's being defined is how to measure weight for any arbitrary object, and only incidentally the weight of a given object.

Operational definitions are also used to define system states in terms of a specific, publicly accessible process of preparation or validation testing, which is repeatable at will. For example, 100 degrees Celsius may be crudely defined by describing the process of heating water until it is observed to boil. An item like a brick, or even a photograph of a brick, may be defined in terms of how it can be made. Likewise, iron may be defined in terms of the results of testing or measuring it in particular ways.

One simple, every day illustration of an operational definition is defining a cake in terms of how it is prepared and baked (i.e., its recipe is an operational definition). Similarly, the saying, if it walks like a duck and quacks like a duck, it must be some kind of duck, may be regarded as involving a sort of measurement process or set of tests (see Duck test).

Limitations
If a definition invokes an historical event, such as having weighed an object sometime in the past, it is no longer repeatable, so it fails to qualify as operational. Similarly, a specific brick cannot be operationally defined by the process of making it, because that process is historical. (But see the example of the constellation Virgo below for a discussion of how to avoid this difficulty.)

Operational definitions are inherently difficult &mdash; arguably, even impossible &mdash; to apply to mental entities, because these latter are generally understood to be accessible only to the individual who experiences them and are therefore not independently verifiable. According to this line of thinking, a person's mental image of a brick cannot be operationally defined because it cannot be measured from outside that person's mood. Philosopher Daniel Dennett has argued that first-person operationalism is possible and desirable, using the anthropological version of the scientific method to bring the mind fully into the third-person realm required by science. As part of the Multiple Drafts Model of consciousness, Dennett defines a process he calls heterophenomenology, by which the mental is defined operationally in terms of the observed behavior of the subject.

Usefulness
Despite the controversial philosophical origins of the concept, particularly its close association with logical positivism, operational definitions have undisputed practical applications. This is especially so in the social and medical sciences, where operational definitions of key terms are used to preserve the unambiguous empirical testability of hypothesis and theory. Operational definitions are also important in the physical sciences.

Relevance to philosophy
The Stanford Encyclopedia of Philosophy says the following about Operationalism stored at http://plato.stanford.edu/entries/scientific-realism/ and written by Richard Boyd:

However, this rejection of operationalism as a general project destined ultimately to define all experiential phenomena uniquely did not mean that operational definitions  ceased to have any practical use or that they could not be applied in particular cases.

Relevance to science
Operational definitions are at their most controversial in the field of psychology, where intuitive concepts, such as intelligence need to be operationally defined before they become amenable to scientific investigation, for example, through processes such as IQ tests. Such definitions are used as a follow up to a conceptual definition, in which the specific concept is defined as a measurable occurrence. John Stuart Mill pointed out the dangers of believing that anything that could be given a name must refer to a thing and Stephen Jay Gould and others have criticized psychologists for doing just that. A committed operationalist would respond that speculation about the thing in itself, or noumenon, should be resisted as meaningless, and would comment only on phenomena using operationally defined terms and tables of operationally defined measurements.

A behaviorist psychologist might (operationally) define intelligence as that score obtained on a specific IQ test (e.g., the Wechsler Adult Intelligence Scale test) by a human subject. The theoretical underpinnings of the WAIS would be completely ignored. This WAIS measurement would only be useful to the extent it could be shown to be related to other operationally defined measurements, e.g., to the measured probability of graduation from university. 

The special theory of relativity can be viewed as the introduction of operational definitions for simultaneity of events and of distance.

Relevance to business
On October 15 1970, the West Gate Bridge in Melbourne, Australia collapsed, killing 35 construction workers. The subsequent enquiry found that the failure arose because engineers had specified the supply of a quantity of flat steel plate. The word flat in this context lacked an operational definition, so there was no test for accepting or rejecting a particular shipment or for controlling quality.

In his managerial and statistical writings, W. Edwards Deming placed great importance on the value of using operational definitions in all agreements in business. As he said:


 * "An operational definition is a procedure agreed upon for translation of a concept into measurement of some kind." - W. Edwards Deming


 * "There is no true value of any characteristic, state, or condition that is defined in terms of measurement or observation. Change of procedure for measurement (change of operational definition) or observation produces a new number." - W. Edwards Deming

Relevance to process
Operational, in a process context, also can denote a working method or a philosophy that focuses principally on cause and effect relationships (or stimulus/response, behavior, etc.) of specific interest to a particular domain at a particular point in time. As a working method, it does not consider issues related to a domain that are more general, such as the ontological, etc.

The term can be used strictly within the realm of the interactions of humans with advanced computational systems. In this sense, an AI system cannot be entirely operational (this issue can be used to discuss strong versus weak AI) if learning is involved.

Given that one motive for the operational approach is stability, systems that relax the operational factor can be problematic, for several reasons, as the operational is a means to manage complexity. There will be differences in the nature of the operational as it pertains to degrees along the end-user computing axis.

For instance, a Knowledge Based Engineering system can enhance its operational aspect and thereby its stability through more involvement by the SME, of course, thereby opening up issues of limits that are related to being human, in the sense that, many times, computational results have to be taken at face value due to several factors (hence the Duck test's necessity arises) that even an expert cannot overcome. The end proof may be the final results (reasonable facsimile by simulation or artifact, working design, etc.) that are not guaranteed to be repeatable, may have been costly to attain (time and money), and so forth.

Many domains, with a numerics focus, use limits logic to overcome the Duck test necessity with varying degrees of success. Complex situations may require logic to be more non-monotonic than not raising concerns related to the qualification, frame, and ramification problems.

Temperature
The thermodynamic definition of temperature, due to Nicolas Léonard Sadi Carnot, refers to heat "flowing" between "infinite reservoirs". This is all highly abstract and unsuited for the day-to-day world of science and trade. In order to make the idea concrete, temperature is defined in terms of operations with the gas thermometer. However, these are sophisticated and delicate instruments, only adapted to the national standardization laboratory.

For day-to-day use, the International Practical Temperature Scale (IPTS) is used, defining temperature in terms of the electrical resistance of a thermistor, with specified construction, calibrated against operationally defined fixed points.

Electric current
Electric current is defined in terms of the force between two infinite parallel conductors, separated by a specified distance. This definition is too abstract for practical measurement, so a device known as a current balance is used to define the ampere operationally.

Mechanical hardness
Unlike temperature and electric current, there is no abstract physical concept of the hardness of a material. It is a slightly vague, subjective idea, somewhat like the idea of intelligence. In fact, it leads to three more specific ideas:


 * 1) Scratch hardness measured on Mohs' scale;
 * 2) Indentation hardness; and
 * 3) Rebound, or dynamic, hardness measured with a Shore scleroscope.

Of these, indentation hardness itself leads to many operational definitions, the most important of which are:


 * 1) Brinell hardness test&mdash;using a 10 mm steel ball;
 * 2) Vickers hardness test&mdash;using a pyramidal diamond indenter; and
 * 3) Rockwell hardness test&mdash;using a diamond cone indenter.

In all these, a process is defined for loading the indenter, measuring the resulting indentation and calculating a hardness number. Each of these three sequences of measurement operations produces numbers that are consistent with our subjective idea of hardness. The harder the material to our informal perception, the greater the number it will achieve on our respective hardness scales. Furthermore, experimental results obtained using these measurement methods has shown that the hardness number can be used to predict the stress required to permanently deform steel, a characteristic that fits in well with our idea of resistance to permanent deformation. However, there is not always a simple relationship between the various hardness scales. Vickers and Rockwell hardness numbers exhibit qualitatively different behaviour when used to describe some materials and phenomena.

The constellation Virgo
The constellation Virgo is a specific constellation of stars in the sky, hence the process of forming Virgo cannot be an operational definition, since it is historical and not repeatable. Nevertheless, the process whereby we locate Virgo in the sky is repeatable, so in this way, Virgo is operationally defined. In fact, Virgo can have any number of definitions (although we can never prove that we are talking about the same Virgo), and any number may be operational.

Duck typing
In advanced modeling, with the requisite computational support such as KBE, mappings must be maintained between a real-world object, its abstracted counterparts as defined by the domain and its experts, and the computer models. Mismatches between domain models and their computational mirrors can raise issues that are apropos to this topic. Techniques that allow the flexible modeling required for many hard problems must resolve issues of identity, type, etc. which then lead to methods, such as Duck typing.