Editing Operational definition (section)

== Application ==
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]].

=== Philosophy ===
The ''Stanford Encyclopedia of Philosophy'' entry on scientific realism, written by [[Richard Boyd]], indicates that the modern concept owes its origin in part to [[Percy Williams Bridgman]], who felt that the expression of scientific concepts was often abstract and unclear. Inspired by [[Ernst Mach]], in 1914 Bridgman attempted to redefine unobservable entities concretely in terms of the physical and mental operations used to measure them.<ref name=Boyd>{{cite encyclopedia|last=Boyd|first=Richard|title=Scientific Realism|url=https://plato.stanford.edu/archives/sum2010/entries/scientific-realism/|encyclopedia=Stanford Encyclopedia of Philosophy|access-date=8 February 2013}}</ref> Accordingly, the definition of each unobservable entity was uniquely identified with the instrumentation used to define it. From the beginning objections were raised to this approach, in large part around the inflexibility. As Boyd notes, "In actual, and apparently reliable, scientific practice, changes in the instrumentation associated with theoretical terms are routine.  and apparently crucial to the progress of science. According to a 'pure' operationalist conception, these sorts of modifications would not be methodologically acceptable, since ''each'' definition must be considered to identify a ''unique'' 'object' (or class of objects)."<ref name=Boyd />

=== Science ===
The [[theory of relativity|special theory of relativity]] can be viewed as the introduction of operational definitions for [[relativity of simultaneity|simultaneity of events]] and of [[length contraction|distance]], that is, as providing the operations needed to define these terms.<ref name=Woodhouse>{{cite book |title=Special relativity |author=NMJ Woodhouse |page=58 |url=https://books.google.com/books?id=ggPXQAeeRLgC&pg=PA50 |isbn=1-85233-426-6 |publisher=Springer |location=London |year=2003}}</ref>

In [[quantum mechanics]] the notion of operational definitions is closely related to the idea of [[observables]], that is, definitions based upon what can be measured.<ref name=Isham>{{cite book |title=Lectures on Quantum Theory |author= C. J. Isham |page=95 |url=https://books.google.com/books?id=xR3sS2hEFzcC&q=observable+operational+definition+quantum&pg=PA95|isbn=1-86094-001-3 |publisher=Imperial College Press |year=1995 }}</ref><ref name=Blank>{{cite book |title=Hilbert Space Operators in Quantum Physics |author1=Jiří Blank |author2=Pavel Exner |author3=Miloslav Havlíček |isbn=1-56396-142-3 |publisher=Springer |year=1994 |url=https://books.google.com/books?id=V0BSIoGXHLQC&q=observable+operational+definition+quantum&pg=PA252|page=252 }}</ref>

Operational definitions are often most challenging in the fields of [[psychology]] and [[psychiatry]], where intuitive concepts, such as [[intelligence (trait)|intelligence]] need to be operationally defined before they become amenable to scientific investigation, for example, through processes such as [[IQ test]]s.

=== 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.

=== General 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.

=== In computing ===
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Science uses computing. Computing uses science. We have seen the development of computer science. There are not many who can bridge all three of these. One effect is that, when results are obtained using a computer, the results can be impossible to replicate if the code is poorly documented, contains errors, or if parts are omitted entirely.<ref>Collberg, C., Roebsting, T. (2016) "Repeatability in Computer Systems Research" Communications of the ACM, Vol. 59, No. 3, pages 62–69 (via [https://cacm.acm.org/magazines/2016/3/198873-repeatability-in-computer-systems-research/abstract acm.org])</ref>

Many times, issues are related to persistence and clarity of use of variables, functions, and so forth. Also, systems dependence is an issue. In brief, length (as a standard) has matter as its definitional basis. What pray tell can be used when standards are to be computationally framed?

Hence, operational definition can be used within the realm of the interactions of humans with advanced computational systems. In this sense, one area of discourse deals with computational thinking in, and with how it might influence, the sciences.<ref>"Computational Thinking in Science" American Scientist, Jan/Feb 2017 (via [https://www.americanscientist.org/issues/pub/2017/1/computational-thinking-in-science My American Scientist])</ref> To quote the American Scientist:
* The computer revolution has profoundly affected how we think about science, experimentation, and research.

One referenced project pulled together fluid experts, including some who were expert in the numeric modeling related to computational fluid dynamics, in a team with computer scientists. Essentially, it turned out that the computer guys did not know enough to weigh in as much as they would have liked. Thus, their role, to their chagrin, many times was "mere" programmer.

Some [[knowledge-based engineering]] projects experienced similarly that there is a trade-off between trying to teach programming to a domain expert versus getting a programmer to understand the intricacies of a domain. That, of course, depends upon the domain. In short, any team member has to decide which side of the coin to spend one's time.

The International Society for Technology in Education has a brochure detailing an "operational definition" of computational thinking. At the same time, the ISTE made an attempt at defining related skills.<ref>"Operational Definition of Computational Thinking" (for K–12 Education) 2011 (via [https://www.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf website])</ref>

A recognized skill is tolerance for ambiguity and being able to handle open-ended problems. For instance, a [[knowledge-based engineering]] system can enhance its operational aspect and thereby its stability through more involvement by the [[subject-matter expert]], thereby opening up issues of limits that are related to being human. As in, 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 (observational)|artifact]], working design, etc.) that are not guaranteed to be repeatable, may have been costly to attain (time and money), and so forth.

In advanced modeling, with the requisite computational support such as knowledge-based engineering, 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 apropos 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. Many domains, with a [[Numerical analysis|numerical]] focus, use limit theory, of various sorts, to overcome the duck test necessity with varying degrees of success. Yet, with that, issues still remain as representational frameworks bear heavily on what we can know.

In arguing for an object-based methodology, Peter Wegner<ref>Wegner, P. () "Beyond Computable Functions" ''Specification of Parallel Algorithms'' Page 37 American Mathematical Society (via [https://books.google.com/books?id=vg5RyQ1bcPYC&pg=PA37 Google])</ref>  suggested that "positivist scientific philosophies, such as operationalism in [[physics]] and behaviorism in psychology" were powerfully applied in the early part of the 20th century. However, computation has changed the landscape. He notes that we need to distinguish four levels of "irreversible physical and computational abstraction" (Platonic abstraction, computational approximation, functional abstraction, and value computation). Then, we must rely on interactive methods, that have behavior as their focus (see duck test).