How to Define Your Concept a.k.a. Concept Explication [Part 2]

This is part 2 (the final part) of a series, be sure to read part 1 as well.

A key to research that can be used and repeated is the careful definition of the major concepts in the study. A hazy definition of a concept may enter into relationships with other variables, but since the concept was ill-defined the meaning of those relationships can be no better than ill-defined. The process by which concepts are defined for scientific purposes is called explication, that’s your ten-dollar-impress-your-grad-professor word of then day. Also in academia the word often substitutes for the word “explanation” becase it sounds much, much cooler. So, now that the intro is covered, let’s jump into part 2!

Author’s note: This post is based on a handout from my grad work and the monograph, “Fundamentals of Concept Formation in Empirical Science,” by Carl G. Hempel (1952) – citation at the end of the post.

  1. Apply Defining Criteria:  By this point in your defining you should have culled down your thinking to a few definitions. The more specific you can get, the better. Analyze  them by means of these criterions:
    1. Specificity, or how specific the definition currently is , in terms both of details of observation and lack of  sentences linking the various elements of the concept (the fewer the better). The more general the definition the worse off you are. Examples:
      1. It is more useful to record that Jim-Bob “watched Channel 13 from 7 to 9 p.m. yesterday evening” than to say he “watched TV last night.”
      2. A definition of “dissonance” as “any cognitive discrepancy” is less helpful than an extended definition that catalogs the various kinds of cognitions that can be discrepant with one another, the various means by which they might be that way, etc.
    2. Non-reification, Ok we’re getting a bit more complex here. Nothing insane, just pay attention. Avoid giving names to attributes that you might imagine exist, but that cannot be observed. You may think that there is a key factor that has not been observed, but that could be given empirical meaning by careful research. If this is the case, you are proposing a hypothetical construct (the hypothesis being that it does, in fact, exist). If you really need to do this, the first task of your research should then be a “validity check” on its existence. When you provide evidence of a hypothetical construct, it attains the more secure status of as a variable. If a hypothetical construct remains unobserved, it is considered a reification (see, took me a while, but we got around to  the definition), and other researchers are unlikely to be persuaded by your reference to it. The important thing is to recognize that status of all elements of your definition, and to design research that will demonstrate their empirical content.  Examples:
      1. Some common reifications in communication research are terms “catharsis,” “dissonance,” “group cohesiveness,” “coorientation,” and “attitude.”  So far, none of these things has ever been observed, yet they hold important positions in certain theoretical formulations.  The danger is that they may not exist, except in the minds of the theoreticians.
      2. By careful research, some hypothetical constructs that have gradually been converted into variables include “empathy,” “understanding,” “learning,” and “conformity.”  However, these concepts are tied to very specific operational definitions, and when they are used to cover other kinds of situations they are simply reified terms.
    3. Invariance of usage.  This is a simple one – the same person should use a term consistently. Sadly, this isn’t always the case. Some writers use the same term to refer to different things at different times. Even more common is the switching levels of analysis without making any terminological distinction. Examples:
      1. Marshall McLuhan jumps from discussion of individual differences in perception to statements about national character, historical epochs, and other macroscopic concepts (no surprise there, McLuhan was a bit all over the place).
      2. The term “generation” is a term used appropriately for analyzing families and other kinship systems. It can be is misapplied to differences between age groups in society as a whole in the notion of a generation gap.
    4. Inter-observer invariance – the measure of scientific usage would be that everyone uses the concept to mean the same thing. This level of agreement is practically impossible to achieve. But it is a useful goal to strive for, and careful application of the concept criteria and explanation can move you toward that goal.
  2. Set boundaries.  Perhaps the most important step in explication is to decide on clear boundaries for your concept. In meaning analysis, this is simply a matter of considering whether of not to include various lower concepts in your definition. In empirical analysis, boundaries are set by understanding which conditions are necessary and/or sufficient, and which are neither necessary or sufficient. In both cases, this stage of explication consists of stripping the concept of extra meanings. Examples:
    1. A study shows that the strength of an expressed opinion can be increased by reinforcing it through social approval. The author’s conclusion is that reinforcement is a necessary condition for opinion formation. A later study demonstrates that there are conditions under which opinions change without reinforcement. So the definition is watered-down, in that reinforcement becomes a sufficient condition, rather than a necessary one. Finally, it is found that in some instances opinions shift in a direct opposite to the pattern of reinforcement.  So, the element of reinforcement is eliminated from the definition of opinion formation, because it is neither necessary or sufficient.
  3. Tentatively define. Try to develop a satisfactory definition via empirical analysis. You may find that it is surprisingly brief and simplified. Simpler is better as long as you are satisfied that it covers what you want the concept to mean, and does not cover anything else. If an empirical definition eludes you, more research may be needed. So turn to meaning analysis and work on a list of lower concepts. Keep in mind, though, that this is an intermediary stage in the development of your concept.
  4. Define operationally. For each element of each concept that you retain in your final definition, you must specify at least one operational definition. The more specific the better, and the more carefully each operation is linked to your conceptual definition by clear reduction statements the better. It is not necessary to attempt to list all operational definitions; indeed, if your concept is not trivial, it will be impossible to list them all.  But it is necessary to demonstrate that each element of your definition is amenable to observation in real world experiences. Operational definition consists of stating the observable indicators of the attributes (properties or relations) involved, so that someone else can “know one when he sees one.” Operational definitions might be contrived in the form of interview questions, experimental manipulations, unobtrusive observations, content categories, etc.  The key to this final stage of explication is that all your reasoning and linkages be spelled out explicitly, so that someone else reading your work will know what you have done, what you think it represents conceptually, and why.

In the early stages of planning a research project, it is unnecessary to reduce operational definitions to precise terms.  What is needed is to demonstrate conclusively that you can do so when the time comes to design an empirical study.

This was Part 2 and the thrilling conclusion to: How to Define Your Concept a.k.a. Concept Explication, be sure to read Part 1.

Citation: Hempel, C. G. (1952). Fundamentals of concept formation in empirical science. Chicago: University of Chicago Press.

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One Response to How to Define Your Concept a.k.a. Concept Explication [Part 2]

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