PLAUSIBILITY
What is Plausibility?
Plausibility concerns the premises and preseumptions whereby we examine reality: microscopic or macroscopic; case-by-case or aggregated; precisely or approximately. If we are looking for the big picture, the details, no matter how remarkable, may be irrelevant. If we are comparing for a common characteristic, the idiosyncratic differences are “under the radar.” If a rough answer will do, looking for strict criteria is a waste of time. And visa versa. Each of the pairs characterizing plausibility are at the opposite ends of a parameter.
Theory vs. Practice
Are you looking at the pattern or the particulars? “A practice is a tangible and visible behavior.” So, seeing is believing. A theory is an intangible and implicit schema. So it focuses you on the forest rather than the trees. There is a joke that certain intellectuals will comment about a procedure that “Yes, I know it works in practice, but does it work in theory?” Both are correct, and either is acceptable. Try them together! The parameter that involves theory and practice can be called transaction.
Differentiate vs. Correlate
Do you prefer to deal with case studies, particular instances – or, do you want the average of a series, whether the mode or median? One way of describing these choices is either comparison or contrast. The basis for correlation is always some feature, characteristic, or aspect that instances share – the basis for differentiation is something that instances do NOT share. Entities always have both uniqueness and something in common. The parameter that underlies differentiate and correlate is formation of the variables.
Exact vs. Fuzzy
Linguist Benjamin Lee Worf identified two different kinds of entities to which quantification could be applied (see MacNeal). On the one hand there are entities with definite outlines (i.e., sticks, stones, men, mice, etc.), and on the other hand there are entities with indefinite outlines (i.e., water, air, entropy, gravity, etc.). Those things with definite outlines can be counted, exactly. Those things with indefinite outlines can only be measured, approximately. Approximate groupings have fuzzy boundaries. So, depending on the domain, either exact or fuzzy methods are required. The parameter that includes exact and fuzzy refers to precision.
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