QUALITATIVE VALIDATION PROCEDURES
By Lucio Muñoz
A simple knowledge generation model
The best way to understand the nature of traditional validation procedures is to look at how they fit the simple knowledge generation model(R) described below:
1) K = T + E + P
K = Knowledge
T = Theory is important
t = Theory is not important
E = Practice is important
e = Practice is not important
P = Perceptions are important
p = Perceptions are not important
The above formula indicates that we can generate knowledge(K) in different ways depending on whether or not we are focused only on theory(T) or only on practice(E) or only on perceptions(P) or focused in any combination of them at the same time. One of the main implications of the above model is that we can generate knowledge even in the absence of theory.
Extreme knowledge and validation gaps
According to the formula 1 there can be
three types of extreme knowledge models: those where only theory is
important(K1 = Tep); models where only the practice is important(
Pseudo-scientific knowledge and partial validation procedures
According to formula 1 there can be three types of pseudo-scientific models: those where both theory and practice are important (K4 = TEp); models where only theory and perceptions are important(K5 = TeP); and those where both practice and perceptions are important(K6 = tEP). Notice that all these pseudo-scientific models are subject to partial validation procedures as each of them assumes that one of the components of knowledge is not important. The fact that validation gaps exist, do not erode the scientific quality attached to those models. Most traditional research methods are based on the premise that the theory must match the practice or that the theory must match the perceptions, and not many traditional models appear to be focused on the other possible notion according to formula 1 that the practice must match the perceptions. Notice that if we drop the factor that is not important in each of the pseudo-scientific knowledge models described above we are given an illusion of completeness by eliminating complexity and we get K4 = TE ; K5 = TP ; and K6 = EP. This is what really happens when we assume away complexity to simplify things, and the most common models used under these conditions is K4 = TE or K5 = TP
True scientific knowledge and full validation procedures
According to formula 1, there can be only one true scientific knowledge model, those where the theory, the practice, and the perceptions are important at the same time(K7 = TEP). Only then, full validation procedures are considered binding because the theory, the practice, and the perceptions must match at the same time. Here as much complexity as possible is included to reflect full validation procedures and to achieve consistency by using knowledge gaps to validate or invalidate or create new types of knowledge: theoretical, practical, perceptional, or any combination of them.
Quantitative / Qualitative validation procedures
Validation procedures based on quantitative methods usually work at the level of pseudo-scientific models as most of them usually assume that behavior, which is closely related to perceptions can be easily predicted and/or regulated or can be assumed as homogenous. Qualitative methods are not usually associated with validation goals as they operate in my opinion in the area of extreme knowledge models as they are usually interested on particular theories or on particular practices or on particular perceptions as they relate to one or few cases. Because qualitative methods have no strong emphasis on validation procedures they are considered be less scientifically sound than quantitative methods are thought to be. Yet, as pointed out above, even quantitative research is usually subjected only to partial validation procedures because of its heavy reliance of assuming complexity away.
Qualitative comparative validation procedures
Four types of qualitative validation procedures are introduced: theory-practice matching(TE); theory- perception matching(TP); practice- perception matching(EP); and theory-practice-perception matching(TEP). These validation procedures hold when all the information is either in trichotomy or dichotomy form, and they can be used to integrate the deforestation information provided in the deforestation data page, the perception data provided in the perception date page, and the theoretical data found in the deforestation theory page.
How do the qualitative comparative validation procedures actually work?
To show in simple terms how these validation procedures can be implemented and replicated, considered the following hypothetical information:
a) we are interested in three deforestation factors(F): F1, F2, and F3.
b) theories(T) in dichotomy form indicate that we should expect these three factors F1, F2, and F3 to display strong pressures on deforestation(S);
c) it was found that the dichotomy practice(E) indicates that factor F1 shows increasing pressures on deforestation(1); factor F2 reflects decreasing pressures on deforestation(2) and factor F3 displays also decreasing pressures on deforestation(2)
d) it was found that dichotomy perceptions(P) suggest that factor F1 is a very important causal factor(VI); and that both factor F2 and factor F3 are considered to be not very important deforestation factors(NVI).
All the hypothetical information above is summarized in the table below:
[ F ] [ T ] [ E ] [ P ]
Now, based on the information in the table above, we can summarize how each of the qualitative validation procedures can be applied and its implications:
1. matching theory and practice
If we look only at columns T and E, we can get the following information:
F1 = S.1 = strong theoretical causality(S) matches increasing pressure in practice(1)
F2 = S.2 = strong theoretical causality(S) does not match decreasing pressures in practice(2)
F3 = S.2 = strong theoretical causality(S) does not match decreasing pressures in practice(2)
2. matching theory and perceptions
If we look only at columns T and P, we can get the following information:
F1 = S.VI = strong theoretical causality(S) matches very important perceptions(VI)
F2 = S.NVI= strong theoretical causality(S) does not match not very important perceptions(NVI).
F3 = S.NVI = strong the strong theoretical causality(S) does not match not very important perceptions(NVI).
3. matching practice and perceptions
If we look only at columns E and P, we can get the following information:
F1 = 1.VI = increasing practical pressures(1) do match very important perceptions(VI)
F2 = 2.NVI = decreasing practical pressures(2) do match not very important perceptions(NVI)
F3 = 2.NVI = decreasing practical pressures(2) do match not very important perceptions(NVI)
4. matching theory, practice, and perception
If we look at columns T, E and P at the same time, we can get the following information:
F1 = S.1.VI = strong theoretical role(S), increasing pressures in practice(1), and very important perceptions(VI)
match at the same time
F2 = S.2.NVI = strong theoretical role(S) does not match decreasing practical pressures(2) and not very
F3 = S.2.NVI = strong theoretical role(S) does not match decreasing practical pressures(2) and not very important perceptions(NVI)
An examples of information generated when the validation procedures described above are apply to ideal data is provided below:
Examples of information generated when the validation procedures described above are apply to real data are provided below:
Theory-practice typologies, countries and region
Theory-perception typologies, countries and region
Practice-perception typologies, countries and region
Theory-practice-perception typologies, countries and region
Existing deforestation theories and theory-practice-perception typologies
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