QUALITATIVE VALIDATION PROCEDURES
By
Lucio Muñoz
munoz@interchange.ubc.ca
or at http://www.truesustainability.com
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
Where:
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 ]
|
F1 |
S |
1 |
VI |
|
F2 |
S |
2 |
NVI |
|
F3 |
S |
2 |
NVI |
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
important perceptions(NVI)
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:
See here the
expected theory-practice-perception typologies
Examples of information generated when the
validation procedures described above are apply to real data are provided
below:
Theory-practice typologies, countries and
region
See here examples
of theory-practice matching: dichotomy form
See here examples
of theory-practice matching: trichotomy form
Theory-perception typologies, countries
and region
See here examples
of theory-perceptions matching: average dichotomy
See here examples
of theory-perceptions matching: average trichotomy
See here examples
of theory-perceptions matching: simple majority dichotomy
See here examples
of theory-perceptions matching: simple majority trichotomy
Practice-perception typologies, countries
and region
See here examples
of practice-perception matching: average dichotomy
See here examples
of practice-perception matching: average trichotomy
See here examples
of practice-perception matching: simple manority dichotomy
See here examples
of practice-perception matching: simple majority trichotomy
Theory-practice-perception typologies,
countries and region
See here examples
of theory-practice-perception matching: average dichotomy
See here examples
of theory-practice-perception matching: average trichotomy
See here examples
of theory-practice-perception matching: simple majority dichotomy
See here examples
of theory-practice-perception matching: simple majority trichotomy
Theory-practice-perception,
See here
examples of theory-practice-perceptions, non-local officials
See here
examples of theory-practice-perceptions, local officials
Existing deforestation theories and
theory-practice-perception typologies
See here existing
deforestation theories: Costa Rica
See here existing
deforestation theories: El Salvador
See here existing
deforestation theories: Guatemala
See here existing
deforestation theories: Honduras
See here existing
deforestation theories: Nicaragua
See here
existing deforestation theories: Central America
CopyRights: You can use any material in this page if you find it
useful for academic or practical purposes, but please make a citation to Lucio
Muñoz.