The presence cube model
Other authors, including
Jack Aaron and
Ibrahim Tencer
define functions as expressing different strength and
value parameters. Specifically, the ego and superid blocks are
considered valued, while the ego and id blocks are considered strong. This
distinction also exists in Augusta's work, although in Augusta's work it seems
very little emphasized; it seems to me that the emphasis on the different
flavors of functions is more modern. Generally, valued functions are seen as
psychologically rewarding to attend but not necessarily skillful, and strong
functions are considered skillful to attend, but not necessarily rewarding.
(Throughout this post, I will refer to the idea of separation of strength and
value as "the presence cube", although the presence cube is a model developed
by Ibrahim Tencer linked above. Other authors like Jack Aaron do not use the
same terminology, but his idea similarly involves separate strength and value
and I will also refer to his modeling, and other authors' that I will not name
here, as the presence cube).
Dimensional Strength, or just
dimensionality
was an addendum theory developed by Vladimir Ermak and Aleksandr Bukalov in
the 90s. It characterizes gradations of strength within the weak and strong
blocks, and also suggests that the skilled use of functions varies in
generalizability; high dimensional (high strength) functions have access to
more domains of reflection than lower strength functions. Almost nobody in the
western community pays attention to the specifics of these domains regarding
whether people have access to experience, norms, situations, and time; instead
they regard dimensionality as mere gradations of strength.
It is important to recognize that dimensionality is aquadral. The creative function and ignoring function have identical dimensional strength, despite the ignoring function being out of the quadra. In the presence cube, the value dimension is called "priority" and is a simplification, but a reasonable approximate measure of which quadra blocks are emphasized in the different types within a quadra. As such, the presence cube model is a combination of quadras and aquadral dimensionality. Western Socionics in general is the idea that socionics is a theory of quadra values. The presence cube model with both quadra values and dimensional strength is thus a kind of hybrid model, that socionics is a theory of quadras but not entirely so, although Tencer, Aaron and other authors tend to regard quadras as the more important variable than dimensionality, which makes their models recognizably Western. However, the model that follows, which views socionics as entirely a theory of quadras and entirely ignores dimensionality, is more Western.
Axial Post-dimensionality model
The presence cube making use of dimensionality alongside quadra values has been heretofore the more popularized flavor of Western socionics. I wish to point out some flaws of dimensionality and the presence cube and present a different and simpler model.
What is a strong function, anyway? Socionics is a model of information
metabolism, which means that it is a model of how different people differently
pay attention to different sorts of information. The idea of strength and
value as separate, independent parameters of functions implies
more, that not only is there a hierarchical rank of some domains that are more
attended and some that are less attended, in addition there is an assumption
that these hierarchically ranked attentions are qualitatively different in
their skillfulness and in their rewardingness. Likewise, some functions (e.g.
the ignoring) are skillful but unrewarding, and hence, the theory goes,
ignored and hardly ever utilized, while others (e.g. the mobilizing) are
rewarding and therefore subject to frequent practice, but are inherently
unskilled, and are never fully grasped as skillfully as those people who have
this function as a stronger function.
The presence cube model has the following bad features:
- It assumes that some functions are rarely used, but nonetheless skillful, which is hard to measure (i.e., in principle how do you observe someone being skillful at something that they rarely or never do?).
- There are two parameters of function quality, value and strength. Two parameters are harder to measure, and harder to understand, than one.
- Having additional free parameters in a model dilutes the explanatory power of that model.
In my model, there is only one parameter to measure per function, degree of
attentional visibility, which I call strength. With fewer independent things
to measure, it is more straightforward to measure change in function strength
over time, which led me to my idea that the superid functions level up over
time, and thus change their strength as people grow and work on their
weaknesses.
In this model, the mobilizing function is a strong function, and the ignoring
function is a weak function and blind spot, equivalently weak or weaker than
the vulnerable function. The fact that dimensionality describes the mobilizing
function as weaker than the ignoring function is the most glaring issue with
the concept. I can not understand what property the ignoring function has that
makes it stronger or more skillful than the mobilizing function in any respect
whatsoever, as dimensionality predicts. It is very hard for me to understand
why the ignoring function which is rarely or never used could be considered
strong in any way. The classical view that the mobilizing function is weak,
makes more sense, and the classical notion of the mobilizing function as
"stubborn" or misguided can be seen sometimes, usually in young people that
have not developed much confidence and not developed their superid functions
very well. But usually, people have a lot of confidence in their mobilizing
functions, and emphasize this function a lot, and make it externally visible
-- and by using it frequently and leveling it up early on in their lives, they
usually become skillful at it pretty quickly.
I came up with the following simple math to translate between my axial view of model A, and the parameter of function strength output:
strength = axis*balance
strength = axis*balance
In other words, each of the four function axes (e.g. Ti and Te) has a overall
strength level and an imbalance towards one end. The logic axis of the LSE is
very strong, as it is the dominant axis, but extremely weighted towards Te, in
other words extremely imbalanced. The logic axis of the EII, by contrast, is
much weaker overall, and more balanced.
As an example of this model for proof of concept, with sort of ad hoc made up
numbers:
LSE
Str(Te) = Str(logic) * balance(logic) ≈ 0.99*0.99 ≈ 0.99
Str(Si) = Str(sensorics) * balance(sensorics) ≈ 0.9*0.7 ≈ 0.63
Str(Ne) = Str(intuition) * balance(intuition) ≈ 0.7*0.97 ≈ 0.7
Str(Fi) = Str(ethics) * balance(ethics) ≈ 0.5*0.45 ≈ 0.23
Str(Fe) = Str(ethics) * (1-balance(ethics)) ≈ 0.5*0.55 ≈ 0.28
Str(Se) = Str(sensorics) * (1-balance(sensorics)) ≈ 0.9*0.3 ≈ 0.27
Str(Ti) = Str(logic) * (1-balance(logic)) ≈ 0.99*0.01 ≈ 0.01
Str(Ni) = Str(intuition) * (1-balance(intuition)) ≈ 0.7*0.03 ≈ 0.01
This pretty well matches the function visibility weights that we normally see
in people. Note that these parameters, axis strength and axis balance, are 8
parameters, same number as if we treated each function as having independent
strength (and fewer parameters than the presence cube in which each function has an independent strength and value, so 16 parameters to measure).
The "developmental parameters" which change over time can be attributed to the
balance of the suggestive functions axis, and possibly the axis strengths for
the weaker axes will become better developed as people work on their
weaknesses and improve them. Most of the parameters will likely be more
stationary. Importantly, axial post-dimensionality allows for modeling these
developmental changes as nonstationary measurements over time without
introducing more parameters. We can simply model the development of people improving their weak points as increases in axis strength over time, while leaving the axis balance stationary.
The post-dimensionality axial model is better than the presence cube model.
- Axial post-dimensionality has fewer parameters to measure than the presence cube.
- It explains why equivalently valued functions in the presence cube have different strengths.
- It explains the property of the role and demonstrative function as being "half valued" -- which the presence cube also models, but with different numerical outputs. (specifically, the presence cube considers the demonstrative 4D+2P as much stronger than the role 2D+2P, which I think is dubious, and the ignoring 3D+1P as equal or roughly equal to the role 2D+2P. Tencer suggested to me a modification, where P (valuedness) is weighted more highly than D (dimensional strength, which allows for the role to be stronger than the ignoring; however, unless the coefficient for dimensionality is zero or very close to zero, the strength of the ignoring is estimated too highly for me)
- It more clearly describes what parameters are changing than the presence cube when developmental changes occur as people improve upon their weaknesses.
Dimensional strength is a bad theory and should be discarded. The presence
cube which incorporates dimensionality is a bad model and should be
discarded.
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