Research Functionality
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The research team
The research team must be composed by individuals who are adapted to the environment. This adaptation refers to the unified field under study.
One of the differences between research on complex systems and simple systems is that simple systems have defined and accepted variables. Therefore, research on simple systems does not imply facing ambiguity.
Complex systems are ambiguous by definition and are therefore perceived as chaotic by all individual that is not adapted to them. The one who is adapted flows with them and does not have any perception of chaos.
What the research does is to make the adaptation process conscious, which until then contained intuitive elements that could not be explained.
The research team needs that the leader knows the environment under study or a homologous environment thoroughly. The other team members may be experts from different disciplines according to the function of the object under study.
Inference rules and logical derivation
The research of complex fields was possible thanks to the discovery of the structure of concepts that regulate their evolution and to the existence of the rules of inference and logical derivation that regulate concepts’ evolution.
Let us take the example of a rule applied to external gravitational forces that exert influence on countries:
“When a gravitational force is dominating, it defines the structure of the purpose of the one dominated. Domination is perceived by the lack of freedom of action of the verbal function of the one dominated.”
In any situation in which there are asymmetric relationships between countries it is necessary to validate forecasts on the basis of rules that correspond to them, as, for example, the one mentioned earlier.
Functional conceptual structure of the research of complex systems
Complex systems are studied seeking the foundation through experimentation based on preexisting secure knowledge.
This implies that the purpose of research work is to build foundations that will eventually be used in the diagnosis in order to exert influence on a given reality.
Research necessarily implies experimentation, which must allow repetition. That is to say, regardless of the number of times that the experience is carried out the result should always be the same.
Results from experimentation must be verifiable, that is, they have to able to be measured objectively, subjectively or through forecast.
In addition, the experimentation of the complex system under study must “work”, that is, this should be a real activity that produces a result for which such system has been designed. To work means an actual activity that cannot be simulated.
All research is based on preexisting secure knowledge. This knowledge must have quality assurance, be operable and verified.
Research on complex systems cannot be built on the basis of hypothetic knowledge. When there are only hypothesis then real foundations cannot be reached, instead, hypothetical foundations are built.
Diagnosis as an objective
The goal of research work is to diagnose the reality under analysis.
To diagnose implies the ability to forecast with foundation so as to be able to explain the phenomenon under analysis to exert influence on the environment it operates in. This is how the diagnosis functional concept is determined.
The diagnosis is the goal of a complex systems research.
When we define the groundings and forecast a given reality in static terms we refer to a state in such reality at a given moment, whilst when we refer to dynamic foundations and forecast we are talking about a reality in motion.
When we seek to influence we need to have a dynamic foundation and forecast.
Instead, when we seek to explain a given reality, a forecast and foundation at a given time is enough.
The diagnoses can be: Descriptive, Static, Causal or Functional.
Descriptive Diagnoses
These are the ones that explain reality by describing its operation. They are usual in the field of medicine, meteorology, sociology, etc.
Static Diagnoses
These are the ones that explain, in a logical way, a state of things from a given reality, isolating it from its context and evolution. They are usual in the field of formal sciences, some hard sciences, information systems, etc.
Causal Diagnoses
They diagnose a given reality from a systemic point of view on the basis of known causal relationships in order to define their possible evolution. They are frequently found in the field of physics, chemistry, anthropology, etc.
Functional Diagnoses
They diagnose a given reality from a conceptual point of view that integrates the systemic view on the basis of functionality. They are the ones that focus on the forecast based on the knowledge of the nature of such reality. They are usually found in future research.
The goal of diagnosing is to influence
To influence is to act with energy, having “internalized” the reality upon which one seeks to influence, to achieve the influential sympathy in order to set such reality in motion toward the determined “place”.
A diagnosis has the goal of influencing. Hence, it requires a high level of energy consumption. The diagnoses of simple systems, in turn, do not require a high level of energy consumption since in this case, only the understanding of its variables is required. The rationalistic approach impedes the diagnosis of complex systems.
