Propositions and Research in Global Brain Theory
This space uses a formal approach for the creation of better theory. Here, the nodes and connectors are the theory. Rules: For this experiment in theory building, only two "things" are allowed - 1. Concepts (boxes - measurable things) and 2. Connections (CAUSAL relationships supported by research). To test the validity of a relation, try to say it as a proposition (e.g. "more A causes less B").

Additional "Rules" for this experimental theory building space: Concepts, Connections, Validity, Complexity, Systemicity - how to accelerate the creation of a better theory

A concept is accepted as "valid" when two or more causal arrows are pointed towards it.

Of course, adding additional concepts with causal arrows to existing concepts improves the validity of the existing concept. However, the newly added concepts are not valid because they are not resulting from two or more causal connections. The key to the puzzle is to make the map large enough so that the concepts are interconnected with one another.

A connection is "valid" when it is supported by empirical research. More research (and research that measures the causal relationship more directly) is better. And, the thickness of the connecting lines should indicate the quantity and quality of the research. Alternatively, a dashed or dotted connecting arrow may be used to indicate a proposed casual relationship between two concepts. Proposed connections are indications of where more research is needed.

Researchers could then cite the map & the project as a source "calling" for additional research. By choosing to research certain connections, researchers can identify and focus on "high leverage" research - that is to say, research that will more rapidly increase the Systemicity of the theory - and therefore more rapidly increase the usefulness of the theory in practical application.

It is *possible* to have a concept that is not directly measurable. However, such concepts should be a small minority of the theory. Also, non-measurable concepts should be surrounded by concepts that are measurable.

Overall, the quality of the map is measured in two ways. First, the Complexity - the number of valid concepts in the map. This is a measurement of the "breadth" of the theory. Does the map cover one city, a nation, or the world?

Second, the map is measured by its "Systemicity" - this is the "depth" of the map. Metaphorically, this asks if your map of the world consists of a set of disconnected dots with names of cities, or are the dots connected with roads? Systemicity is calculated as follows: First, identify the total number of concepts (boxes) in the map (the Complexity - as noted above). Second, identify the number of "concatenated" concepts (those with two or more causal arrows pointing towards them). Third, divide the total number by the concatenated number to give a ratio. For example, if the map contains 8 concepts and two are concatenated, the Systemicity is 2 divided by 8 so S = 0.25.

The goal is to have a theory with a high level of systemicity. A high level of Complexity is probably also useful for a large theory. Again, concepts must be measureable and relationships must be causal (and supported by empirical research).

As the theory builds and emerges, some conversations may occur - negotiating new meanings for concepts and their relationships.

Have Fun!


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