Jig: Cause-Effect
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Unur Sukhbaatar
Unur Sukhbaatar is a fellow at CIPA (Cornell Institute of Public Affairs) graduating in 2021. He has a background in economics and business. He is also a candidate for the Systems Thinking, Modeling, and Leadership (STML) Certificate. Before joining Cornell University, Mr. Sukhbaatar had worked as a lecturer and a researcher at the University of Finance and Economics in Mongolia. His current research interest covers the application of systems thinking in policy and political analysis.
More posts by Unur Sukhbaatar
Unur Sukhbaatar

This blog is part of a set of blogs under the tag "cognitive jigs."Be sure to check out the tag to read them as a group and learn how cognitive jigs are at play in our everyday lives.
A cause-effect jig is one variant of the Barbell Jig. Because of it's common usage, cause-effect is treated as a separate jig. Note also that cause-effect jigs take different forms.
In the simplest form, the cause-effect jig shows a relationship between A and B where A causes B. We can put anything in place of A and B. For example, too much rain [A] causes a flood [B] as shown in Figure 1.
Figure 1. Simple cause-effect jig
However, this use of cause and effect is limitless. For example, we can combine two or more cause-effect jigs to create a causal chain of relationships as shown in Figure 2. Building off of our previous example, too much rain causes a flood which in turn causes loss of harvest. The loss of harvest may cause starvation and so on...
Figure 2. A chain of cause-effect relationships
Two or more cause-effect jigs can be combined in to a set of circular relationships as seen in Figure 3. Below you see that A causes B and B causes C which is a two-way causality and is very common in social sciences. For example, in economics, demand is dependent on market price. And the market price is dependent on demand.
Figure 3. A circular reference is a combination of two or more cause-effect jigs
The cause-effect jig is a type of Barbell, so it can therefore become a relationship distinction systems (RDS) of cause-effect (see Barbell Jig blog). For example, too much rain does not need to cause a flood, if there are flood control measures acting as a relationship between the. Figure 4 shows that flood control is a whole system comprised of different parts such as dams, canals, and barriers (and the interactions between them).
Figure 4. RDS in a cause-effect jig
Want to play with these jigs? Below are some interactive resources you can explore...check out this Jig Map (you can duplicate the map for your own use):