Nomological network

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A nomological[1] network can be viewed as a representative constructs of a study and its observable manifestations and the interrelationships between at least two or more constructs.

Christ commanded that his disciples make the people sit down in groups of ten networked together in ranks of tens and hundreds until all were connected together in what science of philosophy might call an nomological network.

There are several necessary elements of a nomological network those lawlike elements would be directed by Christ. If we are to identify His kingdom or His Church as a divinely inspired nomological network these elements would be observable through interrelationships of those constructs or individuals or their families.

The science tells us there must be:

  1. At least two constructs;
  2. One or more theoretical propositions[2], specifying a comparable linkages in the form of a relation between constructs.
  3. Correspondence rules, allowing each construct to be measured empirically.[3] Such a rule is said to "operationalize" the construct.[4]
  4. Empirical linkages represent hypotheses before data collection, empirical generalizations after data collection.
  1. The term "nomological" derives from the Greek, meaning "lawful", or in philosophy of science terms, "law-like".
  2. A theoretical proposition is a statement about the concepts that may be judged as true or false if it refers to observable phenomena.
  3. Since empirical means experienced or observed rather than mere theory then an empirical measure is a random measure arising from a particular realization of a sequence of random variables in mathematics. The motivation for studying empirical measures is that it is often impossible to know the true underlying probability measurement.
  4. Operationalization means turning abstract concepts into measurable observations. Although some concepts, like height or age, are easily measured, others, like spirituality or anxiety, are not. Through operationalization, you can systematically collect data on processes and phenomena that aren't directly observable.