Logic Model Theory

A logic Model entity :

LM 

The list of 7 arguments of a logic model:

ARGS[LM] 

the arguments are separated into 2 parts

Abstract[LM]
Concrete[LM] 

Where the Abstract[LM] directs(or frame) the Concrete[LM]

• The Implementation of a Logic Model is based on Concrete[IM]. When implementing, the input starts to be actually transformed into output by the specified process (deterministic or non? or both?).
• The actual input, actual process, actual output, (and the evaluation) is

State[LM]

• The Evaluation of a Logic Model is to compare the output and the Success Criteria to check whether the SC is finished.
  • The Operational data is also the output generated along the process.

Evaluation[SC,State] =>  the SC[LM] is determined (whether or not SC is reached, is counted in State? ) 

• The Verification of a Logic Model is to verify the attribute of the model based on ARGS[LM]. It does not depend on the State.

Verification[SC, ARGS] => some SC is determined

Verification Model

• The verification counterpart of LM, VLM, which is also a logic model:
• The relation between LM and VML:

Context[VLM]: share with LM (?) 
Goal[VLM]: Verify LM 
Success Criteria[VLM]: Correctness, Speed, Completeness of Verification 
Ouput[VLM]: Verification results, predicting which conditions will meet in which conditions and why (additionally, the process information helps itself to optimize) 
Process[VLM]: Workflows (need examples)
Input[VLM]: The Logic Model which is in the accepted domain. 
Boundary condition:  ?

Iteration of Logic Model

• is this information contained in the logic model?
  • 1st option: separate to provide clarity
  • 2nd: but if we separate, then a single logic model does not contain "that much information? " So we just describe the iteration without specifying another logic model.

Could be simplified into

Abstract[LM] -[direct]->  Concrete[LM] -[direct]-> Implementation -[cause]-> State change -> Evaluate output and operational data -> 

where the SC[LM] is constantly verified through Evaluation to enhance determinism and generate information