Distortion of Evaluation Across Boundaries


Abstract

When signals cross system boundaries, they do not retain their original evaluative meaning. This monograph defines Distortion of Evaluation Across Boundaries (DEAB) as the transformation of signal interpretation caused by differences in control structures, thresholds, and internal states between coupled systems.

We show that distortion is not noise or error. It is a structural consequence of coupling, where evaluation is reshaped by the receiving system’s configuration.


1. From Signal Integrity to Evaluation Distortion

Signal transmission:

  • preserves structure

Evaluation:

  • transforms meaning

A signal does not carry its meaning across systems. Meaning is reconstructed.


2. Defining Evaluation Distortion

Distortion of Evaluation Across Boundaries (DEAB) is defined as:

The alteration of signal interpretation resulting from differences in evaluation criteria, thresholds, and control structures between interacting systems.

Distortion affects:

  • perceived relevance
  • assigned weight
  • resulting control action

3. Source of Distortion

Distortion arises because:

  • systems do not share identical evaluation frameworks
  • control memory differs
  • normalization states vary

Each system:

  • reconstructs meaning independently

4. Transformation During Evaluation

When a signal enters a system:

  • it is filtered
  • weighted
  • contextualized

This process:

  • modifies its effective meaning

Thus:

Input is constant. Interpretation is not.


5. Types of Distortion


5.1 Amplified Interpretation

Signal is:

  • perceived as more significant

Effects:

  • increased influence
  • exaggerated response

5.2 Diminished Interpretation

Signal is:

  • perceived as less significant

Effects:

  • reduced influence
  • weak response

5.3 Altered Interpretation

Signal is:

  • reinterpreted differently

Effects:

  • unexpected response
  • misalignment

6. Role of Threshold Differences

Threshold variation:

  • determines whether signals activate

Differences lead to:

  • inconsistent activation across systems

This contributes to:

  • distortion

7. Influence of Control Memory

Control memory:

  • biases evaluation

Past configurations:

  • shape current interpretation

Distortion accumulates:

  • over time

8. Interaction With Interference

Multiple signals:

  • interact during evaluation

Interference:

  • amplifies distortion
  • alters signal priority

9. Feedback Reinforcement of Distortion

Distorted interpretation:

  • feeds back into the system

Feedback:

  • reinforces altered evaluation

Over time:

  • distortion stabilizes

10. Distortion Without Awareness

Systems:

  • do not detect distortion
  • experience interpretation as accurate

Distortion operates:

  • implicitly

11. Substrate Independence

Evaluation distortion appears in:

  • human cognition
  • machine learning systems
  • communication networks
  • organizational systems

The invariant lies in:

  • independent evaluation structures

12. Modeling Implications

Models must include:

  • transformation of signals
  • evaluation differences
  • distortion accumulation

Ignoring distortion leads to:

  • incorrect interpretation of interaction

13. Structural Consequence

Distortion transforms:

  • shared signals → divergent meanings

Coupled systems:

  • operate on different interpretations of the same input

14. Closing Statement

Signals do not carry meaning across systems unchanged.

They are reconstructed, reshaped, and reinterpreted based on the receiving system’s structure.

Distortion is not a flaw in interaction. It is a fundamental property of how systems evaluate across boundaries.