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When Evaluation Stops Updating

1. Evaluation Is Not Static

Evaluation is often treated as a fixed capacity: a system evaluates inputs and updates conclusions accordingly. In practice, evaluation itself is regulated.

Cognitive systems can continue evaluating while no longer updating.

2. Evaluation vs Update

A critical distinction:

  • Evaluation refers to comparing signals against criteria.
  • Updating refers to modifying internal state based on evaluation.

Evaluation can occur without producing state change.

This creates the appearance of responsiveness without adaptation.


3. How Evaluation Freezes

Evaluation stops updating when:

  • weighting parameters stabilize
  • dominance hierarchies lock
  • feedback reinforces existing priorities
  • termination criteria override discrepancy signals

The system still “checks” inputs, but the outcome is predetermined.


4. Feedback-Induced Evaluation Rigidity

Repeated successful evaluations reinforce:

  • trusted signals
  • familiar criteria
  • dominant interpretations

Over time:

  • alternative signals are down-weighted
  • discrepancies lose impact
  • evaluation becomes confirmatory

The system evaluates to maintain stability.


5. The Appearance of Open-Mindedness

Systems with frozen evaluation often appear:

  • attentive
  • articulate
  • responsive
  • consistent

They can restate opposing signals accurately while never integrating them.

Evaluation occurs. Updating does not.


6. Why Evidence Loses Power

Evidence influences cognition only if it can alter control parameters. When:

  • closure thresholds dominate
  • recursion is suppressed
  • feedback favors consistency

evidence is processed but neutralized.

This is not rejection. It is structural insulation.


7. Evaluation Saturation

As evaluation rigidity increases:

  • additional input yields diminishing returns
  • processing cost rises
  • variability decreases

The system enters a saturated evaluation regime.


8. Substrate Independence

Evaluation freeze occurs in:

  • human cognition
  • automated decision systems
  • learning algorithms under fixed reward structures

The invariant lies in control-layer saturation.


9. Diagnostic Signal

If a cognitive system:

  • acknowledges new information
  • repeats prior conclusions
  • exhibits stable confidence
  • resists reconfiguration

Evaluation has stopped updating.


10. Boundary Conditions

This article does not:

  • label evaluation as biased
  • propose reopening strategies
  • assign intent
  • introduce emotional constructs

It isolates a control phenomenon.


11. Closing Statement

Evaluation without update is not failure of attention. It is stabilization of regulation.

When evaluation stops updating, cognition remains active while change becomes impossible.

Understanding this distinction is essential for diagnosing persistent cognitive rigidity.