Systems Theory (Structural Coherence)

Definition

Systems Theory (Structural Coherence) is the foundational science that studies how structures, processes, and relationships produce stable, reliable, and coherent behavior across a system. It examines how components interact, how constraints shape patterns, and how internal architecture determines what a system can and cannot do.

In Meaning System Science, Systems Theory provides the scientific basis for understanding Structural Coherence (C)— how meaning moves through the architecture of roles, decisions, workflows, accountability structures, and communication pathways.

Structural Coherence is not about culture or interpersonal dynamics. It is about the design of the system itself.

Intellectual Lineage

Systems Theory draws on a broad, interdisciplinary lineage from engineering, biology, cybernetics, sociology, and information science. Meaning System Science inherits directly from:

• Ludwig von Bertalanffy – General Systems Theory

• Norbert Wiener – Cybernetics and feedback systems

• Jay Forrester – System dynamics and organizational modeling

• Stafford Beer – Management cybernetics

• Niklas Luhmann – Social systems theory

• Herbert Simon – Bounded rationality and system architecture

• Ross Ashby – Homeostasis, regulation, requisite variety

These thinkers established the principle that structure determines behavior, the core insight that Meaning System Science extends to meaning behavior.

Structural Coherence in Meaning System Science

Structural Coherence (C) is one of the five foundational forces that shape the behavior of meaning systems, and one of the three numerators in the Legitimacy Equation.

In MSS, structural coherence measures:

• how well the system conducts meaning

• whether roles and responsibilities are clearly designed

• whether decision pathways are consistent and transparent

• the stability of workflows and information flow

• whether authority and structure are proportionally aligned

• how well the system handles complexity and pressure

When coherence is high, meaning moves cleanly.
When coherence is low, drift accelerates.

Systems Theory vs. Structural Coherence

Systems Theory is the foundational science that explains:

• how structure creates behavior

• how constraints shape patterns

• how architecture determines meaning flow

Structural Coherence is the structural variable derived from that science.

Systems Theory is the discipline.
Structural Coherence is the measurable force within Meaning System Science.

Role in the Legitimacy Equation (C)

Systems Theory provides the conceptual framework for:

C = Coherence Coefficient
in
L = (T × P × C) ÷ D

Where structural coherence determines whether truth and signals can be sustained through the system without distortion.

When structure is misaligned, even perfect truth (T) and strong power alignment (P) fail to create legitimacy.

Coherence is the stabilizing force.

Relationship to Other Foundational Sciences

Semantics (Truth Fidelity):

High truth fidelity is meaningless if the structure cannot transmit it.

Semeiology (Signal Behavior):

Signal behavior must move through structure; weak structure distorts signals.

Thermodynamics of Meaning:

Meaning entropy increases when structural coherence breaks down.

Affective Science:

Emotional stability depends heavily on structural predictability.

Systems Theory in Organizational Life

Systems Theory explains why:

• unclear roles create drift

• poor decision pathways create confusion

• overloaded structures increase meaning entropy

• missing boundaries lead to chaos

• contradictory structures produce contradictory behavior

• teams build shadow systems when structure is unclear

• organizations fail not from effort, but from design

High-structure systems experience:

• clarity

• predictability

• continuity

• stable meaning

Low-structure systems experience:

• drift

• burnout

• misalignment

• political distortion

• meaning collapse

Structural coherence is a first-order condition for organizational health.

Applications in Transformation Science and Management

Systems Theory is used to:

• evaluate structural clarity

• assess decision architecture

• detect bottlenecks, contradictions, and structural overload

• design roles, workflows, and governance

• model how meaning moves through the system

• identify where coherence is lost

• anchor stable transformation practices