📖 Media Substrate Glossary

This glossary defines the core vocabulary of the Media Substrate Model (MSM). These terms describe the structural physics of media ecosystems—how signal, distribution, attention, narrative, and cadence interact to produce stability, drift, cascades, fragmentation, and reconstruction.

Each term is defined substrate‑first, independent of any specific platform, ideology, or content domain.

🛰 Signal Integrity (S)#

The fidelity and reliability of information as it moves through the ecosystem. High S supports coherent narratives; low S accelerates noise, distortion, and epistemic decay.

🌐 Distribution Topology (D)#

The structural shape of information flow. Includes centralization, federation, networked flow, fragmentation, and chaotic topology. Determines amplification, reach, and drift pathways.

⚡ Attention Dynamics (A)#

The energy of the media ecosystem. Includes volatility, pooling, spikes, cascades, decay, and burnout. High A drives cascades; low A leads to stagnation.

🧩 Narrative Coherence (N)#

The stability and interpretability of meaning across the ecosystem. Includes alignment, plurality, conflict, drift, and collapse. Low N characterizes Fragment and Cascade basins.

⏱ Temporal Cadence (T)#

The speed and decay pressure of the media environment. Includes update frequency, acceleration, compression, refresh pressure, and persistence. High T overwhelms verification and narrative stability.

🧭 Invariants#

Structural relationships between axes that must hold for the system to remain coherent. MSM defines four core invariants:

• Signal–Narrative Coherence
• Distribution–Attention Fit
• Temporal–Signal Stability
• Attention–Narrative Feedback

Breaks in invariants trigger drift, cascades, or collapse.

🌀 Basins#

Stable or semi‑stable attractor regions in the media substrate. MSM defines six basins:

• Broadcast
• Network
• Fragment
• Cascade
• Stagnation
• Reconstruction

Each basin has a canonical vector and gate conditions.

🔧 Modes#

Behavioral states describing how a system behaves inside a basin:

• Stable
• Tension
• Drift
• Cascade
• Collapse
• Reconstruction

Modes reflect invariant strain and drift magnitude.

🧬 Drift#

Directional movement across the substrate caused by invariant strain. Drift can be:

• Micro
• Meso
• Macro
• Regime shift

Magnitude and direction determine transitions.

🔄 Transition#

A shift from one basin to another triggered by invariant breaks, attention surges, cadence acceleration, signal collapse, narrative collapse, or reconstruction efforts.

📡 Media Signals#

Raw inputs that adapters convert into substrate vectors. Categories include:

• Signal integrity signals
• Distribution topology signals
• Attention dynamics signals
• Narrative coherence signals
• Temporal cadence signals

These signals form the basis of MSM analysis.

🔌 Adapter#

A module that converts raw external data (text, metrics, graphs, narratives) into MSM primitives such as MediaVector, invariant states, and drift signatures.

🧱 Canonical Vector#

The representative vector for a basin. Used as the attractor center for classification and drift detection.

🚧 Gate Conditions#

Thresholds that must be satisfied for a system to be classified into a basin, even if the canonical vector is nearby. Prevents misclassification.

🧠 Narrative Drift#

Gradual semantic shift caused by cadence pressure, signal degradation, or attention volatility. A precursor to fragmentation or cascade.

⚙️ Cadence Pressure#

Strain caused by increasing update speed. High cadence pressure reduces verification capacity and accelerates narrative decay.

🔥 Cascade#

A high‑energy, high‑speed reconfiguration event driven by attention spikes and accelerated cadence. Characteristic of the Cascade Basin and Cascade Mode.

🧊 Stagnation#

A low‑energy state characterized by weak narratives, low attention, and slow cadence. Often follows collapse or burnout.

🛠 Reconstruction#

A deliberate process of restoring signal integrity, narrative coherence, and distribution structure after collapse or cascade.