📖 Media Substrate Glossary

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.