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🔄 Transition Detection

Transitions are triggered by invariant breaks, drift acceleration, attention spikes, narrative collapse, cadence overload, or reconstruction forces. They are the Analyzer’s highest‑level signal of systemic change.

🧭 What Counts as a Transition#

A transition occurs when the system crosses a boundary in either:

  • Basin (e.g., Network → Fragment)
  • Mode (e.g., Tension → Drift)
  • Both simultaneously (e.g., Network/Drift → Cascade/Cascade)

Transitions are not subtle fluctuations. They represent structural reconfiguration.

🧩 Inputs to Transition Detection#

The Analyzer uses several signals to detect transitions:

  • Previous basin vs current basin
  • Previous mode vs current mode
  • Drift magnitude and direction
  • Invariant strain patterns
  • Attention volatility
  • Cadence acceleration or compression
  • Narrative stability or collapse

Transitions are detected only when these signals cross structural thresholds.

⚡ Transition Triggers#

The MSM defines six primary trigger types:

Invariant Break#

One or more invariants exceed their strain threshold.
Examples:

  • Signal–Narrative Coherence breaks → narrative collapse
  • Distribution–Attention Fit breaks → cascade onset

Attention Spike#

Sudden, extreme increase in A.
Often leads to:

  • Cascade
  • Narrative churn
  • Distribution overload

Cadence Acceleration#

Temporal cadence increases faster than the system can stabilize.
Common in:

  • High‑velocity media cycles
  • Crisis events
  • Viral cascades

Signal Collapse#

Sharp drop in S.
Leads to:

  • Narrative simplification
  • Epistemic decay
  • Collapse mode

Narrative Collapse#

N drops rapidly due to conflict, fragmentation, or overload.
Often paired with:

  • High A volatility
  • High T
  • Drift acceleration

Reconstruction#

Deliberate stabilization effort.
Characterized by:

  • Rising S
  • Rising N
  • Slowing T
  • Decreasing drift

Reconstruction is the only positive‑direction trigger.

🌀 Basin Transitions#

Basin transitions occur when the system’s structural fingerprint moves closer to a new attractor and satisfies its gate conditions.

Examples:

  • Network → Fragment
    Narrative divergence + distribution fragmentation

  • Fragment → Cascade
    Attention spike + cadence acceleration

  • Cascade → Collapse
    Overload + signal failure

  • Collapse → Reconstruction
    Stabilization + rising coherence

Basin transitions are the most visible form of systemic change.

🎛 Mode Transitions#

Mode transitions reflect changes in behavior, not location.

Examples:

  • Stable → Tension
    Early invariant strain

  • Tension → Drift
    Directional movement begins

  • Drift → Cascade
    Volatility exceeds structural capacity

  • Cascade → Collapse
    System overload

  • Collapse → Reconstruction
    Stabilization begins

Mode transitions often precede basin transitions.

🧬 Combined Transitions#

Some transitions involve both basin and mode changes simultaneously.

Example:

Network / Drift  →  Cascade / Cascade

This indicates:

  • A basin shift into the Cascade attractor
  • A behavioral shift into Cascade mode
  • A high‑severity structural event

Combined transitions are rare but high‑impact.

📦 Output: MediaTransition#

The Analyzer returns:

{
  from: string,
  to: string,
  trigger: string,
  severity: number
}
  • from — previous basin/mode
  • to — current basin/mode
  • trigger — the dominant structural cause
  • severity — magnitude of the transition (0.0–1.0)

Severity is influenced by drift magnitude, invariant breaks, and volatility.

🧠 Why Transitions Matter#

Transitions reveal:

  • When a system becomes unstable
  • When cascades are forming
  • When collapse is imminent
  • When reconstruction is underway
  • How media ecosystems evolve over time

They are essential for monitoring, forecasting, and simulation.

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