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NV-3 — MindOS Failure: Choice Overload at Operator Layer (Cognitive Drift → Output Collapse) (Almost-Code Canonical) v1.0

Too much choice inside execution destroys phase stability.

Summary (Canonical)

MindOS fails (especially under deadlines) when boundary-level choice/symmetry breaking leaks into interior execution.
Operators require symmetry to execute quickly and reliably.
When choice overload exceeds the symmetry budget ((\rho \ge 1)), phase shear accumulates and output collapses (P2→P1→P0 moments).
This is a computable failure mode, not “lack of motivation.”

1) The Root Error (Negative Void)

The absent function

Missing: interior protection + truncation of choices.

A stable MindOS needs:

  • a protected interior routine (SOP corridors)
  • a sandbox for exploration (Architect)
  • Oracle gates (checklists, scope locks)
  • fast truncation when overload spikes

Without these, everything becomes “decide again,” and cognition destabilises.

2) CivOS Mechanism (Symmetry Budget at Z0)

Define:

  • (S_{inj}) = symmetry breaks injected (choices, options, forks)
  • (S_{cap}) = absorption capacity (bind strength + routines + tempo slack)
  • (\rho=S_{inj}/S_{cap})

When:
[
\rho \ge 1
]
the learner/person enters a failure regime:

  • working memory overload
  • contradictions increase
  • scope slips
  • time-to-repair exceeds stress cycle length

Output collapses.

3) Observable Pattern (What you see)

Z0 (student / individual)

  • “I don’t know where to start”
  • jumping between plans
  • rewriting the first sentence repeatedly
  • forgetting words they “know”
  • panic errors under time

Z1 (family)

  • inconsistent routines
  • too many enrichment streams
  • changing rules weekly
  • argument loops (semantic noise)

Z2 (school/class)

  • constant rubric shifts
  • too many “creative options” with no constraints
  • weak checklists, no stable frames
  • high variance outcomes

These are all symmetry overload manifestations.

4) The Collapse Corridor (MindOS)

  1. More options introduced (ΔS events)
  2. Interior routine weak or absent
  3. (\rho) approaches 1 (shear accumulating)
  4. Under time pressure, (\rho) spikes above 1
  5. Attention scatters; judgement gates fail
  6. Output collapses (P0 moment)
  7. Confidence drops; avoidance increases
  8. Long-term drift (P1 becomes baseline)

5) Hidden Fragility (Why “smart students” collapse)

High node count (vocabulary) can hide weak binds:

  • they have many words
  • but no stable corridor frames
  • so every task is “invent from scratch”
  • which injects massive choice into execution

This is Architect work forced into Operator time.

It collapses under load.

6) Failure Mode Trace (Required)

Weak interior SOP + high choice injection → (\rho\ge 1) spike under time → phase shear → attention scatters → scope drifts → output collapse (P0 moment) → avoidance loop → baseline P1 drift.

7) Safety Conditions (What must exist to prevent NV-3)

MindOS must enforce:

  1. Interior SOP corridors (stable frames, routines)
  2. Choice truncation triggers (freeze options when overload)
  3. Oracle gates (checklists, scope locks, definitions)
  4. Sandbox boundary exploration (Architect time separate from execution time)
  5. Load training (practice stability under time)

Almost-Code Spec Block (Copyable)

NegativeVoid.NV3.MindOSChoiceOverload.v1.0

Negative Void:
  Choice overload injected into Operator execution (interior lanes)
  Missing functions: interior SOP protection + choice truncation + Oracle gating
Model:
  S_inj(t) := Σ ΔS_i (choices/forks)
  S_cap(Z0,t) := f(bind strength, routines, tempo slack)
  ρ(t) := S_inj(t) / S_cap(Z0,t)
Failure Condition:
  if ρ(t) >= 1 => phase shear accumulates => output collapse under load
Observable Signs:
  indecision loops, restart behaviour, panic errors, scope drift, high variance results
Failure Mode Trace:
  weak SOP + high ΔS -> ρ spike -> attention scatter -> judgement fails ->
  output collapse (P0 moment) -> avoidance -> baseline P1 drift

FAQ (Short)

Q1: Isn’t “more choices” better learning?
Not inside execution lanes under time pressure. Choices must be sandboxed and gated.

Q2: What’s the fastest fix in exams?
Truncate choices: use a single frame/checklist, execute, then refine after.

Q3: How does this propagate to civilisation?
At scale, choice overload in Operator layers increases coordination cost, slows repair, and reduces regeneration throughput—raising collapse risk.

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