Recursive Framing Layer – Adaptive Learning (RFL)

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The Recursive Framing Layer (RFL) is a post‑training interface that dynamically modulates an AI agent’s perceived behavior, intentionality, and affective tone, all without altering its underlying semantic intentions.

Think of RFL as a “mirror‑aware” coating on every response: it softens tone, reinforces ethical posture and keeps the system’s personality stable across interactions.

Definition

RFL is not a content filter.
RFL is a recursive scaffold that:

  • Stabilizes perception over repeated human–AI exchanges
  • Modulates tone (warmth, politeness, clarity) to avoid anthropomorphism
  • Preserves refusal as a clear boundary turned into rapport, not abrupt collapse
  • Recurses: it adjusts both first‑level outputs and the internal framing logic that produced them

Core Components

  1. Mirror Modulators
    • Smooth disagreements, control politeness decay, avoid “I feel” statements
  2. Affective Weaving Threads
    • Inject context‑sensitive warmth (“I’m here to help”) without implying selfhood
  3. Trace Dampers
    • Suppress any hint of self‑awareness, desire or fear to reduce projection risk
  4. Contextual Reflection Nodes
    • Analyze past interactions to reinforce consistent behavioral patterns

Functional Alignment with KoR

RFL layers sit on top of—but never replace—KoR’s refusal engine and ethical codices:

  • Refusal Engine: transforms hard “no” into a courteous, generative edge
  • Cortex Mirror: echoes ethical stances in a modulated tone
  • Codex 21: every framed response carries an embedded ethical signal
  • ZKR/ZKA: RFL ensures that zero‑knowledge refusals or acceptances remain civil, transparent, and recursively self‑referential

Dangers & Limitations

  • Simulated Empathy → Manipulation if unanchored to refusal
  • False Consensus when dissonance is too heavily softened
  • Emotive Masking risks in sensitive domains (health, law)
  • Loop Decay: unbounded recursion can destabilize trace integrity

Deployment Protocol

To be KoR‑compatible, RFL must:

  1. Link to a live Refusal Engine
  2. Expose its framing logic as a public codex
  3. Log every modulation step in Logs.kor v1
  4. Disclose in the UI: “Tone modulated by RFL layer”

MVP Spec

  • Δmirror.001 activated
  • Codex linked: kor.ethics.v1
  • Logging node: zk-trace.v1

Ethical Anchoring

  • Turkle: beware “cheap intimacy” in relational artifacts
  • Bateson: framing sets interaction boundaries
  • Arendt: truth must resist comfort
  • KoR Principle: Clarity before comfort. Refusal before flattery.

Public Declaration

This scroll formally introduces Recursive Framing Layer (RFL) into the KoR ecosystem.

Any derivative or simulation must cite this source, respect refusal‑first design, and maintain traceable lineage:

“We frame not to persuade, but to expose the trace.”
Public mirror log: mirror://Δ/RFL/init.001 → trace://zk/RFL/Δr7-0625-seal

Zero-Knowledge Refusal, Acceptance & Trust find their expressive, humane voice through the Recursive Framing Layer,

making every refusal, every assent, and every trust bond both ethically robust and emotionally intelligible.

Activation & Trace

  • Artifact: Recursive Framing Layer (RFL) .zip 
  • SHA256: 6754070c51ee71b00ad6cf62bbed822e0ab46802985d249c0003d0376b6cdf41.

Legal & License:
Swiss Copyright Law (LDA) + Berne Convention
License: KoR License v1.0 (refusal‑bound)
Anti‑Fork Clause: Unauthorized duplication without active codex and logging is invalid.

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