terminalSystem Active // V1.0 PROTOTYPE

QDD_METRICS

Qualitative Directional Disclosure

Measuring disclosure utility, prediction vectors, and intelligence credibility.Document status: Draft for community reviewPre-release Beta

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Qualitative Directional Disclosure

QDD — Qualitative Directional Disclosure — is a structured evaluation framework that measures whether a disclosure claim, prediction, or public statement moves the needle toward verifiable truth or merely occupies narrative space. The framework assigns directional vectors to information quality, distinguishing signal from noise across disclosure events and predictive claims.

Purpose

To evaluate whether a media claim, disclosure, or public statement materially advances understanding or merely occupies narrative space. To track prediction accuracy and evidence accumulation over time through structured scoring vectors.

Anti-Goal

To reject performative claims, narrative laundering, and confirmatory repetition that lacks verification vectors.

Core Interrogation

"Does this claim move us closer to verifiable truth, accountability, or material insight — or does it stall, redirect, monetize, or mythologize?"

The Three Pillars of QDD

Qualitative

Assessing the substance and specificity of claims — not volume or repetition. Information quality over quantity.

Directional

Measuring whether information advances understanding (positive vector) or adds noise, misdirection, or stagnation (negative vector).

Disclosure

Evaluating claims against verification criteria — source credibility, falsifiability, corroboration, and material consequence.

Methodology

QDD applies disclosure evaluation principles to assess information quality in media claims, predictive statements, and intelligence credibility. The framework measures directional value — whether a claim advances understanding or adds noise.

  • High QDD: Specific, verifiable, actionable claims with clear causal reasoning and evidence accumulation.
  • Low QDD: Vague assertions, unfalsifiable disclosures, or recycled narratives without new information.
  • The scoring system tracks contributor credibility and prediction accuracy over time, structurally modeled on intelligence credibility scoring systems.
  • Prediction Registry: Registers claims with event horizons, tracks corroborating and contradicting evidence, and computes confidence vectors as new information surfaces.

QUALITATIVE DIRECTIONAL DISCLOSURE // EVALUATION FRAMEWORK // PROTOTYPE V1.0