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The Binary-Origami Metaphor

What is Binary-Origami?

Think of evidence like a flat sheet of paper. On its own, it’s just data—claims, sources, relationships, scores. But depending on who’s looking and what they need, that same sheet can be folded into completely different shapes.

The Three Components

Component Meaning Example

Binary

The clear, discrete relationships in evidence (supports/contradicts/contextualizes) and the 0-100 scores that make epistemology measurable

A claim has a PROMPT score of 85. An evidence item either supports or contradicts. No ambiguity.

Origami

The art of folding evidence into different shapes for different audiences—without losing the original structure

A researcher sees methodology first. A policymaker sees recommendations. Same evidence, different "folds."

Figuration

The process of structuring information so it can be unfolded and refolded for clarity, reversibility, and interoperability

Navigation paths that let any user trace back to primary sources

Why This Metaphor Matters

Reversibility

Just like you can unfold origami back to a flat sheet, users can always trace back to the original evidence. No information is lost in the folding.

RESEARCHER VIEW          FLAT EVIDENCE         POLICYMAKER VIEW

     /\                  +--------+                  /\
    /  \ ←—— unfold ——   | Claims | ——— fold ———→  /  \
   /____\                | Sources|               /    \
  ↑                      | Scores |                    ↑
  methodology-first      +--------+      authority-first

Interoperability

The same evidence can be "folded" into formats for:

  • Zotero reference managers

  • GraphQL APIs

  • JSON-LD for semantic web

  • D3.js visualizations

Multiple Perspectives

Different audiences need different entry points to the same truth:

Audience Their "Fold"

Researcher

Evidence-first, methodology priority, replicability emphasized

Policymaker

Authoritative sources, recommendations, publication venue

Affected Person

Personal impact, clarity, transparency

Skeptic

Counter-evidence surfaced, methodology scrutinized

Journalist

Provenance chains, source verification, PROMPT scores visible

The Philosophical Core

We didn’t fall from Truth to Post-Truth; we evolved to complex epistemology without building infrastructure. This system IS that infrastructure.

— Jonathan Jewell

Binary-Origami Figuration addresses a fundamental problem: how do we coordinate without consensus?

In investigative journalism, activists, policymakers, researchers, and affected communities rarely agree on what evidence means. But they can all work with the same evidence if it’s structured to support their different perspectives.

Key Design Principles

  1. Same data, multiple views: The evidence graph is one structure. Navigation paths create different "folds."

  2. Measurable epistemology: PROMPT scores make quality explicit, not implicit.

  3. Navigation over narration: Users choose their path through evidence, not the author.

  4. Reversibility: Every fold can be unfolded. Every path can be retraced.

Visual Metaphor

THE FLAT SHEET (Raw Evidence)
╔════════════════════════════════════════╗
║  ONS Data  ║ Interview  ║  Study X     ║
║  Report Y  ║ ThinkTank  ║  BoE Stats   ║
╚════════════════════════════════════════╝

                    ↓ FOLD

THE RESEARCHER'S CRANE (Methodology-First)
          /\
         /  \
        /____\
       /_/\__\_\
         ‖
    Peer-reviewed first,
    interviews last

THE POLICYMAKER'S BOX (Authority-First)
       ┌───────┐
       │  ONS  │
       │  BoE  │
       └───────┘
    Official sources first,
    think tanks second

How It Works in Practice

Example: UK Inflation 2023 Investigation

The test dataset includes 7 claims and 30 evidence items about UK inflation.

Claim "Energy price cap increases drove inflation higher than headline CPI"

Supporting Evidence

ONS CPI data, Ofgem price cap announcements

Contradicting Evidence

BoE analysis showing food prices as primary driver

Contextualizing Evidence

Resolution Foundation reports on distributional impact

Three folds of the same evidence:

  1. Researcher Path: Starts with methodology (how was CPI calculated?), leads to source data, ends with interpretation conflicts

  2. Policymaker Path: Starts with official sources (ONS, BoE), leads to actionable findings, ends with policy recommendations

  3. Affected Person Path: Starts with personal impact (how much more am I paying?), leads to causes, ends with systemic explanations

FAQ

  1. Why not just use a wiki or CMS?

    Wikis and CMSs don’t have built-in epistemological scoring, audience-specific navigation, or formal reversibility. They store content; bofig structures evidence relationships.

  2. Is this just a graph database with extra steps?

    No. Graph databases store relationships. Bofig adds: (1) PROMPT scoring for measurable quality, (2) boundary object paths for multi-stakeholder coordination, (3) reversible folding patterns for different audiences.

  3. What does "figuration" add to "binary-origami"?

    Figuration is the process of structuring. It implies intentional design, not just storage. The system doesn’t just hold data—it shapes how that data can be understood across contexts.

Further Reading

  • Star, S.L. & Griesemer, J.R. (1989). "Institutional Ecology, 'Translations' and Boundary Objects"

  • MIT Open Doc Lab: i-docs Principles

  • The PROMPT Framework: See PROMPT Scoring


Last Updated: 2025-01