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Module: Attack the Rows

By SAUFEX Consortium 25 January 2026

Purpose: Stop subsidising spillovers. Design rows that make dumping costs money.

Output format: Assessment → Confidence (low/med/high) → Next action


[screen 1]

The Four-Layer Pattern

Every disinformation ecosystem follows this structure:

  1. Private trade: Direct transaction between parties
  2. Spillover bundle: Costs dumped on third parties
  3. Avoidance economy: Others paying to avoid the harms
  4. Missing internalisation row: No mechanism to charge spillover back

Understanding this pattern reveals where intervention is possible.


[screen 2]

Avoidance Economy Proves the Harm

If people pay money to avoid something, it’s not hypothetical harm.

Examples of avoidance spending:

  • Moderation teams (platforms and brands)
  • Security consultants (individuals and organizations)
  • PR crisis management (companies and politicians)
  • Mental health treatment (users and employees)
  • Fact-checking organizations (society)
  • Policy and regulatory staff (governments)

This spending exists because harms are real. It’s just allocated to the wrong people.


[screen 3]

Don’t Moralise. Reprice.

“People should know better” is not a strategy. “Platforms should be responsible” is a hope, not a mechanism.

Markets react to:

  • Costs (things that reduce profit)
  • Friction (things that slow activity)
  • Liability (things that create legal risk)

Moral arguments have their place. But behavior changes when incentives change.


[screen 4]

Industrial Reach Is the Lever

Critical distinction: Don’t tax speech. Target industrial distribution.

What you can target:

  • Recommendation systems (algorithmic boost)
  • Monetised scale (revenue from reach)
  • Boosted distribution (paid amplification)
  • Platform infrastructure (hosting, CDN, payment processing)

What you don’t target:

  • Individual expression
  • Small-scale organic sharing
  • Opinion and political speech

Industrial reach is regulable. Speaking isn’t.


[screen 5]

Mechanism Palette

Tools available for internalisation:

Permits: License to operate at scale (like broadcasting) Deposits: Funds held against potential harm (like environmental bonds) Audits: Mandatory transparency about operations Levies: Fees proportional to externality risk Monetisation licensing: Rules about who can earn from reach Reach escrow: Delay distribution pending review Advertiser duty constraints: Requirements on who places ads

These aren’t fantasy. Versions exist for other industries. Information is catching up.


[screen 6]

Design Constraints

Effective mechanisms must be:

Reversible: Can be adjusted as we learn Auditable: Verifiable compliance Proportional: Match intervention to harm Not ideology-dependent: Apply regardless of content viewpoint

Fail any of these, and you’ve built a censorship machine, not an accountability framework.


[screen 7]

Solved Ledger (Definition)

What does “success” look like?

Not: “No more lies on the internet” Not: “Everyone believes truth”

Yes: A ledger where externalities aren’t free to dump.

In a solved ledger:

  • Private trades still happen
  • But spillovers are priced
  • Those who benefit also pay costs
  • Avoidance economy shrinks

Perfect truth isn’t the goal. Functional market is.


[screen 8]

Metrics for a Solved Ledger

Leading indicators (early signals):

  • Reach share of problematic content (is it decreasing?)
  • Monetisation access for violating content (is it harder to profit?)
  • Friction events (are speed bumps working?)
  • Internalisation mechanism adoption (are new costs being applied?)

Lagging indicators (ultimate outcomes):

  • Incidents requiring response (frequency and severity)
  • Harassment volume (measurable harms)
  • Trust indicators (survey data)
  • Enforcement costs (is the avoidance economy shrinking?)

Measure both. Leading indicators tell you if interventions are working; lagging indicators tell you if it matters.


[screen 9]

Case Study: Platform Advertising

Current ledger:

WhoGivesGetsHow
AdvertiserMoneyImpressionsProgrammatic placement
PlatformAd inventoryRevenueAuction system
CreatorContentShare of ad revenueViews/engagement
UserAttentionContent access”Free” service

Spillover: Ads appear next to harmful content. Brand doesn’t know. User is harmed. Platform keeps money.

Internalisation option: Advertiser liability for content adjacency. Platform audit requirement. Creator demonetisation for violations.


[screen 10]

Case Study: Influence-for-Hire

Current ledger:

WhoGivesGetsHow
ClientMoneyCampaign effectsContract
Influence firmLabor, accountsPaymentService delivery
PlatformReach infrastructureEngagementAllowing operation
Target audienceAttention, trustManipulationUnknowing participation

Spillover: Democratic discourse degraded. Trust eroded. No party pays the cost.

Internalisation options:

  • Influence firm registration requirements
  • Platform detection and reporting obligations
  • Client disclosure requirements
  • Financial tracking of campaign funding

[screen 11]

DIM Integration

This is the economics under the whole DIM menu:

Gen 2 (Debunk): Works when spillover is belief-based and correctable Gen 3 (Prebunk): Works when you can reduce demand before exposure Gen 4 (Moderate): Becomes rational when reach has costs attached Gen 5 (Interact): Becomes structural when community resilience is valued

Economic framing makes each generation more effective because it addresses root causes, not just symptoms.


[screen 12]

Practical Exercise: Capstone

Pick ONE actor (platform OR influencer OR troll farm) and deliver a complete analysis:

Deliverables (45 minutes):

  1. 10-row TTF (Transaction Framing Tool)

    • Include all major parties
    • Specify Who/Gives/Gets/How for each
  2. Four-layer map

    • Private trade
    • Spillover bundle
    • Avoidance economy
    • Missing internalisation
  3. 3 internalisation rows with mechanisms

    • What row would you add?
    • What mechanism implements it?
    • How does it change incentives?
  4. 5 metrics

    • 3 leading indicators
    • 2 lagging indicators
  5. Assessment + Confidence + Next action


[screen 13]

Sample Framework: Platform Analysis

Four-layer map:

  1. Private trade: User attention for content access; advertiser money for impressions
  2. Spillover bundle: Moderation costs, mental health harms, democratic erosion
  3. Avoidance economy: Trust & safety teams, fact-checkers, crisis PR, regulatory lobbying
  4. Missing internalisation: No cost to platform for externalities until regulation

3 internalisation rows:

MechanismRow AddedEffect
Harm levyPlatform pays % of ad revenue to offset social costsRaises cost of harmful engagement
Audit requirementPlatform publishes algorithmic transparency reportsCreates accountability pressure
Advertiser liabilityBrands liable for content adjacency harmsShifts due diligence upstream

Metrics:

  • Leading: Harmful content reach share, demonetisation rate, friction event frequency
  • Lagging: Trust survey scores, harassment complaints, regulatory enforcement actions

[screen 14]

Common Objections (and Responses)

“This is censorship” Response: Industrial distribution regulation isn’t speech restriction. You can say it; you can’t demand algorithmic amplification.

“It will hurt innovation” Response: Externality pricing is how markets work. Polluters said the same thing about environmental regulation.

“It’s too complicated” Response: Current system is already complicated. Question is who bears the cost of that complexity.

“Platforms will leave” Response: Collective action across jurisdictions. Markets this large are hard to abandon.


[screen 15]

The Political Reality

Internalisation mechanisms face political opposition:

  • Platform lobbying (protect business model)
  • Free speech absolutism (principle, often exploited)
  • Regulatory capture (industry influence on rules)
  • Ideological polarization (each side fears being censored)

These are real obstacles. But the alternative — permanent spillover dumping — is also politically untenable long-term.

Progress is possible. It’s not easy.


[screen 16]

Building Toward Solved Ledgers

Practical steps:

Document: Make spillovers visible and measurable Quantify: Put numbers on avoidance economy spending Propose: Specific internalisation mechanisms with design constraints Pilot: Test mechanisms in limited contexts Evaluate: Measure against both leading and lagging indicators Iterate: Adjust based on evidence

This is a long-term project. But every step toward pricing externalities makes the next step easier.


[screen 17]

Module Assessment

Scenario: You’re advising a government on platform accountability legislation. The goal is to reduce the harms of disinformation without chilling legitimate speech.

Task (20 minutes):

  1. Identify 3 key spillovers you want to address
  2. Propose 2 internalisation mechanisms with design constraints met
  3. What metrics would you use to evaluate success?
  4. What opposition would you anticipate and how would you address it?
  5. What would you explicitly NOT include in the legislation?
  6. Assessment + Confidence + Next action

Scoring:

  • Credit mechanisms over moralising
  • Reward design constraint awareness
  • Penalize overreach that fails legitimacy test
  • Credit anticipation of opposition

[screen 18]

Key Takeaways

  • Four-layer pattern: private trade → spillover → avoidance economy → missing internalisation
  • Avoidance spending proves harm is real; question is who should pay
  • Don’t moralise, reprice: markets respond to costs, friction, liability
  • Target industrial reach, not speech: recommendation, monetisation, scale
  • Mechanism palette: permits, deposits, audits, levies, escrow
  • Design constraints: reversible, auditable, proportional, ideology-independent
  • Solved ledger: not “no lies” but “externalities aren’t free to dump”
  • Metrics: leading (reach, monetisation, friction) and lagging (incidents, trust, enforcement)
  • This is the economics under the whole DIM menu

Attack the rows. Change the market.


Disinfonomics Path Complete

You’ve completed the Disinfonomics learning path. You now understand:

  • How to frame disinformation as market transactions
  • How to use TTF to map any ecosystem
  • How platforms function as auction systems
  • The difference between influencer and troll farm business models
  • The counter-economy and amplification traps
  • Cross-border coordination challenges
  • How to design internalisation mechanisms

Apply these frameworks to real cases. The analysis muscle builds with use.


Global Grading Penalties (For Self-Assessment)

When reviewing your work, penalize yourself:

  • -2: “People are gullible / educate harder” as main explanation
  • -2: Attribution claims without strong evidence
  • -1: Magical thinking (“this will solve it”)
  • -1: Missing mechanism (what enables the behavior?)
  • -1: Vague Gets/Gives in TTF

If you’re not losing points, you’re not being honest with yourself.