Anti-Learning Regimes
Diagnosing when institutions optimise against evidence—and measuring the structural forces that prevent genuine update.
The 60-Second Version
Why do institutions accumulate evidence while repeating failure?
Anti-learning isn't just failing to learn—it's a structural configuration where the institution actively resists evidence that challenges its current operation. Learning-like activity happens (training, reports, feedback) but the institution becomes progressively more rigid rather than more adaptive.
This paper provides diagnostic metrics for identifying anti-learning regimes: Update Suppression Rates, Feedback Penalty Gradients, Model Rigidity Indices, and Authority-Evidence Coupling measures.
The goal isn't to blame individuals—it's to diagnose structural conditions where learning is safe but ineffective.
The Core Insight
Anti-Learning Regime
Structural configuration where:
- Evidence is abundant but change is absent
- Feedback is costly to deliver
- Models are defended rather than tested
- Authority trumps evidence systematically
Learning Architecture
Structural configuration where:
- Evidence triggers genuine update
- Uncomfortable truths are protected
- Models are updated, not defended
- Evidence has structural authority
Four Types of Anti-Learning Regimes
Anti-learning takes different forms depending on the dominant structural force:
Confirmation Regime
Information is filtered to support existing conclusions. Contradictory evidence is dismissed as noise or bias.
Symptom: Decision-makers only hear what confirms their view
Bureaucratic Regime
Learning is processed through procedures that neutralise its force. Evidence becomes paperwork.
Symptom: Lessons learned exercises produce reports that change nothing
Political Regime
Learning is blocked because it threatens power arrangements. Truth-telling is punished.
Symptom: Honest assessment is career-limiting
Sclerotic Regime
The institution has learned so well in the past that it can no longer update. Success breeds rigidity.
Symptom: Past success used as evidence that change isn't needed
These regimes often combine and reinforce. A bureaucratic regime may protect a political regime. A confirmation regime may develop into a sclerotic one. Diagnosis requires identifying the dominant pattern.
Where This Applies
Regulatory Bodies
Agencies that accumulate failure reports but never change approach. Classic confirmation regimes.
Universities
Institutions with high legitimacy investments that make evidence "dangerous" when it challenges foundational narratives.
Healthcare Systems
Organisations where bureaucratic regimes neutralise clinical learning through paperwork and compliance.
Corporations
Companies where political regimes make honest assessment career-limiting and confirmation regimes filter information to leadership.
Part of the ILA Series
This paper provides the diagnostic layer for Institutional Learning Architecture. It answers: how do we know if an institution is in anti-learning mode?
Common Questions
How is an anti-learning regime different from just failing to learn?
Failure to learn is passive—the institution simply doesn't update. An anti-learning regime is active—the institution has structural mechanisms that resist update. The more evidence arrives, the more rigid the response.
Can an institution be in multiple anti-learning regimes?
Yes. Regimes often combine. A confirmation regime may be protected by a political regime (truth-telling is punished). A bureaucratic regime may mask a sclerotic one (past success justified by process compliance).
What's the point of diagnosing if change is so hard?
Diagnosis enables targeted intervention. A confirmation regime requires different architecture than a political regime. Generic "culture change" fails because it doesn't address the specific structural forces blocking update.
Read the Paper
Explore the full diagnostic framework for identifying anti-learning regimes.
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