CHAPTER 13 STUDIO
Governance, AI, and fractals braided through three working labs.
Institutional theory predicts pressure dynamics that operate at multiple scales. Network science gives us multi-scale graph descriptors. AI is the new pressure environment that intensifies all three classical isomorphic mechanisms. This page connects the three. Sketch a pressure field across five scales and see the dominant mechanism shift. Toggle a decoupling scenario and watch formal and operational drift apart. Edit a regulation cascade and see translation drift compound from regulator to practitioner.
LAB 1: MULTI-SCALE PRESSURE FIELD
Sketch a pressure field. Watch the dominant mechanism shift across scales.
The radar on the right shows the pressure vector at the selected scale. The slider walks through five scales (field, firm, division, team, practitioner). Edit the values directly to construct a field that matches your environment, or load a preset.
Click a cell to edit; drag to set intensity
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field
Coercive (regulation, mandate)
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Mimetic (peers, benchmarking)
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Normative (profession, ethics)
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Dominant mechanism
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LAB 2: THE DECOUPLING LENS
Two signals; one decoupling dimension.
The dotted line on the left is the formal signal (policy, charter, public commitment). The solid line on the right is the operational signal (what actually happens). Drag any value on either side. The decoupling-dimension readout updates in real time. Three pre-loaded scenarios seed the lens with characteristic decoupling shapes.
Drag a column on either side to reshape the signal
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Decoupling dimension
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Per-scale RMSE
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Locus (highest divergence)
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The dimension summarizes the field; the locus tells you where to act.
LAB 3: REGULATION TRANSLATION CASCADE
Edit any layer. Drift recomputes. The waterfall animates.
A regulation is not delivered to a practitioner. It cascades through firm policy, engagement SOP, and practitioner action. Each layer is an editable text box. Drift between adjacent layers is computed via TF-IDF-style cosine similarity. Three preset cascades (DORA, EU AI Act, DAMA-DMBOK) load with one click.
Total drift (sum of edge drifts)
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CHAPTER 13 NOTEBOOK PATH
Each lab has a notebook behind it.
The studio is the surface. The chapter is where the apparatus is implemented and the failure modes are named.
Why governance needs a fractal lens
Frames the chapter, names the three streams, sets the bounded claim.
Pressure field and decoupling
The PressureVector type, the multi-scale decomposition, and the decoupling dimension.
Knowledge graph and visibility graphs
Apply Chapter 12's box-covering and visibility-graph descriptors to governance corpora and time series.
AI as subject and agent
Provenance graph for an LLM, plus an Anthropic-backed parser with deterministic mock fallback.
Translation cascade
Regulation through firm, SOP, and practitioner with TF-IDF-based drift.
Capstone and the failure modes
Build a diagnostic for your own environment. Then read the four failure modes before you ship anything.