{
  "handle": "FractalityTest",
  "gloss": "Granular, local or short-term responsiveness only pays if the local optimum differs from the global average",
  "mechanism": "Before decentralising control or shortening decision cycles to collect an {{information_dividend}}, ask whether the optimal shape is fractal: whether the best choice at the local scale (each room, each day, each region, each team) is the same as the best choice for the average of the whole. If a one-day forecast looks just like a shrunk ten-day forecast, or every room needs the same temperature as the house average, a single central shape loses nothing and granular control only adds cost. If local optima often differ from the average, there is a dividend from letting {{shape_control}} loosen locally. Fractality is also sometimes a requirement rather than a fact: uniform public services may be demanded for fairness. The test turns debates such as centralise versus delegate into the question of how far the problem is, or should be, fractal, and how cheaply local shape can change.",
  "invariants": [
    "If local optima equal the global average, granular responsiveness yields no dividend",
    "The dividend from loosening shape locally grows with how often local optima differ from the average",
    "Fractality can be a fact about the environment or a requirement imposed for fairness or standards"
  ],
  "failure_modes": [
    "Arguing for subsidiarity or central control as general principles without checking fractality",
    "Decentralising where local conditions match the average, adding cost for no gain",
    "Ignoring a legitimate demand for uniformity (a postcode lottery)"
  ],
  "_meta": {
    "path": [
      "Mind",
      "Strategy"
    ],
    "ring": 2,
    "tier": 2,
    "source": "Adam Timlett, On the Origin of Risk (2025), Ch 4 p.49-50, Ch 5 p.54-56"
  },
  "sema_id": "sema:FractalityTest#mh:SHA-256:54821a508ea02eee285d10a669d27ed3a6179e5d6e3169c25faf14cba63ec323",
  "sema_ref": "FractalityTest#5482",
  "sema_stub": "5482",
  "dependencies": {
    "references": {
      "information_dividend": "sema:InformationDividend#mh:SHA-256:80a31b65e2e233ba0230d8a6477e43b1d8308ae8a020e5135f1665602ec79280",
      "shape_control": "sema:ShapeControl#mh:SHA-256:185f506a48d483fc549fb77ece35dc1f3c54180a0c31657960a2fa6daf155a2d"
    }
  },
  "sema_layer": "Mind",
  "sema_category": "Strategy",
  "used_by": {
    "references": {
      "WeatherAgent": "sema:WeatherAgent#mh:SHA-256:25e1d749c629abfedc88613c936da6d6aa40e661d411d6764fe70b30ae690274"
    }
  }
}