2025-12-25, Mathy monday

I’ve been trying to organize my work by giving different kinds of thinking their own days. Yesterday was Sunday Funday, which for me meant cleaning up old tabletop role-playing game material I’ve been carrying around for years. Today is Mathy Monday. That doesn’t mean numbers. It means using math the way I actually use it: as a tool for reading systems without getting hypnotized by their language.

A useful test case for this is the recent proposal to build a large data center near where I live. Like most major development projects, it comes wrapped in claims. Claims about jobs, environmental responsibility, legal compliance, community benefit. The usual public conversation treats these as statements of intent and then argues about whether the intent is sincere or sufficient. That framing is already a mistake. The more basic question is structural: what role do these claims play inside the decision-making system?

To answer that, I treat the city and its approval process as a system, not an agent. It performs a finite set of operations: zoning approvals, environmental review classification, permit issuance, enforcement actions, appeals, and court review. Once you list those operations, you can take any claim and ask a simple, very math-shaped question: does this claim constrain any operation, and if it is violated, does the system behave differently?

When you do that, a hierarchy appears.

Claims like “this project will bring jobs” or “this will be good for the local economy” do not constrain zoning or permitting. Nothing in the system checks them. Nothing breaks if they fail. These claims are decorative. They frame the project narratively, but they do not steer the machine.

Claims like “the project will meet environmental standards” or “water and energy use will be responsibly managed” sometimes go a step further. They may be consulted. They appear in reports and meetings. But unless they are tied to specific thresholds with automatic consequences, violations are tolerated. The system absorbs the failure and continues. These claims are aspirational.

Then there is a much smaller class of claims that everyone ends up fighting over: which environmental review pathway applies, whether the review was properly scoped, whether legal requirements were met. These claims directly constrain operations. If they fail, permits pause, studies are redone, or courts intervene. When they succeed, they don’t just fix a single step; they change what the system has to do next time. These claims are structural. They create feedback.

Once you see this structure, the Hermantown debate becomes much easier to read. Almost all of the language people argue about lives in the decorative or aspirational layers. Almost all of the actual power is concentrated in a few structural choke points tied to process and procedure. And even there, enforcement is narrow and reactive.

At that point, a tempting conclusion is: “Well, then we should just demand better choices. We should require job guarantees. We should enforce outcomes.” But that response still assumes agency. It assumes the city or the corporation can simply decide to behave differently.

This is where systems theory matters.

What we are looking at is not a set of bad decisions by agents. It is a system under strain behaving exactly as systems under strain behave. As slack disappears (economic slack, political slack, ecological slack) systems shed expensive constraints and harden cheap ones. Enforcing material outcomes like job creation is costly: it requires measurement, attribution, monitoring, and punishment. Enforcing procedural correctness is cheap by comparison. It is legible, defensible, and compatible with courts. So the system reallocates constraint accordingly.

In control-theoretic terms, outcome variables become under-regulated while internal state transitions become over-regulated. In organizational terms, compliance replaces performance. In mathematical terms, high-cost feedback loops are cut, and low-cost invariants are preserved. The system is still “stable,” but only in the sense that it continues to operate. Its outputs are no longer governed; only its internal consistency is.

This is why aspirational claims remain aspirational decade after decade, across administrations and jurisdictions. It is not primarily a moral failure. It is evidence of non-agency. The system is not choosing to ignore outcomes; it is structurally incapable of absorbing the feedback that outcome-level enforcement would require without destabilizing itself.

Seen this way, the uncomfortable conclusion is clear. If a city actually wanted job creation to matter, aspirational claims about jobs would have to be made structural: written into contracts, tied to enforcement, and connected to repair when they fail. At the same time, many of the structural claims that do exist today do not have enforcement strong enough to matter for outcomes people care about. The system is very good at protecting its procedures and very bad at guaranteeing its promises.

This is exactly what collapsing systems must do. They preserve internal invariants and externalize failure. They continue to function by narrowing what “counts” as success. Math doesn’t fix that. But it does make it visible. And once you see institutions as systems rather than agents, a lot of familiar questions, “why won’t they just…?", dissolve. What remains is a colder, clearer problem: what kinds of constraints is this system still capable of making real, and what kinds has it quietly decided to let decay?

And that gives a much more stable ground for everyone - including these civic systems - see their own futures in an honest way.