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Russ Gaskin's avatar

I find the question, "How to work with systems that don’t want to change?" interesting, because systems are systems precisely because they have continuity. Without continuity, we have chaos.

And we shouldn't undervalue the value of continuity, of predictability, of something that we know or we're at least familiar with, versus the unknown, untested, and not-yet-experienced.

As Diane Musho Hamilton and folks working with Polyvagal Theory have noted, sameness calms our nervous systems while difference excites our nervous systems. People are encountering so much difference now, so quickly, that it's overwhelming our nervous systems. We don't have adequate practices to deal with that. And since so many of us have dysregulated, even traumatized, nervous systems, and predictability and repetition are natural salves for this, we tend to prefer the devil we know to the devil we don't, even if we literally believe it's a devil.

Whether we are for a system or against a system, whether we benefit from it or we are harmed by it, we all get something from it. At the very least, even if I resist the system, it gives my life some meaning and direction. So we all carry water for dominant systems, even if we're completely dissatisfied with them.

William James wrote in 1890 (in The Principles of Psychology), "The great thing in all education is to make our nervous system our ally instead of our enemy". That's the one element I'm not seeing in the Grenfell Model of Change, and maybe one we most need.

Mike Jackson's avatar

You're pointing at something real, and we haven't resolved it visibly enough in the framing.

The Harm Gap is not a prediction instrument. It measures the distance between what was knowable — seismic hazard, population exposure, governance quality — and what was done about it. Venezuela's fault system was not unknown. The governance capacity to respond was measurable. What failed was not knowledge. It was the decisions made, or not made, in the window between knowing and the event. That's the complicated-to-complex failure mode PreEmpt Disaster is designed to make visible and attributable.

You're right that a different failure mode exists — the genuine phase shift where prior data misleads rather than informs. We don't claim the system handles that yet. But we do have a working test model of experimenting with the unknown The live crisis layer has an explicit chaotic domain protocol whose instruction is: stabilise before you analyse. Not more data. Hold the line on values while the picture forms. That logic should be visible at the PreEmpt Disaster level, not buried in operational detail — and you've identified a real gap.

Where we'd push back: the binary between data engineering and experimenting into the unknown is false in the specific geography this system operates in. People are not dying because their governments lacked a probe-sense-respond epistemology. They are dying because knowledge that existed — often for decades — was ignored, suppressed, or never reached those with authority to act. The Harm Gap measures that distance. The Decision Attribution Layer names the decisions that produced it. That is a governance accountability instrument for the complicated domain. Not a controllability claim.

If you're working on what happens when decision support hits genuine phase-shift territory, that's a conversation we want to have.

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