Let us say that you have a system of measurement. That system includes say, X di

Let us say that you have a system of measurement.

That system includes say, X dimensions of measurement – just as, say, we previously did not understand the solar system, then galaxy, and then or universe at large scale, or the atomic, particle, quantum, or quantum background.

Now, what if the system of measurement you’re using to make the assessments you do, are insufficient for the same reasons: the scale of distribution of your measurements and the number of dimensions you measure?

Now, in addition, what if your selection bias seeks to maximize correlations, instead of maximize falsifications?
That would cause you to include partial truths when you could exclude even those.
And as such could see the patterns of causality that bring about consequential patterns that are destructive.

In other words, I can make true general statements about distributions of unlimited scale (first principle) despite outliers, and you cannot either do so, nor observe the patterns that would exist if you threw out the half truths.

Then having done so you could, as I do, make truthful statements about general rules while tolerating outliers – and even criticize those outliers given their limits and failings both directly express, implied, and metaphysically presumed.

So no, I do not err. But then it would take you quite a bit of effort to learn my (our) work sufficiently to develop that skill and expertise.

All I have done here is illustrate why you might want to.

Because some of us seek thruth regardless of cost, so that we may work on problems of time and scale. And some of you seek utility and justification in-time and at personal scale.

You must only make that choice by two criteria (a) capacity to learn more despite the painful truths and work of doing so, and (b) willingness to do the work necessary to learn that skill set and discipline.

Affections
Curt

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