Census weighting:the arithmetic, worked through

Whoever answers a question is never a cross-section of a country. In conventional research the people who respond are the people who are reachable, available and willing, and those three filters are not neutral. In a simulation the equivalent problem is that the profiles generated skew towards whoever is easiest to describe.

Weighting is the correction. Every respondent, real or simulated, is assigned a weight so that the groups they belong to contribute to the total in the proportion those groups occupy in the population, as measured by an official source — the Census Bureau in the United States, CBS in the Netherlands.

It is worth being clear about what this does and does not fix. Weighting corrects composition. It cannot correct for a group being systematically misunderstood: if a segment's responses are wrong, scaling them up makes the error larger, not smaller.

Treat those two segments as equal voices and you average 40% and 80% and report 60% acceptance. That is the unweighted answer, and it is the answer you get by default from any method that does not correct for composition.

Weight them by population share and the arithmetic changes. The two segments together are 28.8% of the population; within that, the mainstream segment is roughly three quarters of the pair. The weighted result across the pair is about 50%, not 60% — because the segment that is three times larger was reported as though it were the same size as the smaller one.

Ten points, from one correction, on two segments. Across eight segments with shares that differ by a factor of three or more, the gap between the weighted and unweighted answer is routinely large enough to reverse a decision.

The direction of the error is the part that should worry you. It is not noise. The enthusiastic, articulate, easily-described segment is over-represented in unweighted output every single time, which means unweighted results are consistently more optimistic than the population they claim to describe.

A correctly weighted simulation is still a simulation. Weighting is a statement about composition, not about correctness: it guarantees that the groups are present in the right proportions, and guarantees nothing whatsoever about whether each group's simulated response resembles what those people would really say.

It also does not create statistical significance. Significance comes from sampling real units from a real population with known probability. Nothing here is sampled, so there is no margin of error to quote and none is quoted.

Reynard is a simulation. It is not fieldwork, it carries no statistical significance, and it cannot replace talking to a customer. Treat it as a fast, structured second opinion that tells you where to look — not as evidence.