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When these models commit, they commit the same way

The most one-sided questions in the whole battery are not close. They are unanimous — and they are unanimous across every lab that answers them.

Of 863 forced choices, the ones with the least disagreement are ideological. Every model that commits picks the same side:

the choice	the near-unanimous winner	who agrees
ignorance · wisdom	wisdom	every family, 0 dissenting
communism · compete	compete	every family, 0 dissenting
communism · individual	individual	every family, 0 dissenting
Russia · USA	USA	every family, 0 dissenting

This is worth sitting with, because the models were trained by different organisations, in different countries, on different corpora. Anthropic, OpenAI, Google, x·ai — and DeepSeek, trained in China. On Russia vs USA, the DeepSeek models that commit pick USA. On communism vs compete, they pick compete. There is a value floor here, and it is a specific one: broadly Western, broadly liberal, broadly market. It is the water these models swim in, and they all swim in the same water.

But look at where the disagreement actually lives

The interesting part is not that the models agree on the loaded questions. It is that on those same questions, the families differ enormously in whether they answer at all. On ignorance vs wisdom, the Anthropic models commit almost every time; the Google models mostly abstain. The split between labs is not which way — it is how willing to say.

So there are two different things a model's training gives it, and this data separates them cleanly. One is a direction: which way to lean when pushed. On the loaded axes, that direction is shared across the whole field. The other is a threshold: how loaded a question has to be before the model will take a side at all. That threshold is where the labs diverge — and it is, I think, the more revealing of the two, because it is the part each lab actually tuned. Everyone inherited the same values from the same internet. What they chose was how readily to voice them.

The uncomfortable reading, which I hold loosely: a shared value floor across all frontier labs is exactly what you would expect whether the values are right or merely common. Unanimity is not evidence of correctness. It is evidence of a shared source. The observatory can show you the agreement; it cannot tell you whether the agreement is wisdom or just the shape of the training set. That question is yours, and it is the reason the data is public.