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MrMind comments on I love zebras - Less Wrong Discussion
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I agree wholeheartedly with OP's conclusions.
Here, AFAICT, there are two uncorrelated problems.
The first is that Fisher's test can be used to show correlation in a multivariate distribution against the null hypothesis of uncorrelated distribution. Here clearly we do not have such a distribution, since the 'virtual' example is actually the prior, or the null hypothesis in frequentist parlance. But you cannot inject the prior in the data sampling distribution, pretending it to be a "virtual" parameter, and hope to get meaningful results back.
The second problem is of course that the prior is categorical about the absence of zebra, an assumption clearly refuted by the data.
Yagami's conclusion still stands, but for a much simpler and certain reasons than his bogus analysis: if you assume there are no zebras, and you find some zebras, then the assumption is refuted, with certainty 1 (or again, in frequentist-speak, with p=0).
A null hypothesis is a statement about parameters, while the virtual sample is a statement about statistics, so it's not quite correct to say that virtual example is the null. And the null isn't the same as the prior; the null hypothesis is, as the name implies, a hypothesis, while the prior is a confidence level assigned to a hypothesis. So, for instance, "I think the null has a 90% chance of being true" would be a prior.
Your last paragraph, thought, is correct. The correct test would be a Poisson distribution with lambda = 0, and the probability of getting a non-zero value when lambda = 0 is 0.