As you say, there are "different assumptions". The point of calculating
confidence intervals is to avoid being hung up on arbitrary thresholds.
One can produce confidence intervals by inverting the chi-square test -
this would remove your dilemma ;). Another point is there are multiple
"chi-squares" (eg Pearson v Gibbs for these kinds of data; Wald, score
and likelihood ratio tests more generally), which also can disagree.
They are all only asymptotically equivalent. This is all aside from
the widely shared distrust of P-values...