Both of those statements are false. Everything has a result. And the p-value is very literally a quantified measure of how interesting a result was. That's the only thing it purports to measure.
"Woman gives birth to fish" is interesting because it has a p-value of zero: under the null hypothesis ("no supernatural effects"), a woman can never give birth to a fish.
I ate cheese yesterday and a celebrity died today: P >> 0.05. There is no result and you can't say anything about whether my cheese eating causes or prevents celebrity deaths. You confuse hypothesis testing with P-values.
The result is "a celebrity died today". This result is uninteresting because, according to you, celebrities die much more often than one per twenty days.
I suggest reading your comments before you post them.
p-value doesn't measure interestingness directly of course, but I think people generally find nonsignificant results uninteresting because they think the result is not difficult to explain by the definitionally-uninteresting "null hypothesis".
My point was basically that the reputation / carrer / etc of the experimenter should be mostly independent of the study results. Otherwise you get bad incentives. Obviously we have limited ability to do this in practice, but at least we could fix the way journals decide what to publish.
"Woman gives birth to fish" is interesting because it has a p-value of zero: under the null hypothesis ("no supernatural effects"), a woman can never give birth to a fish.