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.

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.

Plenty of journals do, just mostly in fields that don't emphasize P-values. Chemistry and materials science tend to focus on the raw data in the form of having the instrument output included, and an interpretation in the results section.

The peaks in your spectra, the calculation results, or the microscopy image either support your findings or they don't, so P-values don't get as much milage. I can't remember the last time I saw a P-value in one of those papers.

This does create a problem similar to publishing null result P-values, however: if a reaction or method doesn't work out, journals don't want it because it's not exciting. So much money is likely being wasted independently duplicating failed reactions over and over because it just never gets published.

That is what this article is about, changing the expectations of researchers and journals to be willing to publish and read research without p values.