And what should be used as an alternative? There is no reason to believe banning p value would result in improved research quality. Desperate researchers will just find another technique to game.
1. Can the general public see it as jargon? The general public see p-value, and they think 'oh, those scientists probably know what that really means, just tell me if that number should be big or small to be meaningful'
2. Can a headline be made of it? ( Hypothesis X shown to be 'statistically significant' because a journalist saw the p-value result)
3. If a colleague does not understand it, can you make fun of them for not understanding such a 'simple' concept?
Then the referee and reader will be required to understand it and will have the ability to critique it.
In the case of hard sciences and engineering, it's direct sensory data that feeds the argument and maintains the rigor. Every person's eyes more or less, function the same, lest we descend into philosophizing about language, continuity of meaning and perception.
Science will eventually have to come to terms with realizing that interpretation and truth is much more variant than the ideals of science reach for. A lot of social sciences have accepted this, and even teach this. But the expectation is people should then be more intelligent, hard working, and overall have greater competency than the norm demands. Unfortunately this is what creates part of the problem - the ability to bring a pattern into actual existence, by observing it before it actually exists.
I don't like the idea of survival of the fittest in research and ideas though. I think it starts with simple questions, like 'what are we looking to prove/demonstrate/etc?', 'why/how?', which is concurrently processed with stuff like ethical and moral introspection and discussion.
But the big point of science half the time is that no one knows what they are doing. The prestige and authority surrounding academia doesn't really place as much emphasis on this as it should.