1. I'm not interested in being brow beaten by some fool more interested in winning an argument then in addressing the argument.
If you're going to keep attempting an ad hominem then I'm going to simply not talk to you. And then what will you have accomplished? ...you're going to get asinine...
Jeez, pot meet kettle.
To top it off, he addressed your points quite well and it appears that it's you that seems intent upon winning an argument with your long-winded reply, which, of course, doesn't specifically and concretely address the issues raised by the person you're replying to.
Funding to reproduce coming from same institution? So they'll have half the money for original research then. And the suckers tasked with the reproduction won't be advancing their own careers under the Publish (original, ground breaking work) Or Perish model used today.
Like it was stated, in a fairly appropriate analogy, reproducing others' work is akin to re-writing a new software project - in software dev, it's a losing game.
In science it's important, but like in software dev, the boss isn't interested. And while the result may be beneficial, it's hard to convince people that it's a rewarding career move to play catch-up to others' work.
Having said all that, I think we all agree that reproducibility is important -- question is, how to go about it as the current system kinda disfavours it in all but the most important projects.
We need to implement specific, concrete changes -- having grad students do some of that is a good idea, but not sure if it'll completely solve the issue.
But laymen will at least understand what has and has not be verified. That is important. Science cannot be something only scientists understand any more then the law can be something only lawyers understand.
Laymen will never understand cutting edge science (unless they're quite keen on the topic at hand - a miniscule minority), and any layman that thinks they understand the law as well as lawyers generally get their arses handed to them should they attempt pro se representation.
Specialization in complex fields is natural.