> Even if you somehow waved a magic wand and fixed replicability perfectly tomorrow, entire academic fields would still be worthless and misleading.

Even ignoring how, frankly, paternalistic and condescending this sentence comes off as, let's take the rest of your comment on face value.

First, I can agree with you that the parent comment's idea about not allowing publication without replication is a non-starter; it would basically be impossible to implement (in the U.S., you'd immediately run into 1st Amendment issues), and on a practical level, that doesn't match with almost any realistic scenario of how research both is or could be conducted. Anyone that can get published should be welcome to do so.

However, I think that the idea of funding a subset of replication studies would have great value, and your list of "issues" are largely knocking down strawmen. Let's look at this from the point of view of a funding agency, which annually pour billions of dollars into research.

1. Logic errors would be great! A replication report stating "the conclusions of this research are deeply invalid due to x,y, and z logic errors here, here, and here" would make the agency less likely to fund authors that make those errors. If the errors don't invalidate the conclusions, they're still worth noting and can be taken into account.

2. Effect sizes varying in replicated studies is still useful information. Not all "does/doesn't replicate" questions need a binary yes/no answer.

3. Similarly to #1, catching and publishing instances where authors are making invalid claims (even if not doing invalid research) seems like a good thing. "Hey, these researchers have a tendency to claim X when really they're talking about Y. What the heck?" is great information to know for a funding agency to know.

4. See #1 and #3. Generally, the authors of the replication studies are also going to be intelligent; if they're being paid to check for logical fallacies and incoherent concepts (one can imagine a first-year required grad course that lays out these ideas and case studies of how to catch them).

5. I've been thinking about a situations where this still wouldn't produce useful meta information, and I'm having a hard time coming up with them. Imagine a fish survey, where divers are doing fish counts along transects. You can't go re-observe those fish, but a) research groups might want to change their methods to include using cameras instead of marking dive slates, or b) if you are able to re-run their transects due to good record-keeping (yay, replication!) but don't see the same fish, the funding agency now knows that a) the original research group has solid experimental methods and b) maybe they should keep funding groups to run that transect because of the variation, or not fund groups using a single transect data as the basis for forming conclusions. Happy to consider non-outlier (i.e. building a second LHC) examples where this breaks down.

6. Yes, maybe don't fund groups to try replicating these findings. Or maybe do occasionally anyway--if the research groups are doing good work, it should be cheaper to conduct replication-based research than doing a novel one anyway.

7. This is a good argument for replicable research. A huge number of research proposals go unfunded, which is to say that many researchers are somewhat competing for funding. In this paradigm, saying "hey, my group found and thoroughly documented a huge, glaring issue in the methods used in these studies due to a bad-faith corruption of historical data," in a situation where agencies would be looking to pay groups for valid claims. Increasing the number of replication studies adds a greater adversarial capacity to a research system which helps to catch/prevent this kind of fraud in the first place.

This is already a long comment, but I can make similar points about almost all of your claims. In summary: you seem to be making the assumption that replication studies are basically done by robots blindly following an instruction manual of someone else's research. Especially given the funding incentives mentioned above, I don't think that would be true; rather, many errors would be caught (or prevented ahead of time) and lead to better, more solid research being done in the first place.