Why not just require independent reproduction to even publish?
Furthermore, who's going to be doing that independent reproduction? How are you going to incentivize that?
If you require independent reproduction for every paper in a field where that's even possible, that's going to mean either you need to double the rate of running experiments in that field (unlikely), or double the number of researchers in that field (also unlikely) if you want to maintain anywhere close to the current rate of papers being published. (And again, even if you could double the number of researchers, you still need to provide enough of an incentive to reproduce that literally everyone is doing so for half of the studies they run. And you'd somehow have to ensure that you don't end up with fun, interesting studies getting 15 different groups reproducing them, while less-flashy studies that are still important fundamental science languish for years without anyone caring to try.)
Given how much of "publish or perish" is institutional inertia and culture, the idea that it could be systemically "nudged" to allow for this kind of shift is essentially a fantasy. Far too many of the Old Guard who are already in charge of the tenure committees would say, "Well, I had to publish 327 papers to be given tenure, and kids these days have so many newfangled things that let them write papers faster; why shouldn't we require them to publish 327 papers, too??"
You don't have to quite double the number of researchers or experiments. It typically takes less work to replicate final results than all of the work getting to the point of good results. Presumably a lot of the replication would be outsourced to CROs.
Though since the CROs would be focused on replication of results alone, any theoretical errors or errors in experiment design wouldn't be discovered. Replicating results will mostly catch fabricators. It won't catch nearly all of the far more important to the replication crisis bad experimental design.
The point is, op is right that it’s expensive. The computer industry that we’re in claims to be data driven but I’ve observed numerous poor quality studies being done to drive decisions that I’m pretty jaded (no reproduction, poor sample sizes, skewed sample sizes where it’s employees, etc etc). And these are smart people where the decisions being made can impact the financial outcome.
But we don't even seem to be picking up the low hanging fruit - I used to work as an algorithm researcher, and reproduction there (for anyone who set up their experiments logically) is as easy as running a script and waiting x hours for the results to land. Yet reproduction studies were still a novel concept in that field, rather than a standard part of the submission workflow.
If a paper needed to clear the bars of
- can be reproduced by reading the paper and/or a few meetings with the original team
- data is independently reproducible to within the usual statistical parameters
It would presumably increase the signal:noise of research.
Requiring reproduction is several bridges to far.
But requiring reproducibility seems complete reasonable!
What such a requirement would do is dramatically scale back research, and highly incentivize researchers to lie, or the "independent labs" to fudge in order to keep drawing funding from their collaborators.
I think a lot of money would be saved by avoiding researchers to waste resources in dead ends, by trying to build upon results that can't be reproduced. So not exactly double.
Bad incentive structures.
Even reproduction doesn't solve the problem of theoretical errors: https://news.ycombinator.com/item?id=36230450
I suggest an improvement.
It just seems that the entire scientific publishing industry is there to support a jobs and prestige program. Any science is just a side effect that somehow justifies the whole racket, from NSF budget to postdoc dinner table.
Societies fund many things for many reasons, not sure science is worth singling out here.
We could have a separate kind of journal for not-yet-reproduced results, and somehow ensure that the prestige is zero (or equivalent to just posting the study on a blog).
Suppressing publishing at the same time as actively trashing the ability to even study seems like a recipe for disaster way above publishing bad papers to me.
It's not impossible if we're actually interested in the truth.
> Suppressing publishing at the same time as actively trashing the ability to even study seems like a recipe for disaster way above publishing bad papers to me.
It's not clear that a study that cannot be replicated is worth the paper its printed on in the current environment where replication rates are 50% or less across the board. Other strategies that change how we approach individual studies are not as onerous (preregistration, open data), so maybe in that world individual studies would be worth it, but even in that world replication is the only sure fire way to validate results.
Replication is not a be all and end all, because things could replicate even though understanding is wrong (i.e., observation is right in the publication but everything else is wrong). Even the replication itself can be wrong, if certain materials share on unknown contaminant, for example. It addresses some issues, but not all.
For some areas it also not clear what replication means. What is it for theology, for example?
I can't imagine anyone who truly understands the current replication failure rates thinking that a single non-replicated study is valuable for anything other than informing what replications should be attempted.
Just think about it: replication rate is generally less than 50%. That means you'll have a better chance of determining the truth on any question posed by a study by flipping a coin than by actually reading the study.
> Replication is not a be all and end all, because things could replicate even though understanding is wrong (i.e., observation is right in the publication but everything else is wrong).
The observations are the only things that we have to get right. Interpretations can be subject to decades of debate (some QM debates are ongoing a century later), but if the data isn't reliable then you're just wasting time debating falsehoods. Replications are critical to ensuring we have reliable empirical data.
> Even the replication itself can be wrong, if certain materials share on unknown contaminant, for example.
Indeed, and literally the only way to figure out that such variables exist and are affecting the results are by independent replications. The more replications, the better. One replication is a bare minimum threshold to demonstrate that the process of gathering the data is at least repeatable, in principle.
> For some areas it also not clear what replication means. What is it for theology, for example?
It makes perfect sense in any context where you're gathering empirical data. For instance, if you're surveying people's interpretation of "free will" [1], then the process via which you probe their views should be replicable. This means being clear about the specific phrasing of the questions asked, the environment in which they were asked, the makeup of the cohort, and so on.
[1] https://www.researchgate.net/publication/274892120_Why_Compa...
Anything truly critical will (eventually) go through some replication/control of sorts (but it can take a long time).
You can either shut down most of research and then place your bets on what to keep and replicate, or you run broad but with a lot of incorrect stuff in it.
If you go for the former, you run the risk that you keep the wrong things, though. You have to have a way to quantify the direct and indirect costs of all the bad research and see if that trades off vs a much smaller research surface. Not sure if that is the case - empirical data matters much less for a lot of big decisions than people often make it out.
If it's inconsequential, then wouldn't that money be better spent on replications or other research that is consequential? I'm not really clear on what you're suggesting. Although maybe I wasn't really clear on what I've been suggesting.
Edit: to clarify, there are multiple ways to reorganize research. Consider an approach similar to physics, where there's an informal division between theoreticians and experimentalists. What if we have two different kinds of publications in social sciences, one that's proposing and/or refining experimental designs to correct possible sources of bias, and another type of publication that is publishing the results of conducting experiments that have been proposed. The experimentalists simply read proposals and apply for grants to conduct experiments, and multiple groups can do so completely independently. Conducting the experiment must strictly adhere to the proposed experimental design, no deviations can be permitted as is so common in social science when they find uninteresting results, otherwise this breaks the reliability of the results. A proposal should probably undergo a few rounds of refinement before experimentalists should feel confident in conducting the experiment, but I think the overall approach could work.
Sounds like a good idea to have a system of academic publishing that incentivises people to produce replications and similar studies then (and an academic norm of quoting multiple studies that support or oppose hypotheses)
And all that making any research that involves novel research unpublishable until someone else decides to dedicate their time to replicating the experiment from your little known working paper would achieve would be limiting incentives to experiment, especially in fields where it's perfectly possible to publish with statistical reexaminations of existing data (often flawed in other ways) instead.
I work in biology. At a panel of biology startup founders I heard one mention that she got a lot of her research ideas from papers studying bacteria which were published nearly a hundred years ago.
In biology you first seek to extend published results. Only if the extension attempt fails would you spend effort trying to replicate it (assuming you just don't abandon the pathway entirely).