> This is true, but it's true for almost every observational study, and IMO too easy a dismission.
It's also a correct dismissal. The vast majority of results don't replicate. It's super-easy to come up with results like this paper just by playing around with what you control for (with a 5% of a false positive each time) until you get the result you want. It's almost impossible to tell if this happened. There are many similar issues.
> You can use this reasoning to dismiss, or more likely, to cherry-pick probably 95% of all scientific results from economic/medical/social/nutricion/climate science.
And you should! You should believe results only once they've been replicated multiple times, by multiple communities, with multiple methodologies.
> I'd say the onus on sceptics in this case
The onus is on the people presenting the result, in all cases. That's the scientific process. The authors need to defend the null hypothesis as vigorously as you can.
> This paper is likely headed for a serious economic journal, where it typically goes through at least days of labor to scrutinise the execution/details/methodology in peer review. I'm not invested enough to volunteer for that.
Have you ever gone through a peer review process? Seriously?
I understand you're not invested enough to do that, but neither are the reviewers. It's a volunteer position with no credit or upside. Most give a cursory skim, and either accept or reject. It's no better than chance.
Seriously. NIPS did a study, and found it is literally no better than chance.
Of my own papers, I've only had one where peer reviewers did an in-depth read. For the rest, acceptance was completely random. Reviewer comments often have little relation to the actual paper (many reviewers just skim the abstract and the intro, and don't even fully read those).
The authors posit plausible evidence (observed variance across states with different introduction dates of laws, car ownership, going from 2 to 3 children) that car seat laws was a deterrent to having more than 2 children. A substantial criticism would be to come up with some possible confounders or alternative model of the variation. Saying that it might be caused by anything is a low effort dismissal.
> Have you ever gone through a peer review process? Seriously?
Yes I have, on both sides. Maybe it differs by field, but I (and my fellow PhD students) took it serious enough that we rarely read and finished writing a peer review within a single day. (This was mostly on economic theory / methodology papers, where even understanding the paper can take multiple days.)
I am dismissing it as:
One paper = interesting hypothesis
Multiple replicated papers = theory
Multiple replicated papers, with substantially different methodologies = scientific fact
> Yes I have, on both sides. Maybe it differs by field, but I (and my fellow PhD students) took it serious enough that we rarely read and finished writing a peer review within a single day. (This was mostly on economic theory / methodology papers, where even understanding the paper can take multiple days.)
Interesting. I've worked in several fields, and if this is the case, economics is pretty special. Good on you!
It wasn't always this way. As an economist, you study incentives. Think about how to prevent your field from sliding the way others did. Right now, academic incentive structures dictate cursory skim, and cultures+behaviors tend to (often after many years) align to incentives. As someone in a field (apparently) further along that path than economics, all I can suggest is to act sooner rather than later. It's easier to preserve cultures of integrity than to fix cultures of the opposite.
Lecture me again about incentives :)
This conversation illustrates the challenges with the reproducibility crisis. There is a fundamental problem in how we do science and that problem is hidden by our everyday experience of how effective science has been. This experience colors our perceptions of almost anything that gets dressed up as serious science, including objectively serious science. The scientific process is idealized as this effective tool but research happens at the behest of imperfect institutions and fallible people. Institutions and people are driven by financial and reputational imperative as well as the ideals of their research goals. These can cut strongly against the interests of performing meaningful research and publishing good science.
Having skeptical priors about research in general, whether incentives, error rates, or whatnot, is totally fair.
I look at the first paper as generating a hypothesis. That's the first step in any scientific process. A few replications later, we've got a theory, and then a few more later, a fact. The first papers are as important as the rest of that pipeline.
What causes outright harm is:
1) Papers with poor methodology;
2) Authors overselling their results; or just as often
3) Readers / reporters giving too much confidence in preliminary results
To be clear, I was calling em500 on #3, not the authors on #1 or #2.
On a skim, I don't see obvious problems (but, then, I wouldn't expect to find them; most require a deep read). It's published in an open access venue, which is always a good sign. It also helps that you're from BC, which for the most part, (still) has a pretty good reputation for scientific integrity (there's been a rapid decline in scientific integrity over the past two decades, and that's hit the institutional culture across the river from you particularly hard).
So you're okay by me!
Most researchers are incentived to churn out as many papers as possible. Most people who are making research grant decisions have little incentive to give grants to substantial science over insubstantial science that merely looks good. After all they're unlikely to face career consequences for funding science which doesn't replicate. Many of the people involved in the production of science are disincentivezed to point out problems with the process of science because science funding depends on science being highly esteemed, which only indirectly and with significant time lag depends on the effectiveness of science.
All this leads me to the conclusion that, yes, it is entirely possible that 95% of science in those fields (and maybe others) is junk.
I'm don't think that's farfetched at all. The problem though is that people will not apply uniform 95% skepticism to all studies. They'll just embrace or dismiss them based how how aligned the results are with preconceptions.
> Intervention: Jumping from an aircraft (airplane or helicopter) with a parachute versus an empty backpack (unblinded).
In realty I think a proper trial is supposed to always use the best known treatment as control.
This is true, but it's true for almost every observational study, and IMO too easy a dismission. You can use this reasoning to dismiss, or more likely, to cherry-pick probably 95% of all scientific results from economic/medical/social/nutricion/climate science. Just imagine the actual mechanics of setting up a proper Randomized Controlled Trial of seat belt safety!
Back to the actual study, the reasoning appearch to hinge on the variation of outcomes between 1) having a 2nd and 3rd child 2) between car and non-car owning families 3) accross different states in the US with different introduction dates between car seat laws. Of course, their might still be lurking confounders, but the presumption that this is really caused by car seat laws sounds quite convincing to me[1]. I'd say the onus on sceptics in this case is to actually propose some possible confounders that might explain variation in all of 1), 2) and 3).
[1] Disclaimer: I haven't gone through the details of the paper to see if the idea is actually well executed. This paper is likely headed for a serious economic journal, where it typically goes through at least days of labor to scrutinise the execution/details/methodology in peer review. I'm not invested enough to volunteer for that.