A few weeks ago we talked about how to communicate climate science to all three target audiences – other scientists, policy-makers, and the public. We touched on how scientists “do science,” i.e., through research, data analysis, conference attendance, and scientific publication. Today we’ll take a closer look at how scientists can communicate climate science to other scientists, including those scientists who specialize in other fields.
1) Publish the Research: As already noted, the main way for scientists to communicate the science to other scientists is to publish it in peer-reviewed journals. Doing so allows scientists to carefully lay out the premises, the methods, how the data were analyzed, the results, and the conclusions, all so other scientists can evaluate – and recreate – the work. I’ve discussed peer review in depth in previous posts. [Click on these links to read Part 1 (basics of peer review), Part 2 (when peer-review goes wrong), Part 3 (abusing the system), and Part 4 (using the internet to bypass peer-review) of the series.] Once published, the research is further scrutinized, which may confirm or refute the work, and usually leads to more studies…and more publications. Many climate researchers, for example, have hundreds of peer-reviewed scientific papers (whereas most climate deniers have few, if any, peer-reviewed publications).
But think about the scientific publishing process for a moment. Like physicians, for example, where individual doctors may specialize in endocrinology, brain surgery, dentistry, or podiatry, scientists may specialize in astrophysics, archeology, biology, chemistry, mathematics, geology or dozens of other specialties. The more specialized the professional training and expertise, the greater the likelihood that a given scientist won’t be keeping up to date on advancements in other fields. A biologist is likely to have memberships and subscriptions to several biology-related organizations and journals, but may not be reading a physics journal discussing heat transfer in atmospheric systems.
This presents the dilemma that while journal publication is critical, it is largely focused on communicating with other scientists within your own field. That said, despite the tendency toward greater specialization, there is also a greater need for multidisciplinary collaboration. For example, ecologists looking at migratory patterns will see that those patterns are being modified by climate changes.
So how does one reach out to scientists in other fields?
[Continue reading at The Dake Page]
The above is a partial cross-post of a full article on The Dake Page. Please click on the link above to read further. Thanks.
David J. Kent has been a scientist for over thirty years, is an avid science traveler, and an independent Abraham Lincoln historian. He is the author of Tesla: The Wizard of Electricity and the e-book Nikola Tesla: Renewable Energy Ahead of Its Time. He is currently writing a book on Thomas Edison.
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Despite my lurking silence there, the Dake Page articles are excellent, and reflect some admirable objectivity toward the science they address. I highly recommend them.
I’ve always been in a position where any research-based work I’ve done has required a fairly easily observable, physically functioning result. Consequently, there’s never been much doubt about the validity of utilized publications — assuming things worked as predicted.
That said, however, I came across two bad research papers during my early graduate work. In both cases, I had to hire someone else to properly evaluate them in order to definitively ascertain that they were incorrect, and that I could ignore them. Yet, as three post-graduate degrees were justified by their results, they remained unchallenged by the system that reviewed, and then approved their academic publications.
Against this backdrop, I’m not at all a climate change skeptic. And I think the overall evidence that humans have a significant roll in climate change is (apparently) very robust. However, it’s not necessarily the kind of easily observable applied science to which I was able to employ research. Climate is a long-term, statistically-described phenomenon, driven by many, complexly-interacting variables.
Of course, this doesn’t mean that science can’t be applied to its description. But sometimes I worry that at least some research is steeped in the kinds of statistical machinations that can hide misinterpretation — especially with regard to meta-studies. But despite my own, very strong hard science background in a field closely related to some of the science being applied, I will be the first to admit that I am completely unqualified either to validate, or to invalidate most results.
Regardless, trust in an impenetrable process can be a difficult accommodation.
I agree that publications shouldn’t be simply taken at face value. For many years I compiled all the existing literature on a variety of chemicals in order to define the “state-of-the-knowledge” on those chemicals. It was common to find data being used that was referenced to previous studies, but when I tracked those back to the citation they sometimes were simply citing an even earlier paper. Sometimes these could go back several layers such that you think you’re citing 2014 data when those data actually were created in 1954. Notwithstanding the more primitive measurement capacity at the time, sometimes (not often, but enough) I would find there had been a mistake made, and that mistake was simply carried along in all the ensuing papers. In other cases, “data” turned out to be some number that someone came up with at some point, but no one exactly knew how or where and there wasn’t any record of a study.
That said, science is always the sum total of all the relevant studies and data. On something like climate change there are active efforts (e.g., IPCC) to routinely evaluate the science to determine what is happening and why. The scientific consensus is built on dozens/hundreds/thousands of studies, so the sheer mass would likely make any mistake in one single study a moot point.
Still, I’m confident that scientists are working hard to evaluate the data and question everyone elses results. In complex-interaction type sciences, like climate change, the complexity necessitates greater – and continuous – scrutiny. The work relies on hard data, the kind of physically-functioning result you describe in the work you have experience doing.
One other relevant point: While the science of something like climate change is always building (and the results always strengthen the unequivocal conclusions), the “denialists” have never been able to put forth any defensible science that contradicts the real science. Usually, they contradict themselves from one breath to another. That’s because denialists start with their preferred conclusion and desperately seek anything they think supports it, even when it doesn’t, and even when it doesn’t make sense or contradicts what they just said. I’ll take the complexity and uncertainties of real science and statistical evaluation over the political machinations of denialists any day.
Okay, off to write.