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The Scientific Paper Is Obsolete (theatlantic.com)
James Somers, writing for The Atlantic: The scientific paper -- the actual form of it -- was one of the enabling inventions of modernity. Before it was developed in the 1600s, results were communicated privately in letters, ephemerally in lectures, or all at once in books. There was no public forum for incremental advances. By making room for reports of single experiments or minor technical advances, journals made the chaos of science accretive. Scientists from that point forward became like the social insects: They made their progress steadily, as a buzzing mass.
The earliest papers were in some ways more readable than papers are today. They were less specialized, more direct, shorter, and far less formal. Calculus had only just been invented. Entire data sets could fit in a table on a single page. What little "computation" contributed to the results was done by hand and could be verified in the same way.
The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it's contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you've actually discovered, clearly enough that someone else can discover it for themselves.
The earliest papers were in some ways more readable than papers are today. They were less specialized, more direct, shorter, and far less formal. Calculus had only just been invented. Entire data sets could fit in a table on a single page. What little "computation" contributed to the results was done by hand and could be verified in the same way.
The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it's contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you've actually discovered, clearly enough that someone else can discover it for themselves.
We are now in an era where only very few people actually need to know how reality works. The rest of us can become brand managers and youtube content creators.
That you can flood a scientific paper with reams of computer generated data is NOT science. That's technobabble. The point of the scientific paper is to lay down, ON PAPER, the technique you used and what you observed and then, in a separate section, editorializing what you've proven (or refuted).
That so-called scientific papers will merely dump the computer generated data or flood the paper with technical jargon without exposing the underlying algorithm or technique IS the problem.
At one time science was intended for the masses - that the Atlantic attributes this to "a simpler time" is also moronic as it was the intent of the authors, in fact all authors of the time, to write clearly and succinctly so that anyone could understand their work. You see that not only in the scientific papers of the time but also in the laws (the US Constitution). You also see the same problem in laws today where laws are now tends of thousands of pages long. How is any one person (let alone a dedicated group) supposed to understand the law as written?
To wit - it's a societal problem, not a scientific one or a problem with "overcomplex science"
The scientific paper will last as long as paper-printing does. It's still very convenient.
That being said, TFA does make a good point about how current technology can do better than paper. If designed well, an interactive document with computer-driven content can convey a deeper and clearer message.
Better still, perhaps an AI embedded within the document could answer questions about it.
If it weren't for deadlines, nothing would be late.
I'm not sure what is going on here, except that the summary reads like clickbait.
The rule of thumb I was taught was that you write your papers with the assumption that your reader's got only a basic background in the field. We're talking 'has completed a minor in the field' levels at most, typically--you fill in the holes necessary to understand the paper itself in the introduction. At least in the fields I was in, nearly anything that made it into a significant journal--meaning, anything worth even reading the abstract--would be using one of a set of programs for the number crunching, and at least some of the options were open source. Unless there were privacy concerns, you generally could get a copy of the data sets with a few emails if you wanted to shove 'em through a different one of the standard number-cruching programs--privacy concerns just add a few extra hoops. Regardless of that, somebody should have the raw data and it should be in electronic form. You should typically know before you even start the email conversation if there ought to be privacy concerns; if they claim there are when there shouldn't be, or that they somehow don't have the data still, that's a red flag, especially if you're being very interested in learning more about their research and not in the least bit hostile, because researchers are normally very happy to talk about their work as much as they're able to. (It's a great way to keep one happily chattering away for a while, too.)
If you can't understand the jargon and symbols, and you're got a reasonably good background in the field...Google-fu will help some, but generally it's a sign that you've found a journal to dump papers to when you're in a publish-or-perish situation, and the number of papers published matters more than if any of them are of any quality whatsoever.
The scientific paper isn't obsolete. How publication works and academia's relationship to it, however...
If programs are central to the evaluation of a paper then programs need to be published alongside the paper - in source code form.
It doesn't matter if the source code is published with Apache, BSD, GPL, MIT or no license at all (remains copyright to the authors.)
What matters is that the source code is available to review alongside the paper. In this, it isn't performance that is critical, but bugs that influence results, be they buffer overflows or simply logic errors.
A group of people separate to those that do the peer review of papers then needs to review the source code for correctness as to the results it produces.
One of the main points of a scientific paper is that it's peer reviewed.
A decent paper will probably take around 2 hours to read and 2-12 months to write. As inefficient as this is, it has some desirable properties:
1) It presents information in a somewhat standardized format. After all the gimmicky digital notebooks etc turn to dust and the software which runs them becomes obsolete, the articles will remain.
2) It provides references and allows you to use itself as a starting point to discover more about the subject and the claims.
3) It generally represents an incremental advancement in the field.
Aside from the fact that the article is essentially a Mathematica ad, it is somewhat clear that the author has it written any scientific papers
The Scientific Paper Is not obsolete, it has just fallen into evil ways. Paper or electronic, it is still needed in it's original purpose. It just needs to be "beaten with a blacksmith's hammer to get the rust and crud off" !
As a scientist who has published papers in peer-reviewed journals, I strongly disagree. I don't care for many aspects of the publication process or how academia works, but the scientific paper isn't obsolete.
Regarding the use of software in creating results, it is definitely a problem when that software is difficult to use or isn't available at all. The same goes for data sets, many of which aren't released publicly for a variety of reasons. These are issues that need to be addressed.
In my own work, I try to release the software used to perform my analysis under the GPLv3. I also try to include adequate documentation to allow the work to be reproducible. I also support making data publicly available, but sometimes the volume of data sets makes it prohibitive to redistribute the work. The best option in that case is to provide detailed instructions on how to generate the data set. But sometimes it's even worse, such as when the research requires using a closed source program with a license that prohibits redistributing the output. The license makes it relatively difficult to obtain the software for anyone outside of the US government or academia, unless they pay for a commercial license. There isn't a comparable piece of software, but the university that licenses the software uses restrictive licensing requirements to increase their revenue.
To the extent that it's possible, scientists receiving grant funding ought to release their software as free and open source software. The data sets should be released or detailed instructions should be included to allow others to generate the same data set.
Papers can be difficult to read, but there are at least some steps in the right direction. One of the encouraging changes is the use of more first person in scientific papers and less passive voice. The formal tone is being being phased out in favor of readability. I wholeheartedly support this because the subject matter is difficult enough to understand without awkward sentence structures. Peer-reviewed papers also provide some level of quality control for research, though not to the extent of reproducibility.
Scientific papers still have a place, because they're still the best opportunity for scientists to present the key points of their results and describe their methods in detail. Simply releasing software and data sets is not enough. Those also aren't peer-reviewed. The bigger issue is that there just isn't a lot of funding to ensure that results are reproducible. Due to funding limits, there just isn't a lot of effort to reproduce all but the most surprising results. It would be great if funding agencies like NSF would allocate more funds for ensuring the reproducibility of existing results. Unfortunately, funding is so competitive that researchers have to sell their work as being very novel rather than verifying existing research.
At one time science was intended for the masses - that the Atlantic attributes this to "a simpler time" is also moronic as it was the intent of the authors, in fact all authors of the time, to write clearly and succinctly so that anyone could understand their work.
Science has never been "for the masses". Most concepts of any meaningful complexity are not going to be written at an 8th grade reading level. Issac Newton's Principia is certainly not written "for the masses" nor should it be expected to be dumbed down. As Einstein once put it, things should be made as simple as possible but no simpler.
You see that not only in the scientific papers of the time but also in the laws (the US Constitution).
The Constitution isn't really a law. It is a framework for the laws. It sets the boundaries that are fleshed out by the laws. The actual federal laws are the United States Code, the United States Reports and the Code of Federal Regulations. There also
You also see the same problem in laws today where laws are now tends of thousands of pages long. How is any one person (let alone a dedicated group) supposed to understand the law as written?
You are presupposing that it is a good thing that laws be so simple that a single person can understand and know all them. The reality of our society is that it is so complex that the laws governing it inevitably will be similarly complex. Make a simple law and there are going to be gaps in that law unless you add complexity to deal with the corner cases. To circle back, science has no obligation to be simple enough for "the masses" to comprehend any or all of it.
MIT Random Paper Generator for computer science papers
https://pdos.csail.mit.edu/arc...
Mathgen for Math Papers
http://thatsmathematics.com/ma...
Seriously, does anyone even read the paper anymore? I read the abstract and possibly the method.
At the end of the day, it is just an academic echo chamber where every paper references each other and none of it is very earth shattering. You should read the dissertations that don't make it into journals, those are really sad. For example, "Analysis of Socioeconomic Status and Student Achievement", or in other words, "Poor kids don't get good grades.", most papers could classified as Ric Romero papers where the outcome is obvious or in some cases statistically insignificant such that more papers need to be written with new experimental methods.
But for those of your writing papers, I leave you with my favorite research design song.
https://youtu.be/Hxbz656Euyw
I think the problem is misidentified in your comment, but in the details. The data publication is part of the peer review and publication process. It allows another specialist in the field to go over your study and its results, and attempt to replicate them. It also allows for discussion of conclusions. The "Abstract" is supposed to be the basic, plain language breakdown, including the conclusions. However, while you're right about the societal issue, there's a deeper one: All of the relatively easy science has been done. The questions are getting more complex. We're looking to more subtle phenomena to find more secrets of the way reality works.
The observations of physical phenomena that allow computers to work far exceeds the time of Newton (believed by many to be the last time one human could know the sum total of accumulated knowledge about nature). Fields are specialized, and "jargon/technobabble" are the layman's epithets for a field's shorthand that he/she doesn't get. Yes, we could likely simplify the law. Knowledge is not so readily boiled down. No one bats an eye at the odd uses of common words you find in the skilled trades, but everyone loses their shit when a scientist falls back on terms with precise meanings within their own fields.
NOTE: It was once common practice to include an attempt at a layperson's digest with a lot of papers, or at least publish it alongside the paper. This has gone away, which is a shame. However, when every such digest turns into Dunning-Kruger effect demonstration with the public, I would think it gets old. But a lot of the science being done now is beyond the limits of common understanding. Quantum computing, block chains, AMPS firewalls... It's hard to try to break that stuff down for the masses when the Flat Earthers are gaining ground!
How many scientists engaged in climate science research understand even the basics of the Carbon Cycle?
[...]
Given that the first topic in my first university course on climate change was The Carbon Cycle, my bet is that nearly all climate scientists have a fairly well-developed understanding of the Carbon Cycle.
So much of science and scientific publishing relies on what I cynically call "argument by authority" -- someone got some claim past peer review so I will cite it without having to defend it to the reviewers of my paper.[...]
"Argument by Authority" is a well known logical fallacy, in which most scientists are well-versed. Argument by Authority is particularly egregious when the argument is by someone who isn't an authority at all, yet claims to be. This is common in more main stream media, including the kinds of crappy general interest books you can find at your local big box stores, like the ones on fad diets, but is incredibly rare in reputable scientific journals.
The fact is that if a scientist can over-throw an argument made by an authority in a field, they get a tremendous amount of respect, probably becoming authorities in the field as a result. The same goes for over-throwing the scientific consensus. That's the thing about scientists, we really like pushing understanding forward. That's the focus of our work.
Now your comment is instructive on logical fallacies, because your own arguments are absolutely packed with them. Your main problem is motivated reasoning (ie. proving your foregone conclusion), and that you are anomaly hunting, but you are also way behind on the literature, if you have any first-hand exposure to it at all. This means that you make several assertions that simply aren't true: It is well understood that and how the ocean's are absorbing the bulk of carbon emissions. The atmospheric and oceanic isotope ratios are well understood and continue to support our climate models, including absorption of the oceons. The seasonal variations due to the actions of biological systems are also well-understood. In short, the disagreement you see simply does not exist, the dominant models are supported by observation to an amazing degree.
All of this would be covered in detail in any university-level introductory climate change course. If you want to do some reading, I'd recommend Global Climate Change: Convergence of Disciplines, by Arnold Bloom. Honestly, if you can't at least give a common textbook on a well-developed field a read, you'd best just put your faith in the scientific consensus.