Science and such

Why Open Science Daily?

In February of this year I started a new project: a Twitter account called Open Science Daily (@journal_365). I started after reading about Sci Hub, a project of systematic piracy of research articles from behind journal paywalls. This matters because such articles are the lifeblood of academic work, but the cost of journal subscriptions is keeping them locked away. You might not think it’s a big deal whether or not a scientist has access to the Antarctic Journal of Annelid Research but what about journals publishing the latest findings on cancer?

Contemplating a Life Without Truth

I had the jarring experience myself of discovering that one of the universities I work for had forgotten I existed (at least for staff computing privileges) and cut off my access to electronic journals. It felt like I’d lost a limb or a smartphone. I wondered how anyone could possibly survive without being able to find out stuff whenever the out of stuff needed finding. What do you do without access to truth as filtered through the peer-review process? Those were dark days indeed.

After reading about Sci Hub I thought that it should be doable to establish some sort of framework where a journal could offer content freely by optimizing on the fact that its input (research) comes to it for free, its reviewers are free, editors may be unpaid, and there is no longer the overhead of producing materials in hard copy. As I contemplated how this might work, I suddenly remembered that it already existed, and was called open-access publishing.

Now I’m not the most up on my open-access resources, but I’d like to think that I have at least a little more knowledge than the average Jane. Yet I forgot these things even existed! Free peer-reviewed knowledge, and I forgot! It occurred to me that if I didn’t remember these things existed, then (barring explanations including but not restricted to teaching-related stress, lack of sleep, and lack of caffeine), how many other people don’t know or forgot? And so Open Science Daily was born.

So What, Exactly, Are You Doing?

Using the OSD account, I’ve been tweeting about one open-access science journal a day (more or less- but my track record is pretty good). I include the name, the url, and some key hashtags, but my strategy for maximum attention-getting is to use images. Initially I started off doing this sort of thing:

Earth System Dynamics

 

But then it got a little fancier,

Paleo Electr

 

and fancier (this one makes my eyes happy),

TWBul.png

 

and now they’re mini art projects. (Note the superposition of the semi-transparent storm clouds over the melting glacier to give the whole thing an ominous feel.)

EarthFut

 

While making pretty pictures is fun, I’m cognizant that my images might be the first thing someone sees of a given journal. In other words, I’m making the first impression, and I don’t take that lightly. That means I try to make the images look clean and professional, and take cues from the journal’s homepage about what might be appropriate, or what those running the journal might like to see. Sometimes they make it easy, such as by putting a tiny Mars rover at the top of their page, so I can do this:

GeoIMDS

 

The descriptive text in my images comes verbatim from the journal’s homepage whenever that is possible. This is primarily because I’m dealing with many topics that are new to me, and I don’t want to make paraphrasing errors. It’s also much faster. If I had to go through each journal to come up with my own succinct descriptions I simply wouldn’t be able to do this project. It seems reasonable that the journals should speak for themselves in this way.

Which science journals?

I’m working from the Directory of Open Access Journals (DOAJ), and it’s likely this will keep me busy for a while. I’ve covered the journals they’ve filed under “Geology” and am working through categories which are also related to the Earth system and space. I choose journals which use English to describe themselves, so I can avoid cutting and pasting information in a language I don’t understand. The journal must also have a clear description of its focus and scope. Many do, and helpfully label this information “Focus and Scope.” But others have thwarted by best attempts to find a snippet of description that is pithy enough for my images.

Who is this for?

Awareness of open access journals matters for people who are not affiliated with an institution having deep enough pockets to afford journal subscriptions. That could mean people who are members of the general public, who work independently of an institution, or who belong to an organization that simply doesn’t have the cash. It also matters for the researchers and academics whose work is being published, because they might not otherwise consider whether their journal of choice is open access. It matters because institutions can begin to consider open-access publishing in their policy-making, and take steps to encourage it.

This is also for me, because I love the brain rush accompanying the sudden realization that yet another universe of ideas exists, of which I had been completely unaware. It’s like feeling your way around a dark room and encountering an unexpected doorway. Looking at a new journal each day has made me aware of new fields, and allowed me to make connections between seemingly disparate concepts. I sometimes wonder if my little band of followers will become bored if I stray too far from their areas of interest. But I find myself exclaiming, “That’s actually a thing?!” at least once a week, and having that opportunity must appeal to at least a few of them.

Update

After a run of 8 months or so I have deactivated Open Science Daily. I still think it’s a worthy project, but I have other projects right now that need more focus than I was giving them. In the end I evaluated 177 open-access journals for this project, and tweeted about 137 of them.

Categories: Open access, Science and such | Tags: , , , , | Leave a comment

A Guide to Arguing Against Man-Made Climate Change

If you must, then at least do it properly…

The debate about climate change ranges from people arguing that it isn’t happening at all, to those who argue that it is happening, but is entirely natural. The debate can become quite nasty, and part of the reason for this is not that people disagree, but that they disagree without following the rules of scientific discourse. I’m guessing in many cases this is accidental- a kind of cultural unawareness. It’s like making an otherwise innocuous hand gesture while on vacation in a foreign country, only to learn later that it was the rudest possible thing you could have done.

I’ve been annoyed by poor-quality discourse on this topic for some time, and written a few draft blog posts about it, but I’ll defer to the INTJ Teacher for a summary of the key issue (and the main reason I no longer read comment sections after news stories about climate change).

critical thinking2

So now that you know the problem in general terms, let’s talk specifics.

Dismissing the data

First of all, if you’re going to make claims that the data about climate change are problematic in some way, then you should know that there is no one data set. There are thousands of data sets worked on by thousands of people.

Some people seem to think that the whole matter rests on the “hockey stick” diagram of Michael Mann, Raymond Bradley, and Malcolm Hughes published in 1999. (You can download the paper as a pdf here.)

Hockey_stick_annotated

Annotated hockey-stick diagram

Briefly, this was an exercise in solving two kinds of problems: (1) taking temperature information from a variety of sources (e.g., tree rings) and turning it into something that could reasonably be plotted on the same diagram, and (2) figuring out how to take temperature measurements from all over the world and combine them into something representative of climate as a whole. The main reason it became controversial was that it showed a clear increase in temperature since 1850, and that result was not optimal for a certain subset of individuals with a disproportionate amount of political clout. There is a nice description of the debate about the diagram here, including arguments and counter-arguments, along with the relevant citations.

Those arguments are moot at this point, because the PAGES 2k consortium has compiled an enormous amount of data and done the whole project over again, getting essentially the same result (the green line in the figure above).  I can’t help but think that this was an in-your-face moment for Mann et al. (“In your face, Senator Inhofe!  In your face, Rep. Barton!  How d’ya like them proxies?!”)

Despite these results, if you still want to argue that the data are bad, you will need to do the following:

  • Specify which data set you are referring to. Usually this takes the form of a citation to the journal article where the data were first published.
  • Specify what is wrong with it. Was the equipment malfunctioning? Was the wrong thing being measured? Was there something in particular wrong with the analysis?
  • Assuming you are correct about that particular data set, explain why problems with that one data set can be used to dismiss conclusions from all of the other data sets. This will mean familiarizing yourself with the other data and the relevant arguments (although if you are arguing against them you would presumably have done this already).

Things that are not acceptable:

  • Attacks against the researchers. It is irrelevant whether the researchers are jerks, or whether you think they’ve been paid off. What matters are the data. If you can’t supply the necessary information, you have only conjecture.
  • Backing up your argument with someone else’s expert opinion (usually in the form of a url) if that opinion does not cover the points in the first list. It is discourteous to expect the person you are arguing with to hunt down the data backing someone else’s opinion in order to piece together your argument.
  • Arguing from the assumption that man-made climate change isn’t happening. If that’s your starting point, your arguments will tend to involve dismissing data not because there are concrete reasons to do so, but because based on your assumption, they can’t be true. This may be personally satisfying, and ring true to you, but it lacks intellectual integrity. If your argument is any good, that assumption won’t be necessary.

Climate models and uncertainty

It is a common misconception that uncertainty in the context of climate models means “we just don’t know.” Uncertainty is an actual number or envelope of values that everyone is expected to report. It describes the range of possibilities around a particular most likely outcome, and it can be very large or very small.

If you plan to dismiss model results on the basis of uncertainty, you will need to demonstrate that the uncertainty is too large to make the model useful. In cases where the envelope of uncertainty is greater than short-term variations, it may still be the case that long-term changes are much larger than the uncertainty.

Another misconception is that climate models are designed to show climate change in the same way that a baking soda and vinegar volcano is designed to demonstrate what a volcano is. Climate models take what we know of the physics and chemistry of the atmosphere, and add in information like how the winds blow and how the sun heats the Earth. Then we dump in a bunch of CO2 (mathematically speaking) and see what happens. In other words, models specify mechanisms not outcomes. They are actually the reverse of the baking soda and vinegar volcano.

The mathematical equations in a model must often be solved by approximation techniques (which are not at all ad hoc, despite how that sounds), and simplified in some ways so computers can actually complete the calculations in a reasonable timeframe. However, I would argue that they are the most transparent way possible to discuss how the climate might change. They involve putting all our cards on the table and showing our best possible understanding of what’s going on, because it’s got to be in writing (i.e., computer code).

The models aren’t top secret. If you really want to know what’s in them, someone will be able to point you to the code. If the someone is very accommodating (and they often are if you’re not being belligerent or simply trying to waste their time) they might explain some of it to you. But whether or not they do that effectively is irrelevant, because if you’re going to make claims about the models, it’s your obligation to make sure you know what you’re talking about.

If climate changes naturally, then none of the present change is man-made

This is a false dichotomy. No-one is arguing that nature isn’t involved in the usual ways. What they are saying is that the usual ways don’t do all of what we’re seeing now.

A simple way to think about it is as a shape-matching exercise. We would expect that if some trigger in nature is causing the climate to change, then a graph of the temperature change should resemble that of the triggering mechanism. The IPCC has done a nice job of making this comparison easy. In the image below I’ve marked up one of their figures from the Fifth Assessment Report in the way I usually do when I’m researching something. Panel a shows the temperature record (in black), and the panels below it show the changes in temperature attributable to different causes. In the upper right I’ve taken panels b through e and squashed them until they are on the same scale as panel a.

 

IPCC comparison

Annotated shape-matching exercise

A common argument against man-made climate change is to say the sunspot cycles are to blame. You can see the temperature variations that result from these cycles in panel b, and again at the top right. While there are small scale fluctuations in a, it is quite evident that the shape of the effects of sunspot cycles cannot account for the shape of the temperature record, either in terms of having an upward trend, or in terms of the timescale of the temperature change in a. Even if you added in volcanoes (panel c), and the El Niño/ La Niña cycles (panel d), you couldn’t make the trend that appears in a.

The only graph with a similar shape is the one that shows the temperature variations we would expect from adding CO2 and aerosols at the rate humans have been doing it (panel e). The red line in panel a is what you get if you add together b through e. It doesn’t have as much variation as the black line, meaning there are still other things at play, but it does capture the over-all trends.

You needn’t rely on someone else’s complex mathematical analysis to do this. This is something you can do with your own eyeballs and commonsense-o-meter. You may still be inclined to argue that all of these graphs are made up out of thin air, but if you have a look at the many different studies involved (you can do this by reading the chapter in the IPCC report and looking at the citations), you should realize that it’s a pretty lame argument to dismiss all of them out of hand.

But if you are undeterred by said lameness, at that point anyone interested in a serious conversation is going to decide that it isn’t worth their time debating with you, because you’ve already decided that any evidence contrary to your point of view must be wrong. Nothing they can tell you or show you will make a difference, ergo the conversation is pointless. You will appear to be impervious to reason which, incidentally, will be assumed to be the case for your opinions on other matters as well, whether that impression is deserved or not. (“It’s not worth arguing with Jim… if he has an idea in his head, he won’t change his mind no matter what you tell him. He would stand under a blue sky and tell you it’s pink.”)

Scientists are paid off to say climate change is man-made

This argument is quite irrelevant given that the data are what matter, but I think part of this argument might be related to another misconception, so I’m going to address it anyway. It is true that there are millions of dollars spent on climate research grants, but this isn’t pocket money for scientists. To get a grant researchers must justify the amount of money they are asking for in terms of things like lab expenses, necessary travel, and the like. Often their salaries don’t even come into the picture because they are paid by employers, not grants. It is more likely they will be paying grad students and post docs than themselves. When they do apply for funding that will cover their own salaries, that salary must be justifiable in the context of what others in similar positions get paid. In many cases this is a matter of public record, so you can go look up the numbers for yourself.

Most research being done on climate change is funded by government grants. A very few scientists have funding from private donors (though there isn’t nearly as much money as for petroleum-related research), but there is a big check on what influence those donors can have. Research must still go through review to be published. Even if biased research did make it through review, scientists on grants are highly incentivized to pick it apart because that can be an argument for additional grants to further their own research. Getting a grant is a matter of professional survival, so competition for research grants is intense.

In conclusion

There is only one way to make arguments against man-made climate change, and that is to address data and conclusions honestly and appropriately. It may feel good to add your two cents, but if your comments amount to ad hominem attacks or generalizations so broad as to be silly, you shouldn’t expect a good response. You’ve just made the equivalent of a very rude hand gesture to people who value thoughtful and well-informed discourse.

This all seems obvious to me, and I’ve struggled to understand people who argue in a way that I can only describe as dishonest.  But maybe psychology is a factor.  The climate-change deniers need only suggest that scientists are making things up. People don’t want to feel that they’ve been fooled, and most don’t have the background to easily check such claims, so it feels much safer to settle into uninformed skepticism.

Categories: Learning strategies, Science and such, Teaching strategies | Tags: , , , | 3 Comments

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