Understanding the altmetrics wackaloon

I’ve been entertaining myself in a twitscussion with my good friend @mrgunn, a dyed-in-the-wool altmetrics wackanut obsessive. It was all started because he RT’d a reference to an article by Taylor and Thorisson entitled “Fixing authorship – towards a practical model of contributorship” which includes subsections such as “Authorship broken, needs fixing” and “Inadequate definitions of authorship“.

These were the thrusts of the article that annoyed me since I feel there is this whole area of interest that is based on a footing of disgruntled sand. In short, there IS no problem with authorship that “needs fixing”. This has not been proven by the people advancing this agenda to any believable degree and you see an awful lot of “everyone knows” type of assertion.

Some other headings in the bit are illustrative, let’s start with “Varied authorship conventions across disciplines“. This is true. But it is not a problem. My analogy of the day is different languages spoken by different people. You do not tell someone speaking a language other than that you understand that they are doing it wrong and we all just need to learn Esperanto. What you do is seek a translation. And if you feel like that is not giving you a “true” understanding, by all means, take the time to learn the language with all of its colloquial nuance. Feel free.

Heck, you can even write a guide book. For all the effort these “authorship is broken” wackaloons take to restate the unproven, they could write up a whole heck of a lot of style-guidage.

“….the discipline of Experimental Psychology is heavily driven by Grand Theorye Eleventy approaches. Therefore the intellectualizing and theorizing is of relatively greater importance and the empirical data-making is lesser. The data may reflect only a single, rather simple model for producing it. This is why you see fewer authors, typically just a trainee and a supervisor. Or even single-author papers. In contrast, the more biological disciplines in the Neuroscience umbrella may be more empirical. Credit is based on who showed something first, and who generated the most diverse sets of data, rather than any grand intellectualizing. Consequently, the author lists are long and filled with people who contributed only a little bit of data to each publication….”

Done. Now instead of trying to force a review of a person’s academic contributions into a single unified framework, one can take the entirely easy step of understanding that credit accrues differently across scientific disciplines.

ahhhh, but now we come to the altmetrics wackaloons who are TrueBelievers in the Church of Universal Quantification. They insist that somehow “all measures” can be used to create….what? I suppose a single unified evaluation of academic quality, impact, importance, etc. And actually, they don’t give a rat’s patootie about the relevance, feasibility or impact of their academic endeavor to capture all possible measures of a journal article or a contributing author. It doesn’t matter if the measure they use entails further misrepresentations. All that they care about is that they have a system to work with, data to geek over and eventually papers to write. (some of them wish to make products to sell to the Flock, of course).

This is just basic science, folks. How many of us have veeeeeery thin justifications for our research topics and models? Not me of course, I work on substance abuse…but the rest of y’all “basic” scientists….yeah.

The wackaloon justifications sound hollow and rest on very shifty support because they really don’t care. They’ve landed on a few trite, truthy and pithy points to put in their “Introduction” statements and moved on. Everyone in the field buys them, nods sagely to each other and never. bothers. to. examine. them. further. Because they don’t even care if they believe it themselves, their true motivation is the tactical problem at hand. How to generate the altmetrics data. Perhaps secondarily how to make people pay attention to their data and theories. But as to whether there is any real world problem (i.e., with the conduct of science” to which their stuff applies? Whether it fixes anything? Whether it just substitutes a new set of problems for an old set? Whether the approach presents the same old problems with a new coat of paint?

They don’t care.

I do, however. I care about the conduct of science. I am sympathetic to the underlying ideas of altmetrics as it happens, so far as they criticize the current non-altmetric, the Journal Impact Factor. On that I agree that there is a problem. And let’s face it, I like data. When I land on a PLoS ONE paper, sure, I click on the “metrics” tab. I’m curious.

But make no mistake. Tweets and Fb likes and blog entries and all that crapola just substitute a different “elite” in the indirect judging of paper quality. Manuscripts with topics of sex and drugs will do relatively better than ones with obscure cell lines faked up to do bizarre non-biological shit on the bench. And we’ll just end up with yet more debates about what is “important” for a scientist to contribute. Nothing solved, just more unpleasantness.

Marrying these two topics together we get down to the discussion of the “Author Contribution” statement, increasingly popular with journals. Those of us in the trenches know that these are really little better than the author position. What does it tell us that author #4 in a 7 author paper generated Fig 3 instead of Fig 5? Why do we need to know this? So that the almetrics wackaloons can eventually tot up a score of “cumulative figures published”? Really? This is ridiculous. And it just invites further gaming.

The listed-second, co-equal contribution is an example. Someone dreamed up this as a half-assed workaround to the author-order crediting assumptions. It doesn’t work, as we’ve discussed endlessly on this blog, save to buy off the extra effort of the person listed not-first with worthless currency. So in this glorious future in which the Author Contribution is captured by the altmetrics wackaloons, there will be much gaming of the things that are said on this statement. I’ve already been at least indirectly involved in some discussion of who should be listed for what type of contribution already. It was entirely amiable but it is a sign of the rocky shoals ahead. I foresee a solution that is exactly as imprecise as what the critics are on about already (“all authors made substantial contributions to everything, fuck off”) and we will rapidly return to the same place we are now.

Now, is there harm?

I’d say yes. Fighting over irrelevant indirect indicators of “importance” in science is already a huge problem because it is inevitably trying to fit inherently disparate things into one framework. It is inevitably about prescribing what is “good” and what is “bad” in a rather uniform way. This is exemplified by the very thing these people are trying to criticize, the Journal Impact Factor. It boggles my mind that they cannot see this.

The harms will be similar. Scientists spending their time and effort gaming the metrics instead of figuring out the very fastest and best way to advance science*. Agencies will fund those who are “best” at a new set of measures that have little to do with the scientific goals….or will have to defend themselves when they violate** these new and improved standards. Vice Deans and P&T committees will just have even more to fight over, and more to be sued about when someone is denied tenure and the real reasons*** are being papered over with quantification of metrics. Postdoctoral bakers agonizing over meeting the metrics instead of working on what really matters, “fit” and “excitement”.

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*Which is “publish all the data as quickly as possible” and let the hive/PubMed sort it out.
**see complaints from disgruntled NIH applicants about how they “deserve” grants because their publications are more JIF-awesome or more plentiful then the next person.
***”an asshole that we don’t want in our Dept forever”