I think by the end of this post, you won’t think of your editorial filter in quite the way you did when you woke up this morning.
The metaphor of a filter has informed our thinking about information ever since Alvin Toffler popularized the concept of “information overload” in the 1970s. We scholarly publishing types take filtering very seriously. Journals filter out the dross, and editors filter out errors. Our pages are as high-quality and error-free as possible. For editors who eliminate errors and reject unwanted papers, filtering is a private, one-time, reductive process — we confidentially reduce the amount of information to only allow through the highest quality, eliminating the rest.
The junk is filtered out before the public sees it.
At least that’s how we think about it.
Yet there are changes the networked world introduces to our concept of the filter, and they dance together in interesting ways:
- Everything that’s published in the networked world is just a click away from any other resource.
- In the macrocosm of scholarly publishing, very little is ever really filtered out anymore. Any author with a little bit of persistence can get published and included in major indexing services and online searches.
- Many of the filters no longer eliminate information, but rather (obviously or inadvertently) add information.
- Filtering is no longer a private activity but a public, participatory activity.
In an interesting post by David Weinberger on Joho the Blog, Clay Shirky’s idea that “[i]t’s not information overload, it’s filter failure” is extended to introduce the notion that filters are no longer silent, private, and reductive. Instead, more and more are public, verbose, and increasing the size of what’s filtered.
Take this blog post, for example, which filters information by selecting and contextualizing it, just like a journal in some senses. I scanned a number of blogs and news items over the past few days, but the link above is what I wanted to share with you.
Now, because my blog will ping David’s blog, there will be a pingback. Many systems will register that pingback, and it’s potentially important. I filtered out a host of things I didn’t think you’d care about, but by choosing one, I have increased its reach and connectivity. I’m no longer isolated from it. Nor are other filters, and they know our linkage now. When Google indexes this site and David’s, it will use the link from here to Joho the Blog to help rank David’s blog as authoritative. You may add a comment to this post. We may debate the merits. This type of interactive filtering in plain sight of the community and the network only adds more information to David’s original post and to the Scholarly Kitchen as a filter. In fact, the more we debate in the spirit of getting the filter right, the larger the resulting information context around this single linkage — new words, new links, new ideas.
When filtering was private and isolated around the single chunk (the article), this didn’t happen unless the editor knew it was happening. Now, it happens without us realizing it, and the filters in the network concatenate it all rapidly into new modifications to be applied immediately.
The filter doesn’t work the same way it used to.
In the networked information space, filtering can add information in new ways. Google filters to the top of its rankings the most authoritative sites for a particular search query. Your contribution of the search term adds information to Google, driving not only its search filters but also its advertising system, its zeitgeist, its auto-suggest, its analytics, and other systems at Google and beyond. Your attempt to filter the Web through search added information to it. Google and others know how to turn filter use and refinement into ongoing business advantages.
Filtering is a dynamic system in the networked world.
This is a fundamentally different filtering system than the ones we’re accustomed to. And it consumes things in a way that shows how porous our traditional editorial filters are, even when we think they’re tight.
Our coarse, article-level filters aren’t suited to the current filtering environment. Why? Because we don’t apply the only filters, the fastest filters, or the finest filters. By comparison, our filters are light, slow, and non-recursive.
With coarse editorial filtration in an information world of abundance, it’s clear that traditional filters are potentially minor and brief impediments. And now we get to why the macrocosm of lots of papers matters more than it used to.
Many journals have studied what happens to rejected papers, and — no surprise — find that rejected papers usually get published somewhere, in some form. With more author-pays publishing, what used to be the small chance of getting published in a journal has probably reversed, and now there’s only a small chance that a slightly persistent author won’t get published in a journal.
So, while a publisher may be proud of its local filter — a journal’s article rejection rate, for instance — the fact is that the ecosystem allows for nearly universal publication. And the ecosystem is now linked and networked, everything just one click away.
Of course, your filter keeps those bad articles out of your journal, so you can rest easy. Your brand isn’t contributing to the prominence of bad articles elsewhere.
Really? Or does your filter’s relatively wide pores inadvertently let through network amplifiers?
Let’s say you just accepted a really good manuscript that cites a paper you rejected, even one that went way down the food chain, from your perspective. Lo and behold, the reference links to the paper which you (and maybe many others) rejected. A citation service makes sure the link works well. Suddenly, the rejected paper and its journal are more authoritative because your good journal threw it a reference. Your filtering process threw off a spark that lit up part of the network. You just increased another journal’s authority in Google. Your filter wasn’t fine enough to catch this loan of credibility.
Your filter is tuned to papers, not to the network. If it were tuned to the network, you might have rejected that reference, knowing its effects on a paper you rejected.
In the old days, this citation would have meant you’d increased the impact factor of that other journal by the tiniest amount. That effect was slow to be felt, and isolated to one measure. Now, the effect happens instantaneously, and it gets networked. It most likely stays in circulation for longer than an impact factor’s two-year window, and the link to the other journal will persist.
This is just one example of ways what we call “filtering” now extends information instead of reducing it. In the networked digital environment, information links with other information at tiny points we don’t currently really deal with. Is the article good? We’ll accept it. Is each reference worth allowing into the information expansion machine? That’s a new question.
And think about how often the most competitive journals cite each other. Are they are just SEO-ing each other, swapping context and brand authority in the network at a fairly high rate? They may compete for papers, but are they really competing in the network? If one were smart, it would prohibit citations to the other, slowly depriving it of borrowed authority, leaving it to fend for itself in the network, isolating it.
It’s the opposite of the citation-packing scandals of a decade or more ago. Instead of packing your journal with self-citations, you want to eliminate citations to your competitors.
By focusing on the power links have in the information economy, filtering (as in “eliminating junk”) becomes a less clearly effective act in scholarly publishing, which focuses on the articles, not the links or comments or other network drivers. We might want to do more granular filtering, realizing that legitimacy and prominence aren’t accomplished solely (or even primarily) through brands, impact factors, article selections, and reputations.
The papers we once rejected now have a back door, passing through our coarse article-centric filters and straight into networked authority systems, networked linking systems, and the myriad filtering systems (news reports, blogs, society sites, tweets) that actually expand them. Instead of small effects, the network amplifies and extends the effects of these traditional points of borrowed legitimacy while introducing a whole range of new ones.
Do you think about filtering differently now?