Data: Harder to Anonymise Yourself Than You Might Think

There’s a lot of discussion around a government’s use of metadata at the moment, where instead of looking at the details of your personal data, government surveillance is limited to looking at the data associated with your personal data. In the world of phone calls, instead of taping the actual call, they can see the number you dialled, the call time and its duration, for example. CBS have done a fairly high-level (weekend-suitable) coverage of a Stanford study that quickly revealed a lot more about participants than they would have thought possible from just phone numbers and call times.

But how much can you tell about a person or an organisation without knowing the details? I’d like to show you a brief, but interesting, example. I write fiction and I’ve recently signed up to “The Submission Grinder“, which allows you to track your own submissions and, by crowdsourcing everyone’s success and failures, to also track how certain markets are performing in terms of acceptance, rejection and overall timeliness.

Now, I have access to no-one else’s data but my own (which is all of 5 data points) but I’ll show you how assembling these anonymous data results together allows me to have a fairly good stab at determining organisational structure and, in one case, a serious organisational transformation.

Let’s start by looking at a fairly quick turnover semi-pro magazine, Black Static. It’s a short fiction market with horror theming. Here’s their crowd-sourced submission graph for response times, where rejections are red and acceptances are green. (Sorry, Damien.)

Black Static – Response Time Graph

Black Static has a web submission system and, as you can see, most rejections happen in the first 2-3 weeks. There is then a period where further work goes on. (It’s very important to note that this is a sample generated by those people who are using Submission Grinder, which is a subset of all people submitting to Black Static.) What this looks like, given that it is unlikely that anyone could read a lot 4,000-7,000 manuscripts in detail at a time, is that the editor is skimming the electronic slush pile to determine if it’s worth going to other readers. After this initial 2 week culling, what we are seeing is the result of further reading  so we’d probably guess that the readers’ reviews are being handled as they come in, with some indication that this is one roughly weekly – maybe as a weekend job? It’s hard to say because there’s not much data beyond 21 days so we’re guessing.

Let’s look at Black Static’s sister SF magazine, Interzone, now semi-pro but still very highly regarded.

Interzone – Response Time Graph

Lots more data here! Again, there appears to be a fairly fast initial cut-off mechanism from skimming the web submission slush pile. (And I can back this up with actual data as Interzone rejected one of my stories in 24 hours.) Then there appears to be a two week period where some thinking or reading takes place and then there’s a second round of culling, which may be an editorial meeting or a fast reader assignment. Finally we see two more fortnightly culls as the readers bring back their reviews. I think there’s enough data here to indicate that Interzone’s editorial group consider materials most often every fortnight. Also the acceptances generated by positive reviews appear to be the same quantity as those from the editors – although there’s so little data here we’re really grabbing at tempting looking straws.

Now let’s look at two pro markets, starting with the Magazine of Fantasy & Science Fiction.

Fantasy & Science Fiction – Response Time Graph

This doesn’t have the same initial culling process that the other two had, although it appears that there is a period of 7-14 days when a lot of work has been reviewed and then rejected – we don’t see as much work rejected again until the 35 day mark, when it looks like all reader reviews are back. Notably, there is a large gap between the initial bunch of acceptances (editor says ‘yes’) and then acceptances supported by reviewers. I’m speculating now but I wonder if what we’re seeing between that first and second group of acceptances are reviewers who write back in and say “Don’t bother” quickly, rather than assembling personalised feedback for something that could be salvaged. Either way, the message here is simple. If you survive the first four weeks in F&SF system, then you are much less likely to be rejected and, with any luck, this may translate (worse case) into personal suggestions for improvement.

F&SF has a postal submission system, which makes it far more likely that the underlying work is going to batched in some way, as responses have to go out via mail and doing this in a more organised fashion makes sense. This may explain why this is such a high level of response overall for the first 35 days, as you can’t easily click a button to send a response electronically and there’re a finite number of envelopes any one person wants to prepare on any given day. (I have no idea how right I am but this is what I’m limited to by only observing the metadata.)

Tor.com has a very interesting graph, which I’ll show below.

Tor.com – Response Time Graph

Tor.com pays very well and has an on-line submission system via e-mail. As a result, it is positively besieged with responses and their editorial team recently shut down new submissions for two months while they cleared backlog. What interested me in this data was the fact that the 150 day spike was roughly twice as high as the 90 and 120. Hmm – 90, 120, 150 as dominant spikes. Does that sound like a monthly editors’ meeting to anyone else? By looking at the recency graph (which shows activity relative to today) we can see that there has been an amazing flurry of activity at Tor.com in the past month. Tor.com has a five person editorial team (from their website) with reading and support from two people (plus occasional others).  It’s hard for five people to reach consensus without discussion so that monthly cycle looks about right. But it will take time for 7 people to read all of that workload, which explains the relative silence until 3 months have elapsed.

What about that spike at 150? It could be the end of the initial decisions and the start of “worth another look” pile so let’s see if their web page sheds any light on it. Aha!

Have you read my story? We reply to everything we’ve finished evaluating, so if you haven’t heard from us, the answer is “probably not.” At this point the vast majority of stories greater than four months old are in our second-look pile, and we respond to almost everything within seven months.

I also wonder if we are seeing previous data where it was taking longer to get decisions made – whether we are seeing two different time management strategies of Tor.com at the same time, being the 90+120 version as well as the 150 version. Looking at the website again.

Response times have improved quite a bit with the expansion of our first reader team (emphasis mine), and we now respond to the vast majority of stories within three months. But all of the stories they like must then be read by the senior editorial staff, who are all full-time editors with a lot on our plates.

So, yes, the size of Tor.com’s slush pile and the number of editors that must agree basically mean that people are putting time aside to make these decisions, now aiming at 90 days, with a bit of spillover. It looks like we are seeing two regimes at once.

All of this information is completely anonymous in terms of the stories, the authors and any actual submission or acceptance patterns that could relate data together. But, by looking at this metadata on the actual submissions, we can now start to get an understanding of the internal operations of an organisation, which in some cases we can then verify with publicly held information.

Now think about all the people you’ve phoned, the length of time that you called them and what could be inferred about your personal organisation from those facts alone. Have a good night’s sleep!