Get Me Off Your Fucking Mailing List [pdf]
scs.stanford.edu
scs.stanford.edu
Essentially, predatory journals spam scientists, seeking to publish their paper for a small fee. Someone wrote this in 2005 as a joke response to spammy conference invites, then someone else more recently sent this to one of those predatory journals.
>After receiving a spam email from the International Journal of Advanced Computer Technology, Dr. Peter Vamplew of Federation University Australia’s School of Engineering and Information Technology sent the anti-spam article as a reply to the spam email without any other message, expecting that they might open it and read it, but not that it would be considered for publication.
>To his surprise, the journal accepted the paper and sent him an acceptance email that had two PDF attachments. One was a formal statement of acceptance and the second was the reviewer report.
>It’s clear from examining the reviewer report that the same filled-out form is used for most or all submissions. Certainly, no peer review was completed despite the journal’s claim to be a peer reviewed journal. The acceptance indicates that the next step for Associate Professor Vamplew is to wire USD $150 to the bank account of Tej Pal Singh, and the paper will be published, but I don’t think he’ll be doing that.
Most of them stand out as obvious (especially when they spam me based on a journal article that wanted names formatted like "J. Triplett"). But sometimes they have almost enough believability that I could imagine someone not familiar with this type of scam falling for it. Some of them stand up to a quick search, and someone seeing the journal title and CFP, not doing the research on it, sending a draft ("spray and pray"), and following along with the process and any fees. (Some journals charge substantial fees as well, sometimes by the page, with extra for diagrams.)
The mails often follow the usual tactics of playing up the recipient's status. And any university IT department would tell you that students and professors are not by any means immune to scams. When one "success" earns hundreds in fees, it wouldn't take a significant success rate to make this scam profitable.
For the graphed data itself, I suspect people do tend to pay more attention to the Y axis, and more specifically to the extremes; the results in most papers tend to talk about those extremes (with the exception of the rare graph that highlights consistency across a range of results). Given that, it makes sense to check the scale for "how high" or "how low" first, and then check "by varying what".