Hi AoIR: I’m working on a paper right now about Internet filtering in public institutions (project page <http://mappinginfoaccess.org/about>). The tl;dr is that we FOIA’d every public school and library in Alabama asking for, among other things, configurations of filters, lists of whitelisted/blacklisted sites, categories used, etc. Not every institution responded, but a few dozen did. The upshot is I now have a bunch of screenshots (or things that can be screenshotted) of these configurations and I’m trying to figure out how to fit them into the paper. The point of the paper is to provide empirical evidence supporting/consistent with certain theoretical arguments that have been made about knowledge infrastructures and the disunified/multiple quality of the Internet. Much of the paper is, of course, textual, and I’m working on some tables to summarize the data. But the real richness, I think, comes from seeing the screenshots, which forces you to encounter these alien ontologies of what kind of content is worth filtering. (I didn’t want to attach examples, bc I don’t know how the listserv deals with attachments, but if you want to see some examples, check slides 21-34 <http://cl.ly/3G112H1n1C1w> of my Theorizing the Web presentation; the config images are really fascinating) My basic question is: what are some effective strategies you’ve used (or seen used) for working media artifacts, particularly screenshots, into journal articles? In books, I’ve offset images into little boxes as artifacts that interrupt or lay alongside the text, but I’m not sure that works as well in articles. I don’t necessarily need (or want) the images to be the subject of analysis as much as objects for the reader to encounter that support/confirm the analysis. I suspect this also depends on the journal. I plan to submit to some of the major ones in ‘Internet studies,’ but if you have particular journals that would be good homes for this in topic and in format, I’m definitely open to suggestions! Thanks, — Chris Peterson Research Affiliate, MIT Center for Civic Media