Sometimes I just get ideas. From an e-mail I just wrote to a publisher/producer friend in NYC:
"The magazine cooperative is a very simple idea, and grew out of my growing sense of not having the time I need to keep up with all the reading I should be doing. It occurred to me that if you got a bunch of people who went out and subscribed to different magazines, each one could post a summary of that issue's articles online, giving the other members a sense of what was being said in each. If something looked interesting, the other members could always pick up the issue and read it for themselves. Seemed a nice little opportunity for virtual community.
"Then it occurred to me that, with just a bit of programming, you could turn this friendly little service into something much more useful.
"1. Members of the cooperative fill out an e-form before they begin submitting reviews: Age, gender, education level, areas of interest, expertise, profession, politics, sexual orientation, etc.
"2. While each review would include written comments, each review would also be scored: Cover story, editorial, letters, first feature, second feature, etc. Grade for overall quality, significance, whatever. Number grades between 1 and 10.
"Result: As a member of the co-op, my regular reviewing of one (or more) magazine(s) gives me access to a range of reviewers on a number of titles. I can check aggregate scores to see whether people liked this New Yorker better than the previous issue, look inside to see whether there's a must-read article this time. But I can do more, too: By changing my filters, I can look only at the scores and comments provided by gay 35-to-45-year-old men with masters degrees and Republican political leanings who earn in excess of $100k a year. I can look and see who likes a magazine and who doesn't. I can tailor a filter set so that I read only those reviews from like-minded people.
"Cost? A server, some programming, some marketing, incidentals. Your readers provide the content. All you're providing is the bandwidth and a sortable dbase that, given the right software, could offer specific recommendations based on your history of interests or your user profile, a la Amazon.
"Revenues? Ads out the yin-yang. Where would YOU advertise if YOU were a magazine publisher? Where ELSE would you offer subscription discounts?"
(EDITOR'S NOTE: Of course, the SAME system could be used to get coverage of various websites and blogs. dc)