Chris Blattman posts this nice Wordle based on the articles in a course he’s teaching.
Which makes me wonder if someone’s build a tool to generate a Wordle based on the web pages you’ve visited during a period.
Gosh. 50 Million isn’t that big. These are only those who made it that far. Sobering.
The original version is interactive and other wise cool beans.
Did you know that you can purify water by putting it in a bottle and letting it sit out in the sun for a few days? Me either. This method is called SODIS.
Katja Grace mentions that in a posting, which appears to have been triggered by an essay by Ker Than at the National Geographic. Who in turn was responding to prerelease PR for an article in PLoS Medicine.
A lot of misery and death comes of infectious agents picked up from the lousy water supply most humans draw upon. So this looks great. A low cost treatment for a widespread and aweful problem. All that’s left is to solve the coordination problem, e.g. getting the word out and changing behaviors.
That puts the problem into the same class as seat belts, moderate exercise, getting a will, buying life insurance, setting aside a few weeks of emergency supplies. Which is to say: it is a very hard social engineering problem.
The article is not about the hard social engineering, it skips over that. The article reports on a clinical trail intended to capture the Holy Grail of medical research: evidence of efficacy of the treatment. Sadly the study did not capture a statistically significant improvement in the incidence of child diarrhea between the villages where they applied intervened and those in the control group.
The article concludes: “Despite an extensive SODIS promotion campaign we found only moderate compliance with the intervention and no strong evidence for a substantive reduction in diarrhoea among children.” Unsurprisingly the authors are fans of evidence based medicine and so they goto write: “better evidence of how the well-established laboratory efficacy of this home-based water treatment method translates into field effectiveness under various cultural settings and intervention intensities.” Which is fine but kind of misses the point. That demands a end point, i.e. evidence of effective interventions, but first and foremost what’s required is that experts in effective social engineering be brought to the table.
It is hard to convince people to adopt new behaviors, particularly those that require immediate contributions and who’s benefit is statistical and distant. It has taken for ever to get people to wear seat belts, or adopt baby car seats, etc. etc. I am reminded of something I read years ago about how slowly the plow spread across the planet. I’m reminded of the experiment contrasting two campaigns to encourage testing for STD, where no significant difference was found between using fear v.s. rational arguments; but what did work was clearly telling people were the clinic was located. I’m reminded of how hard it is to get a work group to actually utilize a new productivity tool (a wiki, a group email list, a bug tracking system). This stuff is hard.
The vocabulary of health practitioners isn’t much help. Compliance? Intervention intensities?
Insta-theories about why the villagers didn’t adopt this technique are fun, just as long as you don’t get too wedded to any given insta-theory. What caught my attention in reading the Katja’s posting was how it had one insta-theory, which appears to have been gin’d up by one of the twelve authors when on the phone with Ker Than. It’s a fine insta-theory; but I had no trouble coming up with a dozen more. Their insta-theory was that the practice of setting you water out in the sun isn’t fashionable and so the villagers where embarrassed to seen doing it (in econo-legitmacy-speak we say “signalling”). Noting that during the study the researchers lost track of more that 10% of the households due to political unrest … well … I smell projection in that insta-theory.
Like I said this stuff is hard. People always try to skip the hard social engineering step; and then they make up insta-theories for why it didn’t work out.
The latest video from Etsy’s wonderful series Handmade Portraits of videos about selected artists who sell on Etsy. I’m quite amused that the very nice article in the Storque which complements the video includes a link to a random number generator. Note there is a contest to win one of Mimi’s pieces, see the article for details.
Oh poor poor pitiful me! I’ve got to get the bushel of peaches into the freezer.
Antonio notices the curious disconnect between Moore’s law and cloud pricing. I don’t know that I have anything more to say today than I said in my previous two postings (1, 2). What’s clear is that these vendors do not feel any as much pricing pressure as a naive analysis would suggest. Apparently the switching costs are too high and the incentives too weak. My original presumption was that these new operation systems would provide access to unique resources; i.e. Amazon’s distribution and shoppers, Google’s web caches, knowledge bases, and searchers. Along with what ever sticky unique APIs they could throw up. Currently only Facebook is doing much with their unique assets.
I guess the question remains. Is EC2’s pricing telling us something deep about the pricing power, or are they caught in a classic boiling the frog situation when the signals the market is giving them are too weak to trigger a reaction. Hirshman tells a story about how the US automakers failed to hear customer quality complaints because the complainers just rotated around between them; presumably hearing such signals would be even harder if the market was growing as fast as the cloud markets are.
What I didn’t comprehend until recently is how much these systems are about impulse. Not just that you can build something impulsively, but also that you gains some assurance that you will be able to reap the value to be had when the unpredictable impulse of usage hits. The larger the proportion of activity which is slotted into either of those categories the more these systems dominate. I’d guess that proportion is over 80% of all activity.
I wonder if switching (incumbered as it is with huge costs of many kinds for multi-homing) is actually deeply at odds with impulsive. Certainly when you build something rapidly, on impulse, you don’t front load a large prep to enable later switching. And, certainly when your between load spikes there is only a weak incentive to reduce the cost that will be incurred when that spike happens, if it every does.
I’ve been musing recently that their are, presumably, a class of business models that work because they catch passing load spikes. Businesses designed to have very low run rates until the earthquake, blizzard, hurricane, power grid failure, commodity price spike, fad, conference, passes thru. Such are naturally complementary to the cloud computers. It would be fun to be inside Amazon, where it might be possible to collect a large set of examples.
But high minded theories aside – I think it’s mostly switching costs are much higher than people want to admit. I can’t even get around to updating all the damn blog software.
I’m starting another blog: Offering Load about Erlang. I have a mess of notes about Erlang. So it should provide a place to put them. But I’m hoping that it will help me to pull together a more complete feel or Erlang. I keep diving into this or that aspect of the language and then before I feel I’ve hit bottom I wander off.
Maybe if I post some of this in public other people will comment to point out how deluded I am. For example is it true that ampersand is unused in Erlang?
Playing with Riak is what reminded me that wanted to do this.
Boy yesterday was discombobulating. Right on the heels of the Face book acquisition of FreindFeed bringing into focus the discomforting thought that maybe I don’t have a clue what the word social means we have the acquisition of Spring Source by VMWare (aka EMC, aka VCE).
Spring Source has always seemed to me to be slightly conflicted about their exit plans: a bit of both built to flip and built to last. And reading the tea leaves provided by their acquisitions didn’t seem to clarify that. But clearly I wasn’t thinking about who might want to buy them. Early on I thought Microsoft, but over time it became clear that Microsoft that was unlikely. In retrospect I guess it’s obvious that somebody who aspires to be a player in the cloud computing platform space would be a likely buyer.
Aspires is probably the key word there. After Amazon, and possibly Google, everybody else has only aspirations at this point. An opinion that reflects my presumption that this is not a competition that’s well framed in the mindset of enterprise computing.
But the mix of proprietary and open that’s playing out in the cloud data centers needs more thought. Can VMWare capture that platform hub? Who are the significant other players aspiring to own the cloud computing platform. EMC/VMWare/Cisco, IBM and Microsoft obviously, but are there others? Are Redhat or Canonical acquisition candidates now?
Again these are very raw thoughts. I remain confused.
I have always thought that Friend Feed was built to flip, and further I’d presumed that when imagining who’d acquire them they always thought it would be Google. But over time, no doubt, Facebook came to seem just as likely. So, whatever.
But, I’m stewing a hypothesis, call it: Google doesn’t get social. Google’s not buying Friendfeed is another small potato into that pot as are Talk, Wave, Docs, Profile, iGoogle…
Google and Facebook grew from distinct social cultures and their approaches reflect what social means for those cultures. Facebook’s, the social activities of ivy league college freshman, was a better starting point than Google’s – the collaborative open source graduate-school development model.
I’m not deeply committed to this theory. But there something different emerging in the Facebook, Elgg, and Linked-in model of sites – and maybe Twitter and Friendfeed as well. It is a thing that’s different from what you get in the forum or bboard model. And it appears to be different from what firms like Ning or Acquia are chasing with their group forming (Reed’s law) model.
Needs more thought.
No doubt most of my readers have columns in the New York Times, and so they are in need of a list of rules to follow to help assure their columns are highly impact. I’ve taken a stab and distilling out actionable rule of thumb implied by this old and interesting critique of Bob Herbert’s columns in the New York Times. It has a nice subtitle “The perils of punditry for the powerless“