I finally gave in and created a Twitter account back on November 4 so I could participate in the #votereport project. It reminded me somewhat of the way mobile phone or SMS texting has shaped elections in Africa, starting with the 2000 election in Ghana and continuing on to the more recent 2008 election in Zimbabwe. It also got me thinking about how such democracy-movement techniques could be adapted to global health. Perhaps to introduce some much-needed transparency in pharmaceutical supply chains?
Votereport was a volunteer-led project that called on U.S. voters to characterize their election experience by providing three major pieces of information: where they voted, how long they waited to vote and whether the experience was a good one or a bad one. If yours was a bad experience, then you were supposed to give a brief description why, e.g. mismatch of your name compared to driver’s license records caused an official to doubt your right to vote.
From a technical point of view, we’re talking about structured-data.
I messed up my first attempt at tweeting my own vote but fortunately someone named ZekeSaysSo showed me how to do it: “#votereport. #10019 #good #wait:40 at 6 AM. longest lines I have ever seen at this polling place at this hour.”
Each specific piece of information was preceded by a # sign or hashtag, also known as a pound sign, to make the information more easily sortable by computer.
People like Adrian Holovaty have convinced a lot of us reporters that one major path to a future for journalism lies through structured data. As Holovaty defined it in 2006, structured data is “the type of information that can be sliced-and-diced, in an automated fashion, by computers.”
Holovaty’s breakthrough example in 2005: using the structured data from Chicago crime statistics mashed up with Google maps to automatically generate geographical pictures of a neighborhood’s character. You can see the latest iteration of his efforts at Everyblock.com
The new wrinkle about Votereport, the Ghanian and Zimabwean elections is that “we the people” provided the structured data—in real time with tangible results. Mobile texting plus radio coverage stopped voting irregularities in Ghana in 2000 and prevented Robert Mugabe from being able to fudge electoral results in Zimbabwe earlier this year—although it didn’t stop him from hanging on to power.
Nothing quite so impressive in the U.S. but Votereport did help a number of individuals cast regular ballots instead of provisional ballots after minor misspellings of their name threatened their franchise rights. Because anyone who tweeted #bad and provided information as to why they couldn’t vote was automatically put into contact with an election protection lawyer. In many cases, simple misunderstandings were resolved before the voting booths closed.
See also Ethan Zuckerman’s thoughtful look at the pros and cons of twittering vs. texting elections.
Seems like you could adapt this type of technology to other uses. I’m thinking specifically about the government’s drug-supply chain in Malawi.
Many, many people I talked to complained about how they can’t get the drugs they need for hospitals and clinics from the Malawi government’s Central Medical Stores. Even the taxi drivers in Lilongwe know that a lot of the pharmaceuticals get diverted from the public sector to the private sector—despite periodic purges of the employees involved.
What if every hospital administrator, clinical officer and nurse used their mobile phone to text every encounter they had with Malawi’s CMS, giving information about the number and kind of drugs that were missing? And you compared that to the number and kind of drugs they started off with—many made available through international agreements?
How long would it take before CMS employees retaliated? Could you get enough people to participate so that no one individual would be targeted for retribution?
Just wondering. What do you think?
See also this Slideshare presentation on Twitter for Health by PF Anderson at the University of Michigan.
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