All posts tagged Christian Davenport

Measuring Trends in Human Rights Practices

I wrote a thing for Foreign Policy‘s Democracy Lab on evidence that widely-used data on human rights practices understate the improvements that have occurred around the world in the past few decades:

“It’s Getting Better All The Time”

The idea for the piece came from reading Chris Fariss’s May 2014 article in American Political Science Review and then digging around in the other work he and others have done on the topic. It’s hard to capture the subtleties of a debate as technical as this one in a short piece for a general audience, so if you’re really interested in the subject, I would encourage you to read further. See especially the other relevant papers on Chris’s Publications page and the 2013 article by Anne Marie Clark and Kathryn Sikkink.

In the piece, I report that “some human rights scholars see Fariss’ statistical adjustments as a step in the right direction.” Among others I asked, Christian Davenport wrote to me that he agrees with Fariss about how human rights reporting has evolved over time, and what that implies for measurement of these trends. And Will Moore described Fariss’s estimates in an email as a “dramatic improvement” over previous measures. As it happens, Will is working with Courtenay Conrad on a data set of allegations of torture incidents around the world from specific watchdog groups (see here). Like Chris, Will presumes that the information we see about human rights violations is incomplete, so he encourages researchers to treat available information as a biased sample and use statistical models to better estimate the underlying conditions of concern.

When I asked David Cingranelli, one of the co-creators of what started out at the Cingranelli and Richards (CIRI) data set, for comment, he had this to say (and more, but I’ll just quote this bit here):

I’m not convinced that either the “human rights information paradox” or the “changing standard of accountability” produce a systematic bias in CIRI data. More importantly, the evidence presented by Clark and Sikkink and the arguments made by Chris Fariss do not convince me that there is a better alternative to the CIRI method of data recording that would be less likely to suffer from biases and imprecision. The CIRI method is not perfect, but it provides an optimal trade-off between data precision and transparency of data collection. Statistically advanced indexes (scores) might improve the precision but would for sure significantly reduce the ability of scholars to understand and replicate the data generation process. Overall, the empirical research would suffer from such modifications.

I hope this piece draws wider attention to this debate, which interests me in two ways. The first is the substance: How have human rights practices changed over time? I don’t think Fariss’ findings settle that question in some definitive and permanent way, but they did convince me that the trend in the central tendency over the past 30 or 40 years is probably better than the raw data imply.

The second way this debate interests me is as another example of the profound challenges involved in measuring political behavior. As is the case with violent conflict and other forms of contentious politics, almost every actor at every step in the process of observing human rights practices has an agenda—who doesn’t?—and those agendas shape what information bubbles up, how it gets reported, and how it gets summarized as numeric data. The obvious versions of this are the attempts by violators to hide their actions, but activists and advocates also play important roles in selecting and shaping information about human rights practices. And, of course, there are also technical and practical features of local and global political economies that filter and alter the transmission of this information, including but certainly not limited to language and cultural barriers and access to communications technologies.

This blog post is now about half as long as the piece it’s meant to introduce, so I’ll stop here. If you work in this field or otherwise have insight into these issues and want to weigh in, please leave a comment here or at Democracy Lab.

A Few Suggestions for Social Scientists New to Twitter

Earlier today, one scholar whose work I greatly admire asked another scholar whose work I greatly admire for advice on how to get started on Twitter. I liked Dan’s response, but I thought I’d take Christian’s query as an open invitation to share a few suggestions of my own. So:

Replace the egg with a picture of you. Seriously, don’t even start following people until you’ve done this. It’s not vain; it’s just letting people know that there’s (probably) a real human on the other end, and letting us know something about how you plan to present yourself in this context. Some people can get away with using cartoons or pictures of their pets or kids, but most of us can’t. So, unless you’re trying to make a very specific statement by doing something different, you probably shouldn’t try.

Decide why you’re using Twitter. If your main goal is to use Twitter as a news feed or to follow other peoples’ work, then it’s a really easy tool to use. Just poke around until you find people and organizations that routinely cover the issues that interest you, and follow them. If, however, your goal is to develop a professional audience, then you need to put more thought into what you tweet and retweet, and the rest of my suggestions might be useful.

Pick your niche(s). There are a lot of social scientists on Twitter, and many of them are picky about whom they follow. To make it worth peoples’ while to add you to their feed, pick one or a few of your research interests and focus almost all of your tweets and retweets on them. For example, I’ve tried to limit my tweets to the topics I blog about: democratization, coups, state collapse, forecasting, and a bit of international relations. When I was new to Twitter, I focused especially on democratization and forecasting because those weren’t topics other people were tweeting much about at the time. I think that differentiation made it easier for people to attach an identity to my avatar, and to understand what they would get by following me that they weren’t already getting from the 500 other accounts in their feeds.

Keep the tweet volume low, at least at the start. For a long time, I tried to limit myself to two or three tweets per Twitter session, usually once or twice per day. That made me think carefully about what I tweeted, (hopefully) keeping the quality higher and preventing me from swamping peoples’ feeds, a big turnoff for many.

Don’t just share the news; augment it. If you’re tweeting a news story or journal article or something, use a short quote or comment that crystallizes the story or tells us something about why you think it’s worth reading. In other words, try to add value. I usually lead with the title, then insert the link, then hang the quote or comment at the end, like this:

Fiji’s Failing Democratic Transition http://t.co/RjRhSVSoA0 via @yannistellidis. "Growing funding from China" -> less Aus/NZ leverage

— Jay Ulfelder (@jay_ulfelder) April 12, 2013

But, of course, there are lots of ways to do this. You can also drop the title entirely, like this recent one from Joshua Kucera that got me laughing:

Amid all the excitement I missed @StateDept's Festivus, where it airs its grievances with the rest of the world: http://t.co/KnBlxmYIO1

— Joshua Kucera (@joshuakucera) April 20, 2013

Keep it professional. If you’re thinking of Twitter as an extension of your work, don’t tweet about personal stuff. This is especially important when you’re new to the medium. The occasional reference to your life outside the office can help people feel more connected to you, but please err on the side of reticence. I have chosen not to follow or unfollowed many people because the interesting stuff in their feed was overwhelmed by the personal and trivial (and sometimes just downright gross). At some point, all that jetsam gets in the way of the information I’m actually looking for, so I choose to cut it off.

Related to the previous suggestion, be polite. In theory, this should go without saying, but, hey, this is the Internet. If you’re using Twitter for professional purposes, I think it makes sense to use the same language and demeanor you’d use in the office or at a professional conference. That can include humor and the occasional personal tidbit you’d share in a hallway conversation, but probably not the bar talk, and definitely not the post-conference conversations with your confidantes. It most definitely does not include nastiness or pettiness.

Be generous. Don’t retweet something under your own handle just to troll for RTs. If you want to share something someone else already shared, just pass along his or her tweet. The exception to this rule is when you’re going to add your own comment. Then just be sure to acknowledge the source with a via or h/t (hat tip). If a bunch of people already shared something so you’re not sure whom to credit, the answer is, Don’t share it again.

If you modify someone’s tweet at all before passing it along, use MT. This is a Twitter pet peeve of mine. RT (retweet) should only be used when what follows is a verbatim replication of the original. If you change anything—abbreviate, drop a comma, whatever—use MT (modified tweet) instead.

Finally, know that it’s addictive. I don’t mean fun-and-time-consuming addictive; I mean addictive addictive, like nicotine and booze. Before you dive in, it’s worth considering how that addiction might negatively affect your life and how you plan to deal with it. Just because lots of people do it doesn’t mean it’s good for you. The time you spend on Twitter is time you could have spent doing something else. If that something else is more important and you’re prone to addiction, be careful.