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christakis’ query

Last year, Nicholas Christakis argued that the social sciences were stuck. Rather that fully embrace the massive tidal wave of theory and data from the biological and physical sciences, the social sciences are content to just redo the same analysis over and over. Christakis’ used the example of racial bias. How many social scientists would be truly shocked to find that people have racial biases? If we already know that (and we do, by the way), then why not move on to new problems?

Christakis’ was recently covered in the media for his views and for attending a conference that tries to push this idea. To further promote this view, I would like to introduce Christakis’ Query, which every researcher should ask:

Think about the major question that you are working on and what you think the answer is. Estimate the confidence in your answer. If you already know the answer with more than 50% confidence, then why are you working on it? Why not move on?

Try it out.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($1!!!!)/From Black Power/Party in the Street!! 

Written by fabiorojas

January 27, 2015 at 12:02 am

defending computational ethnography

Earlier this week, I suggested a lot is to be gained by using computational techniques to measure and analyze qualitative materials, such as ethnographic field notes. The intuition is simple. Qualitative research uses, or produces, a lot of text. Normally, we have to rely on the judgment of the researcher. But now, we have tools that can help us measure and sort the materials, so that we have a firmer basis on which to make claims about what our research does and does not say.

The comments raised a few issues. For example, Neal Caren wrote:

 This is like saying that you want your driverless cars to work for Uber while you are sleeping. While it sounds possible, as currently configured neither ethnographic practices nor quantitative text analysis are up to the task.
This is puzzling. No one made this claim. If people believe that computers will do qualitative work by collecting data or developing hypotheses and research strategies, then they are mistaken. I never said that nor did I imply it. Instead, what I did suggest is that computer scientists are making progress on detecting meaning and content and are doing so in ways that would help research map out or measure text. And with any method, the researcher is responsible for providing definitions, defining the unit of analysis and so forth. Just as we don’t expect regression models to work “while you are sleeping,” we don’t expect automated topic models or other techniques to work without a great level of guidance from people. It’s just a tool, not a magic box.
Another comment was meant as a criticism, but actually supports my point. For example, J wrote:
This assumes that field notes are static and once written, go unchanged. But this is not the consensus among ethnographers, as I understand the field. Jonathan van Maanen, for example, says that field notes are meant to be written and re-written constantly, well into the writing stage. And so if this is the case, then an ethnographer can, implicitly or intentionallly, stack the deck (or, in this case, the data) in their favor during rewrites. What is “typical” can be manipulated, even under the guise of computational methods.
Exactly. If we suspect that field notes and memos are changing after each version, we can actually test that hypothesis. What words appear (or co-appear) in each version? Do word combinations with different sentiments or meanings change in each version? I think it would be extremely illuminating to see what each version of an ethnographer’s notes keeps or discards. Normally, this is impossible to observe and, when reported (which is rare), hard to measure. Now, we actually have some tools.
Will computational ethnography be easy or simple? No. But instead of pretending that qualitative research is buried in a sacred and impenetrable fog of meaning, we can actually apply the tools that are now becoming routine in other areas for studying masses of text. It’s a great frontier to be working in. More sociologists should look into it.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($1!!!!)/From Black Power/Party in the Street!! 

Written by fabiorojas

January 23, 2015 at 12:01 am

party in the street: the main idea

For the last eleven years, my friend Michael Heaney and I have conducted a longitudinal study of the American antiwar movement. Starting at the 2004 Republican National Convention protests in New York City, we have been interviewing activists, going to their meetings, and observing their direct actions in order to understand the genesis and evolution of social movements.  We’ve produced a detailed account of our research in a new book called Party in the Street: The Antiwar Movement and the Democratic Party after 9/11. If the production process goes as planned, it should be available in February or early March.

In our book, we focused on how the antiwar movement is shaped by its larger political environment. The argument is that the fortunes of the Democratic party affect the antiwar movement’s mobilization. The peak of the movement occured when the Democratic party did not control either the White House or Congress. The movement demobilized as Democrats gained more control over the Federal government.

We argue that the the demobilization reflects two political identities that are sometimes in tension: the partisan and the activist. When partisan and activist goals converge, the movement grows as it draws in sympathetic partisans. If activism and partisanship demand different things, partisan identities might trump the goals of activist, leading to a decline of the movement. We track these shifting motivations and identities during the Bush and Obama administrations using data from over 10,000 surveys of street protestors, in depth interviews with activists, elected leaders, and rank and file demonstrators, content analysis of political speeches, legislative analysis, and ethnographic observations.

If you are interested in social movements, political parties and social change, please check it out. Over the next month and a half, I will write posts about the writing of the book and the arguments that are offered.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($1!!!!)/From Black Power/Party in the Street!!

Written by fabiorojas

January 6, 2015 at 12:01 am

building computational sociology: from the academic side

Before the holiday, we asked – what should computational sociologists know? In this post, I’ll discuss what sociology programs can do:

  • Hire computational sociologists. Except for one or two cases, computational sociologists have had a very tough time finding jobs in soc programs, especially the PhD programs. That has to change, or else this will be quickly absorbed by CS/informatics. We should have an army of junior level computational faculty but instead the center of gravity is around senior faculty.
  • Offer courses: This is a bit easier to do, but sociology lags behind. Every single sociology program at a serious research university, especially those with enginerring programs should offer undergrad and grad courses.
  • Certificates and minors: Aside from paperwork, this is easy. Hand out credentials for a bundle of soc and CS courses.
  • Hang out: I have learned so much from hanging out with the CS people. It’s amazing.
  • Industry: This deserves its own post, but we need to develop a model for interacting with industry. Right now, sociology’s model is: ignore it if we can, lose good people to industry, and repeat. I’ll offer my own ideas next week about how sociology can fruitfully interact with the for profit sector.

Add your own ideas in the comments.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($1!!!!)/From Black Power/Party in the Street!!

Written by fabiorojas

January 2, 2015 at 5:27 am

urban police puzzle and ethnographic method

A few days ago, we discussed an empirical issue around Goffman’s On the Run ethnography. That work focuses on how police intervention cripples poor Black men. The issue is that other ethnography reports an under policing of poor Black neighborhoods. Earlier, I suggested a voter driven explanation – voters like to see young Black men arrested on drug charges and reward police for it.

Here, I’d like to raise a methodological issue. Goffman’s ethnography is not typical in the sense of studying a field site like a firm or a neighborhood. Rather, the ethnography is a study of a cohort of people. You follow them around. That is different than field site ethnography where you choose a location and focus on the action happening in a space. People come in and out. So it is not surprising that if you stand on a modal street corner in Philly, you won’t see many cops walk by. In contrast, if you follow people who are the target of police, then you will, not surprisingly, see a lot of police.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power 

Written by fabiorojas

September 4, 2014 at 12:01 am

book announcement: party in the street – the antiwar movement and the democratic party after 9/11

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It is my pleasure to announce the forthcoming publication of a book by Michael Heaney and myself. It is called Party in the Street: The Antiwar Movement and the Democratic Party after 9/11. It will be available from Cambridge University Press starting in early 2015.

The book is an in-depth examination of the relationship between the major social movement of the early 2000s and the Democratic Party. We begin with a puzzle. In 2006, the antiwar movement began to decline, a time when the US government escalated the war and at least five years before US combat troops completely left Iraq. Normally, one would expect that an escalation of war and favorable public opinion would lead to heightened  activism. Instead, we see the reverse.

We answer this question with a theory of movement-party intersections – the “Party in the Street.” Inspired by modern intersectionality scholarship, we argue that people embody multiple identities that can reinforce, or undermine, each other. In American politics, people can approach a policy issue as an activist or a partisan. We argue that the antiwar movement demobilized not because of an abrupt change in policy, but because partisan identities trumped movement identities. The demobilization of the antiwar movement was triggered, and concurrent with, Democratic victories in Congress and the White House. When push comes to shove, party politics trumps movement activism.

The book is the culmination of ten years of field work, starting with a survey of antiwar protesters at the Republican National Convention in August 2004. The book examines street protest, public opinion, antiwar legislation, and Iraq war policy to makes its case. If you are interested in American politics, political parties, peace studies, political organizations, or social movements, please check this book out. During the fall, I’ll write a series of posts that will explain the argument in some more detail.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power

let’s hear it for null results

A common, and important, critique of journals is that they don’t want to publish null results. So when I saw a new piece in Socio-Economic Review yesterday reporting essentially null findings, I thought it was worth a shout-out. The article, by economist Stefan Thewissen, is titled, “Is It the Income Distribution or Redistribution That Affects Growth?” (paywalled; email me for a copy). Here’s the abstract:

This study addresses the central question in political economy how the objectives of attaining economic growth and restricting income inequality are related. Thus far few studies explicitly distinguish between effects of income inequality as such and effects of redistributing public interventions to equalize incomes on economic growth. In fact, most studies rely on data that do not make this distinction properly and in which top-coding is applied so that enrichment at the top end of the distribution is not adequately captured. This study aims to contribute using a pooled time-series cross-section design covering 29 countries, using OECD, LIS, and World Top Income data. No robust association between inequality and growth or redistribution and growth is found. Yet there are signs for a positive association between top incomes and growth, although the coefficient is small and a causal interpretation does not seem to be warranted.

Okay, so there’s the “signs for a positive association” caveat. But “the coefficient is small and a causal interpretation does not seem to be warranted” seems pretty close to null to me.

In light of the attention this report from S&P has been getting — e.g. from Krugman today (h/t Dan H.) — all solid findings, null and otherwise, on the inequality-growth relationship warrant publication. Hats off to SER for publishing Thewissen’s.

 

Written by epopp

August 8, 2014 at 4:35 pm

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