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Archive for the ‘mere empirics’ Category

new ways to measure movements via hyper network sampling

Rory, from the home office in South Bend, sends me links to new social movement research. A major question in social movement research is how you measure contentious politics. A lot of our sources are notoriously incomplete, such as media accounts. Kriage Bayerln, Peter Barwis, Bryant Crubaugh, and Cole Carnesecca use hypernetwork sampling (asking a random sample of people to list their social ties) to attack this issue. From Sociological Methods and Research:

The National Study of Protest Events (NSPE) employed hypernetwork sampling to generate the first-ever nationally representative sample of protest events. Nearly complete information about various event characteristics was collected from participants in 1,037 unique protests across the United States in 2010 to 2011. The first part of this article reviews extant methodologies in protest-event research and discusses how the NSPE overcomes their recognized limitations. Next, we detail how the NSPE was conducted and present descriptive statistics for a number of important event characteristics. The hypernetwork sample is then compared to newspaper reports of protests. As expected, we find many differences in the types of events these sources capture. At the same time, the overall number and magnitude of the differences are likely to be surprising. By contrast, little variation is observed in how protesters and journalists described features of the same events. NSPE data have many potential applications in the field of contentious politics and social movements, and several possibilities for future research are outlined.

Readers in social network analysis and organization studies will recognize the importance of this technique. As long as you can sample people, you can sample social ties and the adjust the sample for repetition. Peter Marsden used this technique to sample organizational networks. In movements research, my hybrids paper used the technique to sample orgs that were involved in movement mobilization. It’s great to see this technique expand to sample large samples of events.See Bayerlin’s research project website for more. Recommended.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street 

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Written by fabiorojas

October 31, 2016 at 1:34 am

the mind blowing achievement of john hattie – or, we know how to run schools

We often act as if running a school is a mysterious thing. It’s not. There have been thousands of studies looking at every sort of education policy. John Hattie is an educational researcher in Australia who took the time to collect data from thousands of studies and do a meta-meta analysis to figure out what works.

He has a number of books and articles that summarize his findings. Below, I have included a diagram where he standardizes the effects of 195 factors that might affect achievement and ranks them. Major take home points. Here is what predicts achievement in a big way:

  • Prior performance – by far, the biggest predictor of future achievements are estimates of past work (#1 teacher assessment, #3 self reported grades).
  • Process oriented learning (“Piagetian programs” – don’t focus on outcomes, but on how you get the outcome – #4)
  • Teacher practices aimed at individual students – such as intervening directly disabled pupils (#10, #11), micro-teaching (e.g., one on one interaction with students – #9),  and integrating classroom discussion (#10).

What clearly has a negative effect?

  • Home corporal punishment (#193)
  • Television watching (#192)
  • Summer vacation (#190)
  • Student depression (#195)

What has surprisingly small effects (defined as about .1 or less)?

  • School type – being in a charter school, a single sex school, or learning at a distance (all have nearly zero effects)
  • Mentoring
  • Student diversity
  • Teacher credentials

In other words, the baseline is student ability, which determines who well they do. But you can also get big effects through hands on, processed based, and interactive learning. You should avoid disruptive things, like vacations or television, and the school and teacher credentials don’t get you much.

Thank you, John Hattie.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

Hattie rank below:

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Written by fabiorojas

September 12, 2016 at 12:01 am

did bill clinton accelerate black mass incarceration? yes, but he did put a bunch of white people in prison to even it out

cpus_race_national

Pam Oliver has a fascinating post that empirically investigates incarceration trends during Clinton 1 era (1993-2001). It’s an impressive post. Professor Oliver pulls up a lot of data on overall incarceration rates and breaks it down by race. You should read it yourself, but here is my summary, diagrams are from her article:

  • Imprisonment rates, overall, kept on increasing during the entire Clinton 1 presidency.
  • By race, Black imprisonment rates increased till about 2000 and then plateaued. It started at 75/100,000 and then peaked around 200 per 100,000 and then stabilized. There are huge increases, in rates, for Whites, Hispanics, and Native Americans. Asian rates seem to be stable.
  • The story of racial disparity is a bit more complex. Roughly speaking, the Blackness of the prison population peaked around 1995 (see below). Then the Black/White ratio in prisons began to decline.

cpus_blackdisp_national

My interpretation. First, you have to distinguish between between absolute and relative effects. To be blunt, Black mass incarceration in absolute terms unequivocally increased during the Clinton 1 years. Period. Perhaps the only qualifier is that it eventually stabilized, but the Black imprisonment rate never declined or even remotely went back to the levels of the 1980s or early 1990s. Mass incarceration was built in the 1980s and 1990s and it was here to stay.

The real question is why it stabilized. One hypothesis is that it was a policy effect. Perhaps in the late-1990s, there were policy changed that took effect circa 2000. A second hypothesis is that the prison system became saturated and there weren’t any more people to imprison from that population. Professor Oliver’s data are not enough to settle the question.

Second, the real story is in relative rates. Imprisonment became a much more equal system in the 1990s. In other words, prison shifted from being a Black institution to more of an all American institution. My hypothesis is that the drug war machine simply reached its limit in imprisoning Black and expanded by targeted low income white.

In this data, the American prison system appears as a hungry beast, ruthlessly scooping up low SES populations one at a time. After being built in the 1950s and 1960s by liberal reformers, the American justice system now had the power to quickly and swiftly punish people. In the 1970s and 1980s, Republican and Democratic administrations turned this machine on urban blacks and went unstopped until the early 2000s. The machine then turned to poor whites in the 1990s and a similar machine was built to imprison and deport Mexican and Central American migrants.

Francis Fukuyama wrote that we reached the end of history because liberal capitalism won over its socialist and fascist competitors. The sad truth is that the history must continue and the next chapter will be the struggle to liberate the world’s people from predatory prison states.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

Written by fabiorojas

September 7, 2016 at 12:18 am

trump symposium iii: social science and trump

In this third installment of the Trump symposium, I want to talk about how social scientists should think about Trump. Let’s start with prediction – who foresaw Trump? We need to make a distinction.

So what should a social scientist do?

  • Start with the following mantra: Social science is about trends and averages, rarely about specific cases. If an outsider becomes a major party nominee once, then you can cling to the old theory. If you get three Trumps in a row, then it’s time to dump the Party Decides model, unless, of course, you see the party openly embrace Trump and he becomes the new establishment.
  • Feel confident: One crazy case doesn’t mean that you dump all results. For example, polling still worked pretty well. Polls showed a Trump rise and, lo and behold, Trump won the nomination. Also, polls are in line with basic models of presidential elections where economic trends set the baseline. The economy is ok, which means the incumbent party has an advantage. Not surprisingly, polls show the Democratic nominee doing well.
  • Special cases: Given that most things in this election are “normal,” it’s ok to make a special argument about an unusual event. Here, I’d say that Trump broke the “Party Decides” model because he is an exceptionally rare candidate who doesn’t need parties. Normally, political parties wield power because politicians don’t have money or name recognition. In contrast, Trump has tons of money and a great media presence. He is a rare candidate who can just bypass the whole system, especially when other candidates are weak.

What does the future hold? Some folks have been raising the alarms about a possible Trump win. So far, there is little data to back it up. In the rolling Real Clear Politics average of polls, Trump is consistently behind. In state polls, he is behind. He has no money. He has not deployed a “ground game.”In fact, the RCP average has had Clinton 2 ahead of Trump every single day since October with the exception of the GOP convention and about two of the worst days of the Democratic campaign. Is it possible that Trump will be rescued by a sudden wave of support from White voters? Maybe, but we haven’t seen any movement in this direction. A betting person would bet against Trump.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

Written by fabiorojas

September 1, 2016 at 12:44 am

slave names no longer forgotten

The Virginia Historical Society has a website that brings together many documents from the antebellum period of American history so that you can search for the names of African Americans who might otherwise be lost to history. From the website:

This database is the latest step by the Virginia Historical Society to increase access to its varied collections relating to Virginians of African descent. Since its founding in 1831, the VHS has collected unpublished manuscripts, a collection that now numbers more than 8 million processed items.

Within these documents are numerous accounts that collectively help tell the stories of African Americans who have lived in the state over the centuries. Our first effort to improve access to these stories came in 1995 with publication of our Guide to African American Manuscripts. A second edition appeared in 2002, and the online version is continually updated as new sources enter our catalog (http://www.vahistorical.org/aamcvhs/guide_intro.htm).

The next step we envisioned would be to create a database of the names of all the enslaved Virginians that appear in our unpublished documents. Thanks to a generous grant from Dominion Resources and the Dominion Foundation in January 2011, we launched the project that has resulted in this online resource. Named Unknown No Longer, the database seeks to lift from the obscurity of unpublished historical records as much biographical detail as remains of the enslaved Virginians named in those documents. In some cases there may only be a name on a list; in others more details survive, including family relationships, occupations, and life dates.

Check it out.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

 

Written by fabiorojas

June 24, 2016 at 12:07 am

agent based models in sociology, circa 2016

A few days ago, we had a discussion about the different meanings of the word “computational sociology.” A commenter wrote the following:

Are agent based models/simulations a dead end? Are smart people still using that technique? Have there been any important results? I didn’t realize it peaked in the 1980s.

I’m a current doctoral student considering pursuing ABM, but if it’s a dead end then maybe not.

I think that olderwoman’s response is on target. There is nothing out of style about ABM’s, but sociology is mainly a discipline of empiricists. You will find scholars who occasionally to ABMs but no one who ONLY does is very, very rare. Examples of people who have done simulations: Damon Centola, Kathleen Carley, Carter Butts. In my department, I can think of two people who have published simulations (Clem Brooks, Steve Benard, and myself) and those who do methods research often employ simulations. Olderwoman is also correct in that writing simulations helps you develop programming skills that are now required for “big data” work and for industry.

So don’t write an all simulation dissertation, but by all means, if you have good ideas, simulate them!

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

Written by fabiorojas

June 14, 2016 at 12:01 am

twitter’s glass ceiling for women

Twitter Glass Ceiling Image

This diagram compares Twitter users with male and female profiles. Female users are baseline. IRR means “incidence rate ratio.” The quartiles refer to quartiles of users – Q1 Twitter users have very few followers and Q4 users have many followers.. See the paper for study details.

I have a new paper that will be presented at the 10th International Conference on Web and Social Media. This paper, written by Shirin Nilizadeh, Anne Groggel, Peter Lista, Srijita Das, YY Ahn, Apu Kapadia, and myself, documents an important phenomena on social media: there seems to be a “glass ceiling” that penalizes women who strive to be visible on social media.

We took a random sample of 100,000 Twitter users and asked – what is the difference in visibility between those who appear to be male and female in their profile?* Answer, not much – except among those users who have a lot of followers. The nearly identical level of visibility suddenly shifts and those with male profiles have more followers and the difference is significant. Similar results are found using other measures of visibility like retweets and the results hold accounting for user behavior, off line visibility, and other factors.

* There is the subtle point of users who do not present a gender. The paper deals with that. Read it for details.

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($2!!!!)/From Black Power/Party in the Street

Written by fabiorojas

March 30, 2016 at 12:01 am