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Archive for the ‘mere empirics’ Category

minor puzzle about academic hiring

A small puzzle about academic jobs: If getting “the best” is the true purpose of doing a job search, then why do academic programs stop interviewing after the 3rd person? Why it’s a puzzle: There seems to be an over-supply of PhD with good to excellent qualifications. Many never get called out for interviews.

Example: Let’s say you are a top 10 program about to hire an assistant professor. Then what do you look for? You want a graduate of a top 5 (or top 10, maybe) program with one or more hits in AJS/ASR/SF. Perhaps you want someone with a book contract at a fancy press.

You fly out three people. They all turn you down or they suck. The search stops – but this is odd!! These top 5 programs usually produce more than 3 people with these qualifications. Also, add in the fact that every year the market overlooks some really solid people in previous years. My point is simple – departments fly out 2 or 3 people per year but there are usually more than 2 or 3 qualified people!

The puzzle is even more pronounced for low status programs. Why do they stop at 3 candidates when there might be dozens of people with decent publication records who are unclaimed on the market or seriously under-placed? While a top program can wait for the next batch of job market stars, low status programs routinely pass up good people every year.

I have a few explanations, none of which are great. The first is cost – maybe deans and chairs don’t want to pay out more money per year. This makes no sense for top programs which can easily find an extra $1k or $2k for interview costs. For low budget programs, it’s a risk worth taking – that overlooked person could bring in big grant money later. Another explanation is laziness. Good hiring is classic free rider problem. Finding and screening for good people is a cost paid by a few people but the benefits are wide spread. So people do the minimum – fly a few out and move on. Tenure may also contribute to the problem – if you might hire someone for life, you become hyper-selective and only focus on one or two people that survived an intense screening process.

Finally, there may be academic caste. Top programs want an ASR on the CV… but only from people from the “right” schools. This explanation makes sense for top schools, but not for other schools. Why? There are usually quite a few people from good but not elite schools who look great on paper but yet, they don’t get called even though they’d pull up the dept. average.

Am I missing the point? Tell me in the comments! Why is academic hiring so odd?

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Written by fabiorojas

March 29, 2018 at 4:11 am

i declare complete victory in the more tweets, more votes debate

In 2013, my collaborators and I published a paper claiming that there is an empirical correlation between relative social media activity and relative vote counts in Congressional races. In other words, if people are talking about the Democrat more than the Republican on Twitter, then the Democrat tends to get more votes. Here’s the regression line from the original “More Tweets, More Votes” paper:

MTMVjournal.pone.0079449.g001.png

People grumbled and complained. But little by little, evidence came out showing that the More Tweets/More Votes model was correct. For example, an article in Social Science Quarterly showed the same results for relative Google searches and senate races:

senate_google

Latest evidence? It works for wikipedia as well. Public Opinion Quarterly published a piece called “Using Wikipedia to Predict Election Outcomes: Online Behavior as a Predictor of Voting” by Benjamin Smith and Abel Gustafason. From the abstract:

We advance the literature by using data from Wikipedia pageviews along with polling data in a synthesized model based on the results of the 2008, 2010, and 2012 US Senate general elections. Results show that Wikipedia pageviews data significantly add to the ability of poll- and fundamentals-based projections to predict election results up to 28 weeks prior to Election Day, and benefit predictions most at those early points, when poll-based predictions are weakest.

Social media DOES signal American election outcomes! I spike the football. I won. Period.

It’s pretty rare that you propose a hypothesis, your prove it’s right and then it is proved right a bunch of times by later research.

#winning

50+ chapters of grad skool advice goodness: Grad Skool Rulz ($4.44 – cheap!!!!)/Theory for the Working Sociologist (discount code: ROJAS – 30% off!!)/From Black Power/Party in the Street / Read Contexts Magazine– It’s Awesome 

Written by fabiorojas

September 19, 2017 at 4:01 am

unresolved controversy bleg

Installing Order, the sociology of science and technology blog, has a request – can you identify scholarly work about unresolved scientific controversies? 

I need your help: anybody know a few research papers or a book specifically about unresolved controversies? It would be terrific if there was some conceptualization, or even a functional analysis of the manifest and latent consequences of unresolved controversies. In fact, it would be amazing to see research on “intentionally unresolved controversies.”

My hunch is that they should be rare because writers probably want to focus on narrative with clear stories. Anthropology is full of unresolved controversies, so maybe focusing on the writing surrounding Napoleon Chagnon might be helpful.

What would you suggest?

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

Written by fabiorojas

November 28, 2016 at 12:33 am

critique of a recent ajs genetics paper: levi-martin v. guo, li, wang, cai and duncan

John Levi-Martin has written a comment on a recent paper by Guo, Li, Wang, Cai, and Duncan  claiming that the social contagion of binge drinking associated with a medium genetic propensity. Levi-Martin claims that GLWCD having simply misread their data:

Guo, Li, Wang, Cai and Duncan (2015) recently claimed to have provided evidence for a
general theory of gene-environment interaction. The theory holds that those who are labelled as having high or low genetic propensity to alcohol use will be unresponsive to environmental factors that predict binge-drinking among those of moderate propensity. They actually demonstrate evidence against their theory, but do not seem to have understood this.
The main claim is that GLWCD are testing against nulls rather than properly estimating a U-shaped effect:
This is consequential because of the way that choose to examine their data. Although
the verbal description of the swing theory here refers to the comparison of magnitudes  (“more likely”), the methods used by GLWCD involve successive tests of the null hypothesis across three subsets formed by partitioning the sample by level of what is termed genetic propensity. If we denote these three subsets L, M and H, standing for low, medium and high propensity, then, for the kth predictor, they estimate three slopes, bLk, bMk, and bHk. Because the swing theory does not require that any particular predictor have an effect, but only that if it does, it does not in the extreme propensity tiers, this theory holds that for any k, bLk≈bHk≈ 0.
Publishing note: The comment is on SocArXiv for all to read. If the criticism holds water, it’s a shame that it is not in a journal, preferably the AJS. If journals simply aren’t interested in error correction, then they simply aren’t into science.
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Written by fabiorojas

November 21, 2016 at 3:29 am

social science did ok with the 2016 election but not great

masket-graph

From Seth Masket at Pacific Standard.

People have been having meltdowns over polls, but I’m a bit more optimistic. When you look at what social science has to say about elections, it did ok last week. I am going to avoid poll aggregators like Nate Silver because they don’t fully disclose what they do and they appear to insert ad hoc adjustments. Not horrible, but I’ll focus on what I can see:

  1. Nominations: The Party Decides model is the standard. Basically, the idea is that party elites choose the nominee, who is then confirmed by the voters. It got the Democratic nomination right but completely flubbed the GOP nomination. Grade: C+.
  2. The “fundamentals” of the two party vote: This old and trusty model is a regression between two party vote share and recent economic conditions. Most versions of this model predicted a slim victory for the incumbent party. The figure above is from Seth Masket, who showed that Clinton 2 got almost exactly what the model predicted. Grade: A
  3. Polling: Averaged out, the poll averages before the election showed Clinton 2 getting +3.3 more points than Trump. She is probably getting about %.6 more than Trump. So the polls were off by about 2.7%. That’s within the margin of error for most polls. I’d say that’s a win. The polls, though, inflated the Johnson vote. Grade: B+.
  4. Campaigns don’t matter theory: Clinton 2 outspent, out organized, and out advertised Trump (except in the upper midwest) and got the same result as a “fundamentals” model would predict. This supports the view that campaigning has a marginal effect in high information races. Grade: A.

But what about the Electoral College? Contrary to what some folks may think, this is a lot harder to predict because state level polls produce worse results in general. This is why poll aggregators have to tweak the models a lot to get Electoral College forecasts and why they are often off. Also, the Electoral College is designed to magnify small shifts in opinion. A tiny shift in, say, Florida could move your Electoral College total by about 5%. Very unstable. That’s why a lot of academic steer clear of predicting state level results. All I’ll say is that you should take these with a grain of salt.

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

Written by fabiorojas

November 15, 2016 at 12:01 am

driverless cars vs. police departments

In my view, driverless cars are revolutionary. At the very least, they will eliminate a major health problem – auto injuries and fatalities. No system will be accident free, but driverless cars will be better at driving that most humans, they don’t get drunk, and they won’t drive recklessly.

There is another social consequence of driverless cars that needs discussion. Driverless cars will seriously disrupt police departments. Why? A lot of police department revenue comes from moving vehicle violations and parking tickets. In a recent news item, one judge admitted that many small town fund their police department entirely through speeding tickets. Even a big city police department enjoys the income from tickets. New York City receives tens of millions in moving violation fines. This income stream will evaporate.

Another way that driverless cars will disrupt police departments is that they will massively reduce police stops. If a driverless car has insurance and registration (which can be transmitted electronically) and drives according to the rules of the road, then police, literally, have no warrant to pull over a car that has not been previously identified as related to a specific crime. Hopefully, this means that police will no longer use moving violations as an excuse to pull over racial minorities.

Even if a fraction of the hype about driverless cars turns out to be true, it would be a massive improvement for humanity. Three cheers for technology.

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

 

 

Written by fabiorojas

November 3, 2016 at 12:15 am

the parking lot theory of third parties

Right now, we aren’t seeing a collapse of Donald Trump. Instead, we’re seeing (a) Clinton 2 steady at about 45% in the four way race and (b) Trump moving from about 40% to 43%. That means that the third party vote is collapsing. Johnson is dropping from a summer high of 10% to 4%. How can that be?

My current favorite explanation is the “parking lot” theory of American third parties. Most people today are highly polarized, which means they strongly sort themselves into parties and stick with it. A number of people, including myself, have argued that parties are a sort of social identity. Perhaps not as fundamental as gender or racial identity, but important none the less. The consequence of party-identity theory is  that people usually become defensive about their identity and they are loathe to leave it.

“Parking lot” theory is a corollary of party-identity theory. When people are faced with a horrible candidate from their party, they become defensive and don’t want to give it up. They refuse to consider third parties. At best, third parties become “parking lots” for voters who are indecisive or embarrassed until they finally pull the lever for mainstream parties. I suspect that is what resulted in those 10% polls for Johnson. The Libertarian Party was simply the “parking lot” for 5% of American voters who fully intend to vote GOP but are too embarrassed by Trump. There is a real libertarian vote out there, but it is in the low single digits. Definitely not 10%.

I’m not the first to make this argument. In fact, one my BGS* pointed out that this argument appears in Shafer and Spady’s recent book The American Political Landscape. They don’t develop it fully but the historical data is there. In 2016, we see a spike of 10% for the Libertarians but they’ll be lucky to get 5% on polling day. In 1992, Perot peaked in the 30%  range but ended up with 19% (still impressive) and then 10% in 1996. In 1980, John Anderson peaked at 20% but ended up with a paltry 7%.  Nader 2000 is probably the only modern third party candidate that wasn’t a voter parking lot. He polled consistently in the 2%-4% range and got 3%.

Bottom line: The Libertarians may spoil a state or two this round, but they are doomed to be a voter parking lot.

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

* Brilliant Grad Students

Written by fabiorojas

November 2, 2016 at 12:01 am