NCAA — Hoops and Hopes

April 3, 2016
Posted by Jay Livingston

March Madness ends tomorrow night when the student-athletes from the University of North Carolina match up against the student-athletes from Villanova. I’m being ironic about the “student” part, UNC providing one of the most recent and egregious cases. These players are different from most other students. When they were making their choices about higher education, scholarliness had little to do with it. The crucial variables was the quality of the basketball team.

When I ask my students why they came to college, the answer is usually, “To get an education.” When I ask why they would want an education, the answer is, “So I can get a good job.” When I ask what makes a job good, the first response is “money.” My students are student-earners.

How much will they earn? Take a look at the scorecard – the Obama administration’s recently created College Scorecard  (here). It shows median yearly earnings ten years after a student first enrolls. Here’s how the NCAA final four stack up.

(Click on a chart for a larger view.)

Villanova wins handily. But it’s a small private school. Its students come from better-off families, and when its graduates look for jobs nearby, the salary scale is going to be much higher than in Oklahoma. We need something like the Sabermetrics WPA (win probablity added). Fortunately, over at Brookings, Siddharth Kulkarni and Jonathan Rothwell rated the teams in the NCAA bracket on a sort of $PA that adjusts for family income, location, test scores, and other factors that might affect the income of graduates.

Now the NCAA final four look not so evenly matched,and UNC, only a 2½-point underdog on the floor tomorrow night, trails Villanova in the earnings-added tournament by a considerable margin.

College basketball is not life. It’s not even earnings ten years after freshman year. Kulkarni and Rothwell played through the brackets as drawn for the basketball tournament, using the earnings scores rather than basketball scores.  Only Villanova made it to the final four in both tournaments.

These four were not necessarily the highest-rated schools. Southern University, for example, scored a 95 – higher than Utah’s 94 – but the luck of the draw put them up against Duke in the Sweet Sixteen round. Here is the entire tournament.

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The Kulkarni-Rothwell article is here with links to the scores of lots of schools, both 2-year and 4-year.  Not all schools appear in the interactive function. If your school does not appear there, download the spreadsheet data and go to column CW.

Still Telling It Like It Is?

March 30, 2016
Posted by Jay Livingston

If Donald Trump’s star begins to fade or even plummets from the firmament, his statements today about abortion may be the turning point. Trump said abortion should be banned and that “there should be some form of punishment” for women who get abortions. A few hours later he issued a statement saying that he would criminalize only the people who performed the abortion, not the women.

The political problem is not that he is offending women – he’s been offending them all through the successful months of his candidacy. It’s that he risks being seen as a politician. For most of Trump’s hard core constituency, his appeal has not been his stand on the issues, except perhaps immigration. What they like in Trump is his seeming indifference to what others think. Trump is the un-politician, he’s the guy who “tells it like it is.”

Exit pollsters at the South Carolina primary in February asked people about the qualities of the six candidates. On the question, “Which candidate shares my values?” Cruz was the winner. But on “Which candidate tells it like it is?” The difference between Trump and all the others was overwhelming. (source here.)

“Telling it like it is” is not the same thing as being factual. Accuracy does not seem to matter much to Trump voters. Instead, the phrase means speaking your mind without regard to political correctness or political impact. It’s the Trump supporters’ version of “speaking truth to power.” Even Trump’s denigrating what Republicans had been hailing as John McCain’s war heroism cost him no votes. Trump was saying what he thought even though it might violate conservative canons of political correctness.

The South Carolina sentiments are reflected in a  Gallup poll in January that asked Republicans what they thought would be the best thing about a Trump presidency. Nearly a quarter of the responses fit into the tell-it-like-it-is category. Trump “says what he feels” and “does not back down.”

(Click on the image for a slightly larger view.)

Today Trump was different. He put forward a position whose purpose seemed to be its political appeal rather than the expression of what he feels. Then three hours later, he backed down.

“I could stand in the middle of Fifth Avenue and shoot somebody, okay, and I wouldn’t lose any voters,” Trump said just two months ago. He may have been right. But today by changing his position in order to win votes and then changing it back for the same reason he just might be shooting down his own campaign.*

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* I realize that this guess about Trump voters directly contradicts what I said about a particular Trump supporter, Alex Chalgren, in an recent post (here). It’s possible that most of Trump’s backers will find similar ways to resolve the dissonance. But there’s a difference. First, what happened today concerns character, not policy. Second, unlike Alex Chalgren, most of Trump voters and potential voters have not made their support of him so public. 

Based – Off and On

March 26, 2016
Posted by Jay Livingston

“This is based off of self-interest . . . .” wrote one student. Another wrote, “It’s an idea based off others from past years.” 

This construction sounded wrong to my ears. What happened to “based on”? Was this some local North New Jersey variant, like the New Yorkers’ waiting on line when everyone else in the US waits in line? But then I saw it in The Guardian last week:

Kang and her colleagues sent out 1,600 fabricated resumes, based off of real candidates, to employers in 16 different metropolitan areas in the US.

Lexis-Nexis turned up a few others just since the start of the year, and it wasn’t just New Jersey, or even the US.

• “Me and Earl and the Dying Girl “ is based off of the book by Jesse Andrews, (Berkshire Eagle) “We should set a baseline, and that's what the salaries should be based off.” (Chicago Daily Herald)
• . . .little should be read into the upcoming Capital One Cup game based off this result. (Manchester Evening News, UK)
• . . . schools estimated the number of children in their zone based off a ballot sent out in September (Manawatu Standard, New Zealand)

“Busy prepositions, always on the go,” said “Schoolhouse Rock.”* But it seems to me that prepositions are remarkably stable – those New Yorkers are still waiting on line, even though “on line” has added a much different and widely used meaning.

How did we get “based off” and “based off of”? How did this diffusion happen? It’s not like some fashion in clothing. It’s not created in Language Central and sent out amid a big publicity campaign. Nor did any celebrities start using it. Nor is it like the words that people are fully aware of and consciously choose, the phrases that are groovy for a minute or two and then become old hat, or those that are totally awesome and become part of the language and that nobody has an issue with.

My Lexis-Nexis search for “based off” turned up about 300 hits for 2016. (Lexis-Nexis does not consider “of” to be worthy of counting, so adding it to a word or phrase – “based off of” – is useless.) In the same period for 2010, the count was 100. In 2000, zero.

The Google nGrams database of books tells a similar story of the rapid rise of “based off of.” Of course, it is, by several orders of magnitude, still dwarfed by “based on.” But this graph, with “based off of multiplied by 100,000, shows its recent and rapid rise.

The change is probably generational. Older speakers like me will cling to “based on”; but “based off” or “based off of” will be the choice of an increasing number of younger people. It won’t catch up to “based on” immediately. It’s not the faddish kind of change that will happen in a couple of days. Or do I mean “in a couple days”?

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* The song is here. It was written by jazz pianist/composer Bob Dorough, and he performs it with trumpeter Jack Sheldon. Other jazzers, notably Dave Frishberg and Blossom Dearie, contributed to “Schoolhouse Rock” as writers and performers. Busy jazz musicians.

Show, Don’t Tell

March 23, 2016
Posted by Jay Livingston

Can the mood of a piece of writing be graphed?

For his final project in Andrew Gelman’s course on statistical communication and graphics, Lucas Estevem created a “Text Sentiment Visiualizer.” Gelman discusses it on his blog, putting the Visualizer through its paces with the opening of Moby Dick.

(Click on an image for a slightly larger view.)

Without reading too carefully, I thought that the picture – about equally positive and negative – seemed about right. Sure things ended badly, but Ishmael himself seemed like a fairly positive fellow. So I went to the Visualizer (here)  and pasted in the text of one of my blogposts. It came out mostly negative. I tried another. Ditto. And another. The results were not surprising when I thought about what I write here, but they were sobering nevertheless. Gotta be more positive.

But how did the Visualizer know? What was its formula for sussing out the sentiment in a sentence? Could the Visualizer itself be a glum creature, tilted towards the dark side, seeing negativity where others might see neutrality? I tried other novel openings. Kafka’s Metamorphosis was entirely in the red, and Holden Caulfield looked to be at about 90%. But Augie March, not exactly a brooding or nasty type, scored about 75% negative. Joyce’s Ulysses came in at about 50-50.

To get a somewhat better idea of the scoring, I looked more closely at page one of The Great Gatsby. The Visualizer scored the third paragraph heavily negative – 17 out of 21 lines. But many of those lines had words that I thought would be scored as positive.

Did the Visualizer think that extraordinary gift, gorgeous, and successful were not such a good thing?

Feeling slightly more positive about my own negative scores, I tried Dr. Seuss. He too skewed negative.

What about A Tale of Two Cities? Surely the best of times would balance out the worst of times, and that famous opening paragraph would finish in a draw. But a line-by-line analysis came out almost all negative.

Only best, hope, and Heaven made it to the blue side.

I’m not sure what the moral of the story is except that, as I said in a recent post, content analysis is a bitch.

Gelman is more on the positive side about the Visualizer. It’s “far from perfect,” but it’s a step in the right direction – i.e., towards visual presentation – and we can play around with it, as I’ve done here, to see how it works and how it might be improved. Or as Gelman concludes, “Visualization. It’s not just about showing off. It’s a tool for discovering and learning about anomalies.”