I’ve been reading Head First Java this past week and I’m super impressed and want to tell you guys about it if you don’t already know.
I wanted to learn what the big fuss was about object-oriented programming, plus it seems like all the classes my Lede students are planning to take either require python or java, so this seemed like a nice bridge.
But the book is outstanding, with quirky cartoons and a super fun attitude, and I’m on page 213 after less than a week, and yes that’s out of more than 600 pages but what I’m saying is that it’s a thrilling read.
My one complaint is how often the book talks about motivating programmers with women in tight sweaters. And no, I don’t think they were assuming the programmers were lesbians, but I could be wrong and I hope I am. At the beginning they made the point that people remember stuff better when there is emotional attachment to things, so I’m guessing they’re getting me annoyed to help me remember details on reference types.
Here’s another Head First book which my nerd mom recommended to me some time ago, and I bought but haven’t read yet, but now I really plan to: Head First Design Patterns. Because ultimately, programming is just a tool set and you need to learn how to think about constructing stuff with those tools. Exciting!
And by the way, there is a long list of Head First books, and I head good things about the whole series. Honestly I will never write a technical book in the old-fashioned dry way again.
Today I read this article written by Allie Gross (hat tip Suresh Naidu), a former Teach for America teacher whose former idealism has long been replaced by her experiences in the reality of education in this country. Her article is entitled The Charter School Profiteers.
It’s really important, and really well written, and just one of the articles in the online magazine Jacobin that I urge you to read and to subscribe to. In fact that article is part of a series (here’s another which focuses on charter schools in New Orleans) and it comes with a booklet called Class Action: An Activist Teacher’s Handbook. I just ordered a couple of hard copies.
I’d really like you to read the article, but as a teaser here’s one excerpt, a rant which she completely backs up with facts on the ground:
You haven’t heard of Odeo, the failed podcast company the Twitter founders initially worked on? Probably not a big deal. You haven’t heard about the failed education ventures of the person now running your district? Probably a bigger deal.
When we welcome schools that lack democratic accountability (charter school boards are appointed, not elected), when we allow public dollars to be used by those with a bottom line (such as the for-profit management companies that proliferate in Michigan), we open doors for opportunism and corruption. Even worse, it’s all justified under a banner of concern for poor public school students’ well-being.
While these issues of corruption and mismanagement existed before, we should be wary of any education reformer who claims that creating an education marketplace is the key to fixing the ills of DPS or any large city’s struggling schools. Letting parents pick from a variety of schools does not weed out corruption. And the lax laws and lack of accountability can actually exacerbate the socioeconomic ills we’re trying to root out.
I have a theory which I’m slightly embarrassed about but whatever, that’s what blogs are for, I’m going to talk about it. And I have no data for this whatsoever, although I’d be interested to hear thoughts on how to collect some.
Namely, I think a sizable amount of social change we’ve seen in the past few decades, for better and for worse, can be ascribed to what I call “the app effect,” namely the tendency for everyone, but young men in particular to be playing games on their phones or their xbox360’s or whatever rather than interacting with each other.
Look at crime rates. I am not claiming that crime rates have fallen solely because of the app effect over other reasonable effects, like the availability of abortions, or less lead paint, or people having more air conditioning.
But, let’s face it, when I was growing up in Boston in the 1980’s, you’d just see way more people out on the streets on summer evenings because it was too freaking hot to do anything inside and people were damn bored. That’s when the trouble would start. Nowadays you just don’t see that nearly as much. What are people doing? My guess is that they’re playing a shit load of video games. Tell me if I’m wrong.
Here’s another example. People are less politically engaged. Partly it’s because Congress sucks, but partly – yes – it’s because people are playing Candy Crush! They used to maybe spend time going to work reading the paper and otherwise doing the civic duty thing but nowadays they’re just trying to pass level 187. I’ve been there so I know about it.
Also, when the train stops? In the tunnel? And it’s dark and really hot? Everyone just plays their games even harder, where you used to maybe start talking, or shouting, or freaking out. It is a pacifier for grown-ups, a nationwide babysitting service that keeps people in line.
It’s good and bad. Sometimes getting out of line serves a purpose, sometimes it’s just destructive and the wrong thing to do. My worry, as a person who wants to see political engagement, is that we have trained an entire population to take refuge in a pointless activity that doesn’t serve any real purpose except to distract us and to mollify us, not to mention collect our data for later marketing purposes.
Another way to imagine this is, if all the apps and all the video games stopped working for a few weeks, what would happen? What would people do with themselves?
Well hello there, cutie, and welcome. Aunt Pythia loves you today, even more than usual!
For some reason she can’t pinpoint, but probably has to do with a general feeling of happiness and fulfillment, Aunt Pythia is even more excited than usual to be here and to toss off unreasonably smug and affectionate opinions and advice. Buckle up and get ready for the kisses and the muffins.
Everyone set? OK, fabulous, let’s get going. Oh and by the way, at the bottom of the column please please
think of something to ask Aunt Pythia at the bottom of the page!
I am almost out of questions!!!
Dear Aunt Pythia,
How should one deal with sexism and harassment at conferences?
As a white heterosexual male mathematician, I don’t experience much bias against me in my professional life, but I’ve seen (and heard of) a lot of bad stuff happening against anyone not conforming to this norm, which I think is not only bad for the people who experience this, but also bad for mathematics as a whole, for various reasons.
At a recent specialized conference, one of participants (a grad student) was very obviously sexually interested in one of the other grad students (one of only 2 female participants, my field has some serious problems in this regard), who was clearly not interested (and married).
I didn’t know these persons before the conference, and beyond me saying to the the harassing person that she was married and that he shouldn’t annoy her (which didn’t have any impact of course), I didn’t do anything. I would have liked to somehow help the harassed party feel welcome, and communicate that besides that one jerk people were interested in her mathematical ideas, but I didn’t know how to communicate this to her without making it seem inappropriate. So instead, I kept silent, which feels bad. Is there anything I could do next time I was in this type of situation, besides trying not to be a jerk?
Dr. Nonheroic Observer
Dear Dr. NO,
I gotta say, I love your question, but it’s kind of spare on details. What did the guy do? How much did it annoy the married party? It really matters, and my advice to you depends on those facts.
When I think about it, though, I don’t see why the fact that she’s married matters. Speaking as a 17-year married person (as of today!), married people like to flirt sometimes, so it’s not as if it’s intrinsically harassing for someone to express interest in a married person, or for that matter a single person.
But as soon as someone responds with a “not interested” signal, it is of course the responsibility of the interested party to tone it down.
Let me go into three scenarios here, and tell you what I think your response should be in each.
First, the guy likes her. You said it was obvious he was interested and it was also obvious she wasn’t. Depending on how that played out, it could be totally fine and not at all your responsibility to do anything. So, if he was like, hey would you like to go on a walk? and then she said, no thanks I’m going to get some work done and that was that, then whatevs. Again, not holding anything against someone for interest per se.
Now on to the second scenario, which seems more likely, since you mentioned that he annoyed her in spite of your advice to him. So that means he followed her around a lot and generally speaking glommed on her, which probably means he obstructed her normal interaction with other mathematicians at the conference. This is a big problem, because conferences are when the “mathematical socializing” happens, which very often results in collaboration and papers. The fact that men glom onto women prevents that, and might be a reason women don’t join your field.
Your responsibility, beyond telling the guy to lay off, which you did, is to first of all talk math with her explicitly, so she gets some mathematical socializing done. Also be proactive in introducing her to other people who are good math socializers.
Beyond that, I think you need to tell the guy to stop a second time. Ask the guy to think about why she came to the conference, and what she wants and doesn’t want out of the experience. In other words, make him try to think about her perspective rather than his own dick’s perspective. Who knows, it might help, he might just be super nerdy and not actually an asshat.
If that doesn’t work, and if he is in fact an asshat, I suggest you go to her and ask her if he is bothering you. Pretending not to notice isn’t helping her, and she probably has nobody to appeal to and could use an ally. If she says yes, then with her permission, go back to the guy and tell him he is officially bothering her. I guess that would actually work.
Third scenario is when even that doesn’t work, in which case I would go to the organizer of the conference and suggest that the harasser be asked to leave the conference.
I’d be super interested to hear your thoughts, and in particular what you think would happen if you had actually gone to the organizers. Of course, if you were one of the organizers yourself, I’d say you should have threatened the guy with expulsion earlier on.
Write back and tell me more details and tell me whether this advice was helpful!
Dear Aunt Pythia,
Why EW? What is wrong with “He went on way too many dates too quickly”? What makes you the judge of what constitutes too many, when you yourself admit that you “have taken myself out of the sex game altogether – or at least the traditional sex game” so your opinion on traditional sex game (which is exactly what this guy is doing) is clearly biased. He is a modern empowered man who is exploring his options before settling down. What you wrote is nothing different than “slut-shaming” just reversing the gender. I hope you will exercise greater sensitivity in the future posts.
I am all for slutty behavior. In fact I am super sex positive. If the guy were just trying to get lots of great sex with lots of amazing women, then more power to him. I’d tell him about Tinder and I’d even direct him to critiquemydickpic for useful and amusing advice.
But actually he was having one or two dates per day looking for love. What?! That’s way too much emotional drainage. How can anyone remain emotionally receptive if they can’t even remember people’s names? I’d be much much happier for him, and I wouldn’t be judgmental, if he had been bringing home a different woman every night for mind-blowing sex. Youth!!
So, if you want to complain about my “ew”, then I think you’d need to say that, if someone can fuck anything that moves, they should also be able to love anything that moves. I’m not sure there’s a name for this but maybe “love-shaming?”.
In any case, I stand by my “ew”: I don’t think loving one or two people per day is possible. And the woman he ended up with found him, which was different and broke his cycle, kind of proving my point.
Dear Aunt Pythia,
I’m a statistician with four-or-so years of work experience, but currently in the last half year or so of a applied bayesian stats PhD. I have seen the rise of R and Statistics as a hot, talked about subject. And for some reason, I am getting nervous about all the new cool kids that play around on Kaggle; that they will take ALL THE JOBS, and that there will be no space for slightly less cool, more classically trained statisticians such as myself. After all, all we’re doing is a bit of running a glm, or a cluster analysis, or some plotting. A monkey could learn that in three months. Sometimes I wish everyone would stay away and let me have all the datasets for myself.
Am I being unreasonably nervous about the future?
Have Stats Want to Analyze
First, I wanna say, I had high hopes for your sign off until I wrote it out. Then I was like, wtf?! I even googled it but all I came back with was the Hampton Shaler Water Authority. And I am pretty sure that’s not what you meant. And keeping the “t” in didn’t help.
Second, I’ve got really good advice for you. Next time you’re in an interview, or even if you’re just on a bus somewhere with someone sitting next to you who allows you to talk, mention that Kaggle competitions are shitty bars for actual data scientists, because most of the work of the data scientist is figuring out what the actual question is, and of course how to measure success.
Those things are backed into each Kaggle competition, so hiring people who are good at Kaggle competitions is like hiring the chef who has been supplied with a menu, a bunch of recipes, and all the ingredients to run your new restaurant. Bad idea, because that’s the job of the chef if he’s actually good. In other words, it’s not actually all that impressive to be able to follow directions, you need to be creative and thoughtful.
Make sure you say that to your interviewer, and then follow it up with a story where you worked on a problem and solved it but then realized you’d answered the wrong question and so you asked the right question and then solved that one too.
I’m not nervous for you, thoughtful statisticians are in high demand. Plus you love data, so yeah you’re good.
Dear Aunt Pythia,
I’ve been working as faculty in a new department this year and I have repeatedly had the feeling that the support staff is not treating me the way they would if I were 50 and male instead of young and female (although with the rank of professor).
It’s small things like roundly scolding me for using a coffee mug from the wrong cupboard, or hinting I should make sure the kitchen cleaning is easy for staff (I’m not messy!), or the conference support staff ceasing to help with basic support on a conference (and complaining about me to other people), or wanting me to walk some mail to another building.
I realize this is all small potatoes. But I have started to feel like by just taking it passively (e.g. smiling and nodding) I might be saving myself time and anger now but I’m helping to perpetuate the system. I rigorously avoid confrontation and I think I’m typically regarded as a very friendly and helpful team player by my peers. (How could I prove bias anyway, and would confrontation help?). But I’m not sure I can spend my whole life putting up with small potatoes along with the bigger potatoes I encounter from time to time.
Spud Farmer Considering Pesticides
First of all, again, disappointed your sign-off didn’t spell anything. But will let it pass.
Second of all, my guess is that they are sexist. I have a prior on this because I’ve encountered so much sexism in this exact way.
Third of all, I’m also guessing they are administrative people in academia, which means they are also just barely able and/or willing to do their jobs. Again, experience, and since I am administration now in academia, I am allowed to call it. Some people are great, most people are not.
Fourth, I don’t know why you are “rigorously avoiding confrontation” here. The very first thing you should do is choose your tiny battles wisely and create small but useful confrontation. Examples:
- Someone asks you to mail a letter. You say, “oh who usually mails letters? I will be sure to bring it to them.”
- Someone doesn’t want to do their part in helping with basic support on conferences. You say, “Oh that’s not your job? I am so sorry. Who should I be asking for help on this?”
- Someone scolds you for using the wrong coffee cup or some such nonsense. You say, “I am new here and I don’t know the rules but I will be sure to remember this one! I am one of those people with a strong work ethic, and it’s great to see how people around here pull together and make things happen.” You know, be aspirational.
Fifth, if it comes to it, get a faculty ally to explain which staff are bitter and why, and which of them are juts plain nuts, and which ones do everyone else’s job. Useful information. Make sure it’s an ally! Complaining about this stuff to the wrong person could give you a reputation as a complainer.
Sixth, do not let this stuff build up inside you! Make it an amusing part of your day to see how people wiggle out of their responsibilities and blame other people for their mistakes. And keep in mind that the faculty are probably the biggest and best examples of such behavior.
Please submit your well-specified, fun-loving, cleverly-abbreviated question to Aunt Pythia!
Yesterday was a day filled with secrets and codes. In the morning, at The Platform, we had guest speaker Columbia history professor Matthew Connelly, who came and talked to us about his work with declassified documents. Two big and slightly depressing take-aways for me were the following:
- As records have become digitized, it has gotten easy for people to get rid of archival records in large quantities. Just press delete.
- As records have become digitized, it has become easy to trace the access of records, and in particular the leaks. Connelly explained that, to some extent, Obama’s harsh approach to leakers and whistleblowers might be explained as simply “letting the system work.” Yet another way that technology informs the way we approach human interactions.
After class we had section, in which we discussed the Computer Science classes some of the students are taking next semester (there’s a list here) and then I talked to them about prime numbers and the RSA crypto system.
I got really into it and wrote up an iPython Notebook which could be better but is pretty good, I think, and works out one example completely, encoding and decoding the message “hello”.
Yesterday we were pleased to have Suresh Naidu guest lecture in The Platform. He came in and explained, very efficiently because he was leaving at 11am for a flight at noon at LGA (which he made!!) how to think like an economist. Or at least an applied microeconomist. Here are his notes:
Applied microeconomics is basically organized a few simple metaphors.
- People respond to incentives.
- A lot of data can be understood through the lens of supply and demand.
- Causality is more important than prediction.
There was actually more on the schedule, but Suresh got into really amazing examples to explain the above points and we ran out of time. At some point, when he was describing itinerant laborers in the United Arab Emirates, and looking at pay records and even visiting a itinerant labor camp, I was thinking that Suresh is possibly an undercover hardcore data journalist as well as an amazing economist.
As far as the “big data” revolution goes, we got the impression from Suresh that microeconomists have been largely unmoved by its fervor. For one, they’ve been doing huge analyses with large data sets for quite a while. But the real reason they’re unmoved, as I infer from his talk yesterday, is that big data almost always focuses on descriptions of human behavior, and sometimes predictions, and almost never causality, which is what economists care about.
A side question: why is it that economists only care about causality? Well they do, and let’s take that as a given.
So, now that we know how to think like an economist, let’s read this “Room For Debate” about overseas child labor with our new perspective. Basically the writers, or at least three out of four of them, are economists. So that means they care about “why”. Why is there so much child labor overseas? How can the US help?
The first guy says that strong unions and clear signals from American companies works, so the US should do its best to encourage the influence of labor unions.
The lady economist says that bans on child labor are generally counterproductive, so we should give people cash money so they won’t have to send their kids to work in the first place.
The last guy says that we didn’t even stop having child labor in our country until wage workers were worried about competition from children. So he wants the U.S. to essentially ignore child labor in other countries, which he claims will set the stage for other countries to have that same worry and come to the same conclusion by themselves. Time will help, as well as good money from the US companies.
So the economists don’t agree, but they all share one goal: to figure out how to tweak a tweakable variable to improve a system. And hopefully each hypothesis can be proven with randomized experiments and with data, or at least evidence can be gathered for or against.
One more thing, which I was relieved to hear Suresh say. There’s a spectrum of how much people “believe” in economics, and for that matter believe in data that seems to support a theory or experiment, and that spectrum is something that most economists run across on a daily basis. Even so, it’s not clear there’s a better way to learn things about the world than doing your best to run randomized experiments, or find close-to-randomized experiments and see how what they tell you.
When I was prepping for my Slate Money podcast last week I read this column by Matt Levine at Bloomberg on the Citigroup settlement. In it he raises the important question of how the fine amount of $7 billion was determined. Here’s the key part:
Citi’s and the Justice Department’s approaches both leave something to be desired. Citi’s approach seems to be premised on the idea that the misconduct was securitizing mortgages: The more mortgages you did, the more you gotta pay, regardless of how they performed. The DOJ’s approach, on the other hand, seems to be premised on the idea that the misconduct was sending bad e-mails about mortgages: The more “culpable” you look, the more it should cost you, regardless of how much damage you did.
I would have thought that the misconduct was knowingly securitizing bad mortgages, and that the penalties ought to scale with the aggregate badness of Citi’s mortgages. So, for instance, you’d want to measure how often Citi’s mortgages didn’t match up to its stated quality-control standards, and then compare the actual financial performance of the loans that didn’t meet the standards to the performance of the loans that did. Then you could say, well, if Citi had lived up to its promises, investors would have lost $X billion less than they actually did. And then you could fine Citi that amount, or some percentage of that amount. And you could do a similar exercise for the other big banks — JPMorgan, say, which already settled, or Bank of America, which is negotiating its settlement — and get comparable amounts that appropriately balance market share (how many bad mortgages did you sell?) and culpability (how bad were they?).
I think he nailed something here, which has eluded me in the past, namely the concept of what comprises evidence of wrongdoing and how that translates into punishment. It’s similar to what I talked about in this recent post, where I questioned what it means to provide evidence of something, especially when the data you are looking for to gather evidence has been deliberately suppressed by either the people committing wrongdoing or by other people who are somehow gaining from that wrongdoing but are not directly involved.
Basically the way I see Levine’s argument is that the Department of Justice used a lawyerly definition of evidence of wrongdoing – namely, through the existence of emails saying things like “it’s time to pray.” After determining that they were in fact culpable, they basically did some straight-up negotiation to determine the fee. That negotiation was either purely political or was based on information that has been suppressed, because as far as anyone knows the number was kind of arbitrary.
Levine was suggesting a more quantitative definition for evidence of wrongdoing, which involves estimating both “how much you know” and “how much damage you actually did” to determine the damage, and then some fixed transformation of that damage becomes the final fee. I will ignore Citi’s lawyers’ approach since their definition was entirely self-serving.
Here’s the thing, there are problems with both approaches. For example, with the lawyerly approach, you are basically just sending the message that you should never ever write some things on email, and most or at least many people know that by now. In other words, you are training people to game the system, and if they game it well enough, they won’t get in trouble. Of course, given that this was yet another fine and nobody went to jail, you could make the argument – and I did on the podcast – that nobody got in trouble anyway.
The problem with the quantitative approach, is that first of all you still need to estimate “how much you knew” which again often goes back to emails, although in this case could be estimated by how often the stated standards were breached, and second of all, when taken as a model, can be embedded into the overall trading model of securities.
In other words, if I’m a quant at a nasty place that wants to trade in toxic securities, and I know that there’s a chance I’d be caught but I know the formula for how much I’d have to pay if I got caught, then I could include this cost, in addition to an estimate of the likelihood for getting caught, in an optimization engine to determine exactly how many toxic securities I should sell.
To avoid this scenario, it makes sense to have an element of randomness in the punishments for getting caught. Every now and then the punishment should be much larger than the quantitative model might suggest, so that there is less of a chance that people can incorporate the whole shebang into their optimization procedure. So maybe what I’m saying is that arriving at a random number, like the DOJ did, is probably better even though it is less satisfying.
Another possibility to actually deter crimes would be to arbitrarily increasing the likelihood of catching people up to no good, but that has been bounded from above by the way the SEC and the DOJ actually work.