I found the website via Jordan Ellenberg this morning and I honestly can’t stop reading it. It consists of a bunch of anonymously contributed stories, most but not all by women, about everyday sexism that happens in the STEM fields. Many of them resonate either with stuff I’ve lived through or stuff my friends have, some of them don’t seem so bad, some of them are outrageous and actionable.

It’s a great idea to have this, if just for women to be able to point to when men question the level of sexism in STEM fields. Sometimes it’s hard to believe it’s 2014.

Categories: women in math

Notices of the AMS is killing it

I am somewhat surprised to hear myself say this, but this month’s Notices of the AMS is killing it. Generally speaking I think of it as rather narrowly focused but things seem to be expanding and picking up. Scanning the list of editors, they do seem to have quite a few people that want to address wider public issues that touch and are touched by mathematicians.

First, there’s an article about how the h-rank of an author is basically just the square root of the number of citations for that author. It’s called Critique of Hirsch’s Citation Index: A Combinatorial Fermi Problem and it’s written by Alexander Yong. Doesn’t surprised me too much, but there you go, people often fall in love with new fancy metrics that turn out to be simple transformations of old discarded metrics.

Second, and even more interesting to me, there’s an article that explains the mathematical vapidness of a widely cited social science paper. It’s called Does Diversity Trump Ability? An Example of the Misuse of Mathematics in the Social Sciences and it’s written by Abby Thompson. My favorite part of paper:

Screen Shot 2014-10-01 at 8.57.17 AM


Oh, and here’s another excellent take-down of a part of that paper:

Screen Shot 2014-10-01 at 9.02.00 AM


Let me just take this moment to say, right on, Notices of the AMS! And of course, right on Alexander Yong and Abby Thompson!

Categories: math, modeling

People hate me, I must be doing something right

September 30, 2014 32 comments

Not sure if you’ve seen this recent New York Times article entitled Learning to Love Criticism, but go ahead and read it if you haven’t. The key figures:

…76 percent of the negative feedback given to women included some kind of personality criticism, such as comments that the woman was “abrasive,” “judgmental” or “strident.” Only 2 percent of men’s critical reviews included negative personality comments.

This is so true! I re-re-learned this recently (again) when I started podcasting on Slate and the iTunes reviews of the show included attacks on me personally. For example: “Felix is great but Cathy is just annoying… and is not very interesting on anything” as well as “The only problem seems to be Cathy O’Neill who doesn’t have anything to contribute to the conversation…”

By contrast the men on the show, Jordan and Felix, are never personally attacked, although Felix is sometimes criticized for interrupting people, mostly me. In other words, I have some fans too. I am divisive.

So, what’s going on here?

Well, I have a thick skin already, partly from blogging and partly from being in men’s fields all my life, and partly just because I’m an alpha female. So what that means is that I know that it’s not really about me when people anonymously complain that I’m annoying or dumb. To be honest, when I see something like that, which isn’t a specific criticism that might help me get better but is rather a vague attack on my character, I immediately discount it as sexism if not misogyny, and I feel pity for the women in that guy’s life. Sometimes I also feel pity for the guy too, because he’s stunted and that’s sad.

But there’s one other thing I conclude when I piss people off: that I’m getting under their skin, which means what I’m saying is getting out there, to a wider audience than just people who already agree with me, and if that guy hates me then maybe 100 other people are listening and not quite hating me. They might even be agreeing with me. They might even be changing their minds about some things because of my arguments.

So, I realize this sounds twisted, but when people hate me, I feel like I must be doing something right.

One other thing I’ll say, which the article brings up. It is a luxury indeed to be a woman who can afford to be hated. I am not at risk, or at least I don’t feel at all at risk, when other people hate me. They are entitled to hate me, and I don’t need to bother myself about getting them to like me. It’s a deep and wonderful fact about our civilization that I can say that, and I am very glad to be living here and now, where I can be a provocative and opinionated intellectual woman.

Fuck yes! Let’s do this, people! Let’s have ideas and argue about them and disagree! It’s what freedom is all about.

Categories: musing, statistics

Chameleon models

September 29, 2014 13 comments

Here’s an interesting paper I’m reading this morning (hat tip Suresh Naidu) entitled Chameleons: The Misuse of Theoretical Models in Finance and Economics written by Paul Pfleiderer. The paper introduces the useful concept of chameleon models, defined in the following diagram:

Screen Shot 2014-09-29 at 8.46.46 AM


Pfleiderer provides some examples of chameleon models, and also takes on the Milton Friedman argument that we shouldn’t judge a model by its assumptions but rather by its predictions (personally I think this is largely dependent on the way a model is used; the larger the stakes, the more the assumptions matter).

I like the term, and I think I might use it. I also like the point he makes that it’s really about usage. Most models are harmless until they are used as political weapons. Even the value-added teacher model could be used to identify school systems that need support, although in the current climate of distorted data due to teaching to the test and cheating, I think the signal is probably very slight.

Categories: economics, modeling

Aunt Pythia’s advice

September 27, 2014 4 comments

Holy crap, peoples!

Aunt Pythia just counted up her readers’ questions and found super high quality (yay!) combined with super small quantity (boo!), a non-ideal situation. Do you know that there are currently fewer than two weeks’ worth of questions in the bin?! That means that next week might be extra short if nobody comes up with (sexual, optionally true) dilemmas between now and next Saturday.

It’s a situation!! If things don’t change Aunt Pythia will be forced to:

  1. Make up questions. Aunt Pythia has never done this but desperate times call for desperate measures.
  2. Force good friends to submit questions. Aunt Pythia has totally done this but it aint pretty.
  3. Answer questions that have been submitted to other advice columns. Aunt Pythia is actually kind of into this idea. Like, there are plenty of Dan Savage answers she disagrees with, although she loves the guy, obv.

So seriously consider mixing that shit up and:

Don’t forget to submit stolen question from old Dan Savage columns,

especially if you are one of Aunt Pythia’s good friends.

Got it? Good! Love ya!

By the way, if you don’t know what the hell Aunt Pythia is talking about, go here for past advice columns and here for an explanation of the name Pythia.


Dear Aunt Pythia,

I have a question on your recent post entitled Gillian Tett gets it very wrong on racial profiling, when you say:

Specifically, this means that the fact that black Americans are nearly four times as likely as whites to be arrested on charges of marijuana possession even though the two groups use the drug at similar rates would be seen by such a model (or rather, by the people who deploy the model) as a fact of nature that is neutral and true. But it is in fact a direct consequence of systemic racism.”

Racism is not the only interpretation of data. Another possible explanation is that black Americans are less educated and cannot hide marijuana from the cops as well as whites. So it is a correlate, not a cause. Had president Obama done something about education in the US I don’t think we’d see such terrible racial disparity.


Dear NYCN,

Not sure why this is an Aunt Pythia question instead of a comment on that post, but let me respond by, a “WHAA?”. Clearly black kids are much more educated about cops than the average white kids. Are you kidding?

But you do bring up a great point: white kids smoke pot in their own rooms in suburbia, and it’s harder for them to get caught. Black kids maybe don’t have privacy, so they end up doing more pot smoking in public, which means they get caught more. But obviously both whites and blacks walk around with pot in their pockets, so at the end of the day there’s serious racial bias.

This reminds me that I heard a group of Stuyvesant parents met with cops in the Stuy neighborhood and tried to make a deal that, when their kids were caught smoking pot in the nearby park, the cops would just bring them back to school rather than arresting them. Imagine that deal being made in Harlem.

Aunt Pythia


Dear Aunt Pythia,

I saw you asked some good questions at David Madigan’s IDSE Colloquium event this week. I thought it was a really compelling talk (and that Madigan is dreamy…). What were you reactions?

Anyways, when thinking about colloquium in the shower, I started to think about the word. It’s interesting that it’s essentially the same word as colloquial, yet to me they have opposite meanings. Do you think there’s truth to a colloquium really being colloquial?

Curious At the Colloquium

Dear Curious,

First of all, Madigan is awesome and I saw an earlier version of that talk before, in fact I wrote it up in Doing Data Science (Chapter 12). And yes, he’s indeed dreamy, a rare man of integrity. I am a groupie of his, and I don’t mind admitting it. After the talk I gave him a hug and felt a tingle.

Great question about the word colloquium. According to this online Oxford Dictionary, it basically just means “talk together”. Similarly, colloquial just means “conversational”. It makes sense. I wish more things were that informal combined with great.

I just got back from a Day of Data at Yale and I met a guy from the NIH, a really cool motorcycle-driving scientist in fact, and I told him all about Madigan. So I hope that helps the word get out too.

One question, what exactly were you doing in the shower whilst thinking about the talk? Just curious.

Aunt Pythia


Dear Aunt Pythia,

I’m returning back to teaching math after a long illness. I’m starting slow with a modest calculus course at a modest university, somewhere along the north atlantic coast. The budget crisis has taken its toll on the department. The students are barely prepared (serious gaps in algebra and trig.) I have 3 contact hours per week, no discussion sections, no graders.

I’m finding myself with a strange dilemma: should I cut lecturing down to a minimum and rely heavily on the book and youTube videos, while using most of class time for problem-solving and giving insightful examples, or should I go the other way: lecture and relegate homework and quizzes to the online platform that comes with the book.

Please help! I feel like I’m trying to tutor in the midst of lecture and run out of time every time.

Shy and Confounded


Dear Shy,

Given that there are serious gaps in their knowledge, I’d probably try to do at least a few worked-out examples with the students during class to make sure they can handle the mechanics of the solutions in addition to the conceptual ideas you’re presenting.

So maybe that means a 20 minute “review” of the new idea of the day, and then 40 minutes devoted to working out examples, with lots of interaction from the students so you can see what their gaps are and then make announcements about “things to remember”, basically showing them how to do stuff from algebra or trig.

Also consider asking them what is most useful for them to learn the stuff most efficiently in the three hours you have together. And finally, keep in mind that the quiet ones will probably be the ones that feel most behind, so make sure you don’t just listen to the loud people! Maybe a survey monkey?

But I definitely like your idea of offering them lots of online resources to get practice with this stuff if they are having trouble. I definitely think they should be encouraged to do that as well. Keep track of what works so next semester you have something to build on.

Good luck!

Aunt Pythia


Dear Aunt Pythia,

I’m just starting a tenure track job at a well-known place. Another more prestigious university is currently considering giving me a tenured full professorship. At what point do I mention this? I don’t want to mention it too early, because of course it might turn out nothing happens. But it does also seems like an opportunity for a market correction. Variation: How would a tall handsome man handle this?

Wanting Info on Negotiating Contract Extension


I don’t think you can mention it until the offer is firm. I don’t think a tall man would either, however handsome.

The real question is, how do you handle the negotiation between the two places once they are both actively recruiting you? Some people would try to start a bidding war, some wouldn’t. But since I’m one of those people who wouldn’t, I’m not the right person to ask about how to do that. If you want advice about that, write back and I’ll get my good friend who is the king of bidding wars to weigh in.

Aunt Pythia


Please submit your well-specified, fun-loving, cleverly-abbreviated question to Aunt Pythia!

Categories: Aunt Pythia

Women not represented in clinical trials

September 26, 2014 13 comments

This recent NYTimes article entitled Health Researchers Will Get $10.1 Million to Counter Gender Bias in Studies spelled out a huge problem that kind of blows me away as a statistician (and as a woman!).

Namely, they have recently decided over at the NIH, which funds medical research in this country, that we should probably check to see how women’s health are affected by drugs, and not just men’s. They’ve decided to give “extra money” to study this special group, namely females.

Here’s the bizarre and telling explanation for why most studies have focused on men and excluded women:

Traditionally many investigators have worked only with male lab animals, concerned that the hormonal cycles of female animals would add variability and skew study results.

Let’s break down that explanation, which I’ve confirmed with a medical researcher is consistent with the culture.

If you are afraid that women’s data would “skew study results,” that means you think the “true result” is the result that works for men. Because adding women’s data would add noise to the true signal, that of the men’s data. What?! It’s an outrageous perspective. Let’s take another look at this reasoning, from the article:

Scientists often prefer single-sex studies because “it reduces variability, and makes it easier to detect the effect that you’re studying,” said Abraham A. Palmer, an associate professor of human genetics at the University of Chicago. “The downside is that if there is a difference between male and female, they’re not going to know about it.”

Ummm… yeah. So instead of testing the effect on women, we just go ahead and optimize stuff for men and let women just go ahead and suffer the side effects of the treatment we didn’t bother to study. After all, women only comprise 50.8% of the population, they won’t mind.

This is even true for migraines, where 2/3rds of migraine sufferers are women.

One reason they like to exclude women: they have periods, and they even sometimes get pregnant, which is confusing for people who like to have clean statistics (on men’s health). In fact my research contact says that traditionally, this bias towards men in clinical trials was said to protect women because they “could get pregnant” and then they’d be in a clinical trial while pregnant. OK.

I’d like to hear more about who is and who isn’t in clinical trials, and why.

Categories: modeling, news, rant, statistics

The business of public education

September 25, 2014 25 comments

I’ve been writing my book, and I’m on chapter 4 right now, which is tentatively entitled Feedback Loops In Education. I’m studying the enormous changes in primary and secondary education that have occurred since the “data-driven” educational reform movement started with No Child Left Behind in 2001.

Here’s the issue I’m having writing this chapter. Things have really changed in the last 13 years, it’s really incredible how much money and politics – and not education – are involved. In fact I’m finding it difficult to write the chapter without sounding like a wingnut conspiracy theorist. Because that’s how freaking nuts things are right now.

On the one hand you have the people who believe in the promise of educational data. They are often pro-charter schools, anti-tenure, anti-union, pro-testing, and are possibly personally benefitting from collecting data about children and then sold to commercial interests. Privacy laws are things to bypass for these people, and the way they think about it is that they are going to improve education with all this amazing data they’re collecting. Because, you know, it’s big data, so it has to be awesome. They see No Child Left Behind and Race To The Top as business opportunities.

On the other hand you have people who do not believe in the promise of educational data. They believe in public education, and are maybe even teachers themselves. They see no proven benefits of testing, or data collection and privacy issues for students, and they often worry about job security, and public shaming and finger-pointing, and the long term consequences on children and teachers of this circus of profit-seeking “educational” reformers. Not to mention that none of this recent stuff is addressing the very real problems we have.

As it currently stands, I’m pretty much part of the second group. There just aren’t enough data skeptics in the first group to warrant my respect, and there’s way too much money and secrecy around testing and “value-added models.” And the politics of the anti-tenure case are ugly and I say that even though I don’t think teacher union leaders are doing themselves many favors.

But here’s the thing, it’s not like there could never be well-considered educational experiments that use data and have strict privacy measures in place, the results of which are not saved to individual records but are lessons learned for educators, and, it goes without saying, are strictly non-commercial. There is a place for testing, but not as a punitive measure but rather as a way of finding where there are problems and devoting resources to it. The current landscape, however, is so split and so acrimonious, it’s kind of impossible to imagine something reasonable happening.

It’s too bad, this stuff is important.


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