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Guest post: Be more careful with the vagina stats in teaching

This is a guest post by Courtney Gibbons, an assistant professor of mathematics at Hamilton College. You can see her teaching evaluations on ratemyprofessor.com. She would like you to note that she’s been tagged as “hilarious.” Twice.

Lately, my social media has been blowing up with stories about gender bias in higher ed, especially course evaluations.   As a 30-something, female math professor, I’m personally invested in this kind of issue.  So I’m gratified when I read about well-designed studies that highlight the “vagina tax” in teaching (I didn’t coin this phrase, but I wish I had).

These kinds of studies bring the conversation about bias to the table in a way that academics can understand. We can geek out on experimental design, the fact that the research is peer-reviewed and therefore passes some basic legitimacy tests.

Indeed, the conversation finally moves out of the realm of folklore, where we have “known” for some time that students expect women to be nurturing in addition to managing the class, while men just need to keep class on track.

Let me reiterate: as a young woman in academia, I want deans and chairs and presidents to take these observed phenomena seriously when evaluating their professors. I want to talk to my colleagues and my students about these issues. Eventually, I’d like to “fix” them, or at least game them to my advantage. (Just kidding.  I’d rather fix them.)

However, let me speak as a mathematician for a minute here: bad interpretations of data don’t advance the cause. There’s beautiful link-bait out there that justifies its conclusions on the flimsy “hey, look at this chart” understanding of big data. Benjamin M. Schmidt created a really beautiful tool to visualize data he scraped from the website ratemyprofessor.com through a process that he sketches on his blog. The best criticisms and caveats come from Schmidt himself.

What I want to examine is the response to the tool, both in the media and among my colleagues.  USAToday, HuffPo, and other sites have linked to it, citing it as yet more evidence to support the folklore: students see men as “geniuses” and women as “bossy.” It looks like they found some screenshots (or took a few) and decided to interpret them as provocatively as possible. After playing with the tool for a few minutes, which wasn’t even hard enough to qualify as sleuthing, I came to a very different conclusion.

If you look at the ratings for “genius”  and then break them down further to look at positive and negative reviews separately, it occurs predominantly in negative reviews. I found a few specific reviews, and they read, “you have to be a genius to pass” or along those lines.

[Don’t take my word for it — search google for:

rate my professors “you have to be a genius”‘

and you’ll see how students use the word “genius” in reviews of professors. The first page of hits is pretty much all men.]

Here’s the breakdown for “genius”:

genius-neg

So yes, the data shows that students are using the word “genius” in more evaluations of men than women. But there’s not a lot to conclude from this; we can’t tell from the data if the student is praising the professor or damning him. All we can see that it’s a word that occurs in negative reviews more often than positive ones. From the data, we don’t even know if it refers to the professor or not.  

 

Similar results occur with “brilliant”:

brilliant-neg

Now check out “bossy” and negative reviews:

bossy-neg

Okay, wow, look at how far to the right those orange dots are… and now look at the x-axis.  We’re talking about fewer than 5 uses per million words of text.  Not exactly significant compared to some of the other searches you can do.

 

I thought that the phrase “terrible teacher” was more illuminating, because it’s more likely in reference to the subject of the review, and we’ve got some meaningful occurrences:

And yes, there is a gender imbalance, but it's not as great as I had feared. I'm more worried about the disciplinary break down, actually. Check out math -- we have the worst teachers, but we spread it out across genders, with men ranking 187 uses of "terrible teacher" per million words; women score 192. Compare to psychology, where profs receive a score of 110.  Ouch.

And yes, there is a gender imbalance, but it’s not as great as I had feared. I’m more worried about the disciplinary break down, actually. Check out math — we have the worst teachers, but we spread it out across genders, with men ranking 187 uses of “terrible teacher” per million words; women score 192. Compare to psychology, where profs receive a score of 110.  Ouch.

 

Who’s doing this reporting, and why aren’t we reading these reports more critically?  Journalists, get your shit together and report data responsibly.  Academics, be a little more skeptical of stories that simply post screenshots of a chart coupled with inciting prose from conclusions drawn, badly, from hastily scanned data.

Is this tool useless? No. Is it fun to futz around with? Yes.

Is it being reported and understood well? Resounding no!

I think even our students would agree with me: that’s just f*cked up.

Male nerd privilege

I recently read this essay by Laurie Penny (hat tip Jordan Ellenberg) about male nerd privilege. Her essay stemmed from comment 171 of Scott Aaronson’s blogpost about whether MIT professor Walter Lewin, who was found to be harassing women, should also have had his OpenCourseWare physics course taken down. Aaronson says no.

Personally, I think it should, because if I’m a woman who was harassed by that dude, I don’t want to see physics represented by my harasser up on MIT’s website; it would not make me feel welcome to the MIT community. Physics is a social community activity, after all, just like mathematics, and it is important to feel safe doing physics in that community. Plus the courses will be available on YouTube and other places, it’s not like the physics represented in the course has been lost to humanity.

Anyhoo, I did really want to talk about white male nerd privilege. Penny makes a bunch of good points in her essay, but I think she misses a big opportunity as well.

Quick summary. Aaronson talks about how he spent his youth and formative years terrified, since he was a shy nerd boy. Penny talks about how she did too, but then on top of it had to deal with structural sexism. Good point, and entirely true in my experience. Her best line:

At the same time, I want you to understand that that very real suffering does not cancel out male privilege, or make it somehow alright. Privilege doesn’t mean you don’t suffer, which, I know, totally blows.

So, I had two responses to her piece.

First was, she was complaining about her childhood, but she wasn’t even fat! I mean, GAWD. She was complaining about being too skinny, of all things. Plus it’s not clear whether or not she came from an abusive home. So I’ve got like, at least two complaints up on her. She thinks she’s had it bad?!

My point being, we can’t actually win when we count up all the ways we were miserable. Because the truth is, most people were actually miserable in their childhood, or soon after it, or at some time. And by comparing that stuff we just get stuck in a cycle of feeling competitively sorry for ourselves and pointing fingers. We need to sympathize, not only with our former selves, but with other people.

And although she does end the essay with the idea that we have to transcend all of our personal bruises and wrongs, and call each other human, and forget our resentments, it doesn’t seem like she’s giving us a path towards that.

Because, and here’s my second point, she doesn’t do the big thing of naming all of her privileges. Like, that nerds get good jobs. And that white people get loads of resources and attention and benefit of the doubt just for being white. At the end of the day, we are privileged to be sitting around talking about privilege. We are not worried about dying of hunger or exposure.

When Aaronson complained that naming male privilege is shaming, I’m prone to agree, at least if it’s done like this. What I’d propose is to figure out a way to talk about these structural problems in an aspirational way. How can we help make things fairer? How can we move this problem to the next level? Scott, you’re wicked smart, want to be on a taskforce with me?

Would it help if we gave it another name? Basic human rights, perhaps? Because that’s what we’re talking about, at the end of the day. The right to be free, to not get shot by the police, the right to hold a good job and care for your family, stuff like that.

Of course, there are plenty of people who are unwilling to move to the next level because they don’t acknowledge the structural racism, sexism, and other stuff at all. They don’t see the current situation as problematic. But on the other hand, there are loads of people who do, and Aaronson is clearly one of them.

As for problems for women in STEM, we’ve already studied this and we all know that both men and women are sexist, so it’s obviously not a blame game here. Instead, it’s a real cultural conundrum which we would like to approach thoughtfully and we’d like to make progress on as a team.

Aunt Pythia’s advice

Aunt Pythia has something in the works for you dear people, but it’s not quite ready yet, and you’ll have to wait another week. Rest assured, it will be worth it. And apologies to mathbabe.org subscribers who received an errant test post this week.

In the meantime, Aunt Pythia is going to write a quick column today from a Montreal hotel room after an amazing workshop yesterday which she will comment on later in the week.

So quick, get some tea and some flannel-lined flannel, because damn it’s wintery outside, all snowy and shit. Aunt Pythia’s about to spew her usual unreasonable nonsense!

This week in Montreal. From http://montrealgazette.com/news/local-news/city-slickers-take-your-time-on-slippery-snowy-roads

From earlier this week in Montreal. 

LET’S DO THIS PEOPLES!!! And please, even if you’ve got nothing interesting to say for yourself, feel free to make something up or get inspired by Google auto complete and then go ahead and:

ask Aunt Pythia your question at the bottom of the page!

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,

This may not really be an “Aunt Pythia” question. But could either you or Mathbabe comment on this article on sexism in academic science?

I can imagine many ways they could be misrepresenting the statistics, but I don’t know which.

No Bias, Really?

Dear No Bias,

I was also struck by the inflammatory tone and questionable conclusions of this article. But you know, controversy sells.

So, here are a couple of lines I’ll pull out. First:

Our country desperately needs more talented people in these fields; recruiting more women could address this issue. But the unwelcoming image of the sexist academy isn’t helping. Fortunately, as we have found in a thorough analysis of recent data on women in the academic workplace, it isn’t accurate, either.

And second:

Many of the common, negative depictions of the plight of academic women are based on experiences of older women and data from before the 2000s, and often before the 1990s. That’s not to say that mistreatment doesn’t still occur — but when it does, it is largely anecdotal, or else overgeneralized from small studies.

I guess right off the bat I’d ask, how are you collecting data? The data I have personally about sexist treatment at the hands of my colleagues hasn’t, to my knowledge, been put in any database. The sexist treatment I’ve witnessed for pretty much all of my female mathematics colleagues has, equally, never been installed in a database to my knowledge. So yeah, not convinced these people know what they are talking about. It’s famously hard to prove something doesn’t exist, especially when you don’t have a search algorithm.

One possibility for the data they seem to have: they interviewed people after the fact, perhaps decades after the fact. If that’s the case, then you’d expect more and better data on older women, and that’s what we are currently seeing. There is a lag on this data collection, in other words. That’s not the same as “it doesn’t exist.” A common mistake researchers make. They take the data as “objective truth” and forget that it’s a human process to collect it (or not collect it!). Think police shootings.

The article then goes on to talk about how the data for women in math and other science fields isn’t so bad in terms of retention, promotion, and other issues. For there I’d say, the women have already gone through a mighty selection process, so in general you’d expect them to be smarter than their colleagues, so in general their promotion rates should be higher, but they aren’t. So that’s also a sign of sexism.

I mean, whatever. That’s not actually what I claim is true, so much as another interpretation of this data. My overall point is that, they have some data, and they are making strong and somewhat outrageous claims which I can dismiss without much work.

I hope that helps!

Aunt Pythia

——

Dear Aunt Pythia,

In his November “Launchings” column, David Bressoud has presents some interesting data on differences between male and female college calculus students. As much as I’ve appreciated all of Bressoud’s careful explorations of mathematics education, I find I’m a bit irritated by his title, “MAA Calculus Study: Women Are Different,” because it appears to take the male experience as the norm.

Perhaps I was already annoyed because of a NYTimes op-ed, “Academic Science Isn’t Sexist”, in which Wendy Williams and Steven Ceci claim that “[w]e are not your father’s academy anymore,” and that the underrepresentation of women in math-intensive fields is “rooted in women’s earlier educational choices, and in women’s occupational and lifestyle preferences.” Here, too, the message seems to be “don’t worry about changing the academy — women are different from the norm, which is (naturally) that which works for men.”

My question for you, Aunt Pythia, is this: am I overreacting here?

I received my PhD in mathematics in 1984, and I’ve seen significant change for the better in the academy since then. Child care at AMS meetings? A crowd in the women’s rest room at same? Unthinkable when I started. But if women are still disproportionately “choosing” to go into other fields, might we look a little more closely at the environments in which girls and women are making their educational and “lifestyle” choices?

I welcome your thoughts. If you’re eager for more data analysis, I’d also love to hear your take on the paper by Williams, Ceci, and their colleagues.

Still One of the Underrepresented After All These Years

Dear SOotUAATY,

Without even reading that article, I can say without hesitation that yes, it’s a ridiculous title, and it’s infuriating and YOU ARE NOT OVERREACTING. To be clear, that is bold-faced, italicized, and all caps. I mean it.

The word “different” forces us to compare something to a baseline, and given that there is no baseline even mentioned, we are forced to guess at it, and that imposes the “man as default” mindset. Fuck that. I mean, if the title had been, “There are differences between male and female calculus students,” I would not have been annoyed, because even though “male” comes first, I’m not a stickler. I just want to acknowledge that if we mention one category, we mention the other as well.

To illustrate this a bit more, we don’t entitle a blog post “Whites are different” and leave it at that, because we’d be like, different from whom? From blacks? From Asians? From Asian-Americans? See how that works? You need to say different from some assumed baseline, and the assumed baseline has to be a cultural norm. And right now it’s white male. Which is arguable one reason that calculus students act differently when they are men (har!).

As for the other article, I already shit on that in the previous answer but I’m happy to do it once again. It’s bullshit, and I’m disappointed that the Times published it.

As for the article, I don’t have time now but I’ll take a look, thanks!

Aunt Pythia

——

Dear Aunt Pythia,

I am twenty years old, near the halfway point in my senior year of a mathematics BS at a large, well-regarded public university in the Northeast. I’ve been aiming my energies at graduate school, and I am now looking at PhD program applications. Most apps ask for two or three letters of recommendation from a faculty member who is familiar with your work. This poses a very big problem, because all of my professors hate me.

Okay, maybe it’s not quite like that. But I’ve had a really lousy time in the math department at LWRPUN. My fellow students are dispassionate, unresponsive, and unfriendly. My professors are dry, uncommitted to their students, and the ones who aren’t mathematically incompetent are lousy teachers. On top of all this, a crippling bureaucracy has prevented me countless times from taking classes I’m interested in (few as they are in this catalog), substituting instead ANOTHER REQUIRED SEMESTER OF ANALYSIS.

So I haven’t made any personal connections of the sort that might benefit me in the form of a letter of rec. My work hasn’t even been that good; my depression and anxiety (in general as well as re all this) have increasingly prevented me from completing even easy homework assignments. Nobody here has seen my best mathematical work, and for that matter, nobody anywhere else has either*.

And for four years, everyone I’ve come to with this gathering creeping progressively life-eating concern has given me the same old BS about You should really put yourself out there! and It’s just so important to go to your professor’s office hours! without considering maybe — I’ve tried, I really have.

What can I do, Aunt Pythia? I’m really passionate about mathematics, but I’m worried I won’t be able to pursue my studies without these magic papers.

Anxiously,
Reports Embargoed by Crummy Lecturers, Earnestly Seeking Solace

*I thankfully have a professor from an outside experience willing to write about my teaching credentials, but that one letter is surely not sufficient to show my potential as a graduate student and researcher.

Dear RECLESS,

I am afraid I will have to call bullshit on you, RECLESS. Plus your sign-off doesn’t actually spell anything.

Here’s the thing, there are no mathematically incompetent lecturers at large, well-regarded public universities. There are, in fact, mathematically very competent people who can’t get jobs at such places. Such is the pyramid-shaped job market of mathematics. So whereas I believe you when you say your lecturers have been uninspired, and uncommitted to their students, the fact that you added “mathematically incompetent” just makes me not believe you at all, in anything.

Here’s what I think is happening. You think you’re really into math, but you’ve never really understood your classes, nor have you understood that you’ve never understood your classes, because your self-image is that you’re already a mathematician, and that people have just not acknowledged your brilliance.

But that’s not how math actually works. Math is a social endeavor, where you have to communicate your ideas well enough for others to understand them, or else you aren’t doing math.

I’m not saying you haven’t had bad luck with teachers. It’s a real possibility. But there’s something else going on as well, and I don’t think you can honestly expect to go to the next level without sorting stuff out. In other words, even if you don’t love the teacher, if you loved the subject, got into it, and did the proofs, you’d still be getting adequate grades to ask for letters. The thing about writing letters, as a math prof, is that you don’t have to like the student personally to write a good letter, you just need to admire their skills. But since you can’t do that either, you won’t get good letters, and moreover I don’t think you’d deserve good letters. And therefore I don’t think you should go to grad school.

Suggestion: look carefully at your own behavior, figure out what it is you are doing that isn’t working. Maybe think of what you love about math, or about your own image of being a mathematician, and see if there’s something you really know you’re good at, and other people know it to, and develop that.

Good luck,

Aunt Pythia

——

Dearest Aunt Pythia,

I have a sex question for you! Kind of. You have to get through the boring back story first…I’m a 19 year old female physics major. I’m quiet, rather mousy, and awkward. A lot of the time I feel like I have more to prove than the boys do, because I’m a girl, and because of the aforementioned shyness.

People seem to automatically assume I’m unintelligent. I think I’m just as intelligent as the boys in my program, but I don’t come off that way! Point is, I want to be this cool, strong, independent, successful, respectable girl who doesn’t take shit from misogynistic people who assume I’m inferior.

However, I feel extremely guilty about my sexual preferences. I’m pretty submissive. I’d like power exchange in my relationships…hair pulling, bondage, spanking, being bossed around, the whole bit. I like to be dominated by men. Older men. Smart older men. Hopefully I’ve successfully conveyed my dilemma. I want to be respected by the men (and women, and others) I’m surrounded by in my academic life, but taken control of as a girlfriend.

Why does what I despise happening to me in an academic setting please me so much in a romantic/sexual one? Agh, I feel like such a bad girl! (and not in the arousing way…)

Help!
Much Love,
Conflicted

Dear Conflicted,

This is such a relief – finally, a sex question! – and it’s honestly one of the best questions I’ve ever gotten, ever, in Aunt Pythia or elsewhere. I’m so glad I can answer this for you.

It is absolutely not in conflict to want something in a sexual context that is abhorrent to you in normal life. It is in fact a well-known pattern! You shouldn’t feel at all weird about it! Lots – LOTS – of the submissives I’ve met are, in their day jobs, the boss, literally. They have companies and are extremely fancy and in control. And then they love to be bossed around and spanked. Seriously. If anything, my feeling is that your sexual proclivities point to being alpha in real life, but maybe I’m going overboard.

So yeah, no problem here. You are killing it. And in 3 or 4 years I want you to write back and explain to me how you’ve found an amazing lover who gives you what you want in the bedroom and worships your physics prowess outside it. There will, in fact, be people lining up for this role.

And those people in your program? Do your best to ignore them. Men are just impossibly arrogant at that age, but time will humble them somewhat even as your confidence will rise as you learn more. I’m not saying it ever evens out entirely but it does improve.

Also: find other women (and super cool men) to study with. Surround yourself with supportive people. Take note of obnoxious people and avoid them. Trade up with friends whenever possible.

Love always,

Aunt Pythia

——

Well, you’ve wasted yet another Saturday morning with Aunt Pythia! I hope you’re satisfied! Please if you could, ask me a question. And don’t forget to make an amazing sign-off, they make me very very happy.

Click here for a form or just do it now:

 

Neil deGrasse Tyson at NJPAC

Last night I went to the New Jersey Performing Arts Center (NJPAC) with my 12-year-old son to see Neil deGrasse Tyson, whom we both love from the Cosmos series. I also loved this rant on women and blacks in science:

So here’s what he talked about last night, which was stimulating and interesting. I’m not covering absolutely everything, of course, and I am doing my best to summarize what he said:

  • You can follow scientific progress by who gets to name things, because naming follows discovery.
  • For example, looking at the history of the discovery of the periodic table, you learn a lot. Except for Sweden, which just had a lucky break with some weird cave.
  • By this token, from 800 AD to around 1100 AD, mathematical and scientific advancements were happening in the Middle East (see for example the history of algebra and mathematician Muḥammad ibn Mūsā al-Khwārizmī, who invented the terms algebra and algorithm). Then some imam decided it was anti-religious to do anything like that, and progress – scientific and otherwise – stopped.
  • Cultures that embrace science have more growth.
  • In the U.S., about half of the people don’t acknowledge evolution, and that’s a bad sign for our future.
  • In fact we are a hugely prolific scientific force, like Europe and Japan, but unlike them, our power is shrinking rather than expanding.
  • We should go back to the 1960’s, at least in terms of the way we promoted and dreamed about scientific progress, and bottle up the energy and enthusiasm, and bring it back to today.
  • Space flight is a great thing and we should reinvest in it as an inspiration for science in this country and in the world.
  • We should stay curious, and investigate things we don’t understand, and talk to people about their beliefs even if we don’t agree. Childlike and insatiable curiosity and wonderment is the goal.
Categories: education, women in math

What the fucking shit, Barbie?

I’m back from Haiti! It was amazing and awesome, and please stand by for more about that, with cultural observations and possibly a slide show if you’re all well behaved.

Today, thanks to my math camp buddy Lenore Cowen, I am going to share with you an amazing blog post by Pamela Ribon. Her post is called Barbie Fucks It Up Again and it describes a Barbie book entitled Barbie: I Can Be a Computer Engineer

The other book is called "I Can Be an Actress"

The other book is called “I Can Be an Actress”

Just to give you an idea of the plot, Barbie’s sister finds Barbie engaged on a project on her computer, and after asking her about it, Barbie responds:

“I’m only creating the design ideas,” Barbie says, laughing. “I’ll need Steven and Brian’s help to turn it into a real game!”

To which blogger Pamela Ribon comments:
What the fucking shit, Barbie?
Update: Please check out the amazing Amazon reviews of this book (hat tip Chris Wiggins).
BEST UPDATE EVER (hat tip Marko): BARBIE CAN CODE REMIXED

StemFeminist

I found the website StemFeminist.com 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

Interview with a high school principal on the math Common Core

In my third effort to understand the Common Core State Standards (CC) for math, I interviewed an old college friend Kiri Soares, who is the principal and co-founder of the Urban Assembly Institute of Math and Science for Young Women. Here’s a transcript of the interview which took place earlier this month. My words are in italics below.

——

How are high school math teachers in New York City currently evaluated?

Teachers are now evaluated on 2 things:

  1. First, measures of teacher practice, which are based on observations, in turn based on some rubric. Right now it’s the Danielson Rubric. This is a qualitative measure. In fact it is essentially an old method with a new name.
  2. Second, measures of student learning, that is supposed to be “objective”. Overall it is worth 40% of the teacher’s score but it is separated into two 20% parts, where teachers choose the methodology of one part and principals choose the other. Some stuff is chosen for principals by the city. Any time there is a state test we have to choose it. In terms of the teachers’ choices, there are two ways to get evaluated: goals or growth. Goals are based on a given kid, and the teachers can guess they will get a certain slightly lower score or higher score for whatever reason. Otherwise, it’s a growth-based score. Teachers can also choose from an array of assessments (state tests, performance tests, and third party exams). They can also choose the cohort (their own kids/ the grade/the school). The city also chose performance tasks in some instances.

Can you give me a concrete example of what a teacher would choose as a goal?

At the beginning of year you give diagnostic tests to students in your subject. Based on what a given kid scored in September, you extrapolate a guess for their performance in the June test. So if a kid has a disrupted homelife you might guess lower. Teacher’s goal setting is based on these teachers’ guesses.

So in other words, this is really just a measurement of how well teachers guess?

Well they are given a baseline and teachers set goals relative to that, but yes. And they are expected to make those guesses in November, possibly well before homelife is disrupted. It definitely makes things more complicated. And things are pretty complicated. Let me say a bit more.

The first three weeks of school are all testing. We test math, social studies, science, and English in every grade, and overall it depending on teacher/principal selections it can take up to 6 weeks, although not in a given subject. Foreign language and gym teachers also getting measured, by the way, based on those other tests. These early tests are diagnostic tests.

Moreover, they are new types of tests, which are called performance-based assessments, and they are based on writing samples with prompts. They are theoretically better quality because they go deeper, the aren’t just bubble standardized tests, but of course they had no pre-existing baseline (like the state tests) and thus had to be administered as diagnostic. Even so, we are still trying to predict growth based on them, which is confusing since we don’t know how to predict performance on new tests. Also don’t even know how we can consistently grade such essay-based tests- despite “norming protocols”, which is yet another source of uncertainty.

How many weeks per year is there testing of students?

The last half of June is gone, a week in January, and 2-3 weeks in the high school in the beginning per subject. That’s a minimum of 5 weeks per subject per year, out of a total of 40 weeks. So one eighth of teacher time is spent administering tests. But if you think about it, for the teachers, it’s even more. They have to grade these tests too.

I’ve been studying the rhetoric around the CC. So far I’ve listened to Diane Ravitch stuff, and to Bill McCallum, the lead writer of the math CC. They have very different views. McCallum distinguished three things, which when they are separated like that, Ravitch doesn’t make sense.

Namely, he separates standards, curriculum, and testing. People complain about testing and say that CC standards make testing easier, and we already have too much testing, so CC is a bad thing. But McCallum makes this point: good standards also make good testing easier.

What do you think? Do teachers see those as three different things? Or is it a package deal, where all three things rolled into one in terms of how they’re presented?

It’s much easier to think of those three things as vertices of a triangle. We cannot make them completely isolated, because they are interrelated.

So, we cannot make the CC good without curriculum and assessment, since there’s a feedback loop. Similarly, we cannot have aligned curriculum without good standards and assessment, and we cannot have good tests without good standards and curriculum. The standards have existed forever. The common core is an attempt to create a set of nationwide standards. For example, without a coherent national curriculum it might seem OK to teach creationism in place of evolution in some states. Should that be OK?

CC is attempting to address this, in our global economy, but it hasn’t even approached science for clear political reasons. Math and English are the least political subjects so they started with those. This is a long time coming, and people often think CC refers to everything but so far it’s really only 40% of a kid’s day. Social studies CC standards are actually out right now, but they are very new.

Next, the massive machine of curriculum starts getting into play, as does the testing. I have CC standards and the CC-aligned test, but not curriculum.

Next, you’re throwing into the picture teacher evaluation aligned to CC tests. Teachers are freaking out now – they’re thinking, my curriculum hasn’t been CC-aligned for many years, what do I do now? By the way, importantly, none of the high school curriculum in NY State is actually CC-aligned now. DOE recommendations for the middle school happened last year, and DOE people will probably recommend this year for high school, since they went into talks with publication houses last year to negotiate CC curriculum materials.

The real problem is this: we’ve created these new standards to make things more difficult and more challenging without recognizing where kids are in the present moment. If I’m a former 5th grader, and the old standards were expecting something from me that I got used to, and it wasn’t very much, and now I’m in 6th grade, and there are all these raised expectations, and there’s no gap attention.

Bottomline, everybody is freaking out – teachers, students, and parents.

Last year was the first CC-aligned ELA and math tests. Everybody failed. They rolled out the test before any CC curriculum.

From the point of view of NYC teachers, this seems like a terrorizing regime, doesn’t it?

Yes, because the CC roll-out is rigidly tied to the tests, which are in turn rigidly tied to evaluations of teachers. So the teachers are worried they are automatically going to get a “failure” on that vector.

Another way of saying this is that, if teacher evaluations were taken out of the mix, we’d have a very different roll-out environment. But as it is, teachers are hugely anxious about the possibility that their kids might fail both the city and state tests, and that would give the teacher an automatic “failure” no matter how good their teacher observations are.

So if I’m a special ed teacher of a bunch of kids reading at 4th and 5th grade level even through they’re in 7th grade, I’m particularly worried with the introduction of the new and unknown CC-aligned tests.

So is that really what will happen? Will all these teachers get failing evaluation scores?

That’s the big question mark. I doubt it there will be massive failure though. I think given that the scores were so clustered in the middle/low muddle last year, they are going to add a curve and not allow so many students to fail.

So what you’re pointing out is that they can just redefine failure?

Exactly. It doesn’t actually make sense to fail everyone. Probably 75% of the kids got 2’s or 1’s out of a 4 point scale. What does failure mean when everyone fails? It just means the test was too hard, or that what the kids were being taught was not relevant to the test.

Let’s dig down to the the three topics. As far as you’ve heard from the teachers, what’s good and bad about CC?

My teachers are used to the CC. We’ve rolled out standards-based grading three years ago, so our math and ELA teachers were well adjusted, and our other subject teachers were familiar. The biggest change is what used to be 9th grade math is now expected of the 8th grade. And the biggest complaint I’ve heard is that it’s too much stuff – nobody can teach all that. But that’s always been true about every set of standards.

Did they get rid of anything?

Not sure, because I don’t know what the elementary level CC standards did. There was lots of shuffling in the middle school, and lots of emphasis on algebra and algebraic thinking. Maybe they moved data and stats to earlier grades.

So I believe that my teachers in particular were more prepared. In other schools, where teachers weren’t explicitly being asked to align themselves to standards, it was a huge shock. For them, it used to be solely about Regents, and also Regents exams are very predictable and consistent, so it was pretty smooth sailing.

Let’s move on to curriculum. You mentioned there is no CC-aligned curriculum in NY. I also heard NY state has recently come out against the CC, did you hear that?

Well what I heard is that they previously said they this year’s 9th graders (class of 2017) would be held accountable but now the class of 2022 will be. So they’ve shifted accountability to the future.

What does accountability mean in this context?

It means graduation requirements. You need to pass 5 Regents exams to graduate, and right now there are two versions of some of those exams: one CC-aligned, one old-school. The question is who has to pass the CC-aligned versions to graduate. Now the current 9th grade could take either the CC-aligned or “regular” Regents in math.

I’m going to ask my 9th grade students to take both so we can gather information, even though it means giving them 3 extra hours of tests. Most of my kids pass 2 Regents in 9th grade, 2 in 10th, and 3 in 11th, and then they’re supposed to be done. They only take those Regents tests in senior year that they didn’t pass earlier.

What are the good and bad things about testing?

What’s bad is how much time is lost, as we’ve already said. And also, it’s incredibly stressful. You and I went to school and we had one big college test that was stressful, namely the SAT. In terms of us finishing high school, that was it. For these kids it’s test, test, test, test. I don’t think it’s actually improved the quality of college students across the country. 20 years ago NY was the only one that had extra tests except California achievement tests, which I guess we sometimes took as well.

Another way to say it is that we did take some tests but it didn’t take 5 weeks.

And it wasn’t high stakes for the teacher!

Let’s go straight there: what are the good/bad things for the teachers with all these tests?

Well it definitely makes the teachers more accountable. Even teachers think this: there is a cadre of protected teachers in the city, and the principals didn’t want to take the time to get rid of them, so they’d excess them out of the schools, and they would stay in the system.

Now with testing it has become much more the principal’s responsibility to get rid of bad teachers. The number of floating teachers is going down.

How did they get rid of the floaters?

A lot of different ways. They made them go into the schools, take interviews, they made their quality of life not great, and a lot if them left or retired or found jobs. Principals took up the mantle as well, and they started to do due diligence.

Sounds like the incentive system for over-worked principals was wrong.

Yes, although the reason it became easier for the principals is because now we have data. So if you’re coming in as ineffective and I also have attendance data and observation data, I can add my observational data (subjective albeit rubric based) and do something.

If I may be more skeptical, it sounds like this data gathering was used as a weapon against teachers. There were probably lots of good teachers that have bad numbers attached to them that could get fired if someone wanted them to be fired.

Correct, except those good teachers generally have principals who protect them.

You could give everyone a bad number and then fire the people you want, right?

Correct.

Is that the goal?

Under Bloomberg it was.

Is there anything else you want to mention? 

I think testing needs to be dialed down but not disappear. Education is a bi-polar pendulum and it never stops in the middle. We’re on an extreme but let’s not get rid of everything. There is a place for testing.

Let’s get our CC standards, curriculum, and testing reasonable and college-aligned and let’s keep it reasonable. Let’s do it with standards across states and let’s make sure it makes sense.

Also, there are some new tests coming out, called PARCC assessments, that are adaptive tests aligned to the CC. They are supposed to replace Regents down the line and be national.

Here’s what bothers me about that. It’s even harder to investigate the experience of the student with adaptive tests.

I’m not sure there’s enough technology to actually do this anyway very soon. For example, we were given $10,000 for 500 student. That’s not going to go far unless it takes 2 weeks to administer the test. But we are investing in our technology this year. For example, I’m looking forward  to buying textbooks and get my updates pushed instead of having to buy new books every year.

Last question. They are redoing the SAT because rich kids are doing so much better. Are they just trying to get in on the test prep game? Because, here’s the thing, there’s no test that can’t be gamed that’s also easy to grade. It’s gotta depend on the letters and grades. We keep trying to shortcut that.

Listen, this is what I tell the kids. What’s going to matter to you is the letter of recommendation, so don’t be an jerk to your fellow students or to the teachers. Next, are you going to be able to meet the minimum requirements? That’s what the SAT is good for. It defines a lower bound.

Is it a good lower bound though?

Well, I define the lower bound as 1000 in total. My kids can target that. It’s a reasonable low bar.

To what extent do your students – mostly inner-city, black girls interested in math and science – suffer under the wholly gamed SAT system?

It serves to give them a point of self-reference with the rest of the country. You have to understand, they, like most kids in the nation, don’t have a conception of themselves outside of their own experience. The SAT serves that purpose. My kids, like many others, have the dream of Ivy League minus the understanding of where they actually stand.

So you’re saying their estimates of their chances are too high?

Yes, oftentimes. They are the big fish in a well-defined pond. At the very least, The SAT helps give them perspective.

Thanks so much for your time Kiri.

Upcoming talks

A few months ago I gave a talk entitled “Start Your Own Netflix” talk that was part of the MAA Distinguished Lecture Series, the slides for which are available here and a short video version here.

Today I’m planning to modify that talk so I can give a longer and more technical version of it on Friday morning at the Department of Mathematical Science of Worcester Polytechnic Institute, where I’ve been invited to speak by Suzy Weekes.

In about a month I’m going to Berkeley for a week to give a so-called MSRI-Evans talk on Monday, February 24th, at 4pm, thanks to the kind invitation of Lauren Williams. I still haven’t decided whether to give a “The World Is Going To Hell” talk, which would be kind of the technical version of my book (and which I gave at Harvard’s IQSS recently), or whether I should give yet another version of the Netflix talk, which is cool and technical but not as doomsday. If you’re planning to attend please voice your opinion!

Finally, I’m hoping to join in a meeting of some manifestation of the Noetherian Ring while I’m at Berkeley. This is a women in math group that was started when I was an undergrad there, back in the middle ages, in something like 1992. It’s where I gave my first and second math talks and there was always free pizza. It really was a great example of how to create a supportive environment for collaborative math.

Categories: math, women in math

I’m already fat so I may as well be smart

I seem to be in a mood this week for provocative posts about body image and appearance (maybe this is what happens when I skip an Aunt Pythia column). Apologies to people who came for math talk.

I just wanted to mention something positive about the experience of being fat all my life, but especially as a school kid. Because just to be clear, this isn’t a phase. I’ve been pudgy since I was 2 weeks old. And overall it kind of works for me, and I’ll say why.

Namely, being a fat school kid meant that I was so uncool, so outside of normal social activity with boys and the like, that I was freed up to be as smart and as nerdy as I wanted, with very little stress about how that would “look”. You’re already fat, so why not be smart too? You’re not doing anything else, nobody’s paying attention to you, and there’s nothing to gossip about, so might as well join the math team.

It’s really a testament to both the pressure to be thin and the pressure to conform intellectually, i.e. not be a nerd, when you’re a young girl: they are both intense and super unpleasant. The happy truth is, one can be cover for the other. More than that, really: being fat (or “overweight” for people who are squeamish about the word “fat”) has opened up many doors that I honestly think would have, or at least could have, remained shut had I been more socially acceptable.

Going back to dress code at work for a moment: while people claim that corporate dress codes are meant to keep our minds off of sex, that is clearly a huge lie when it comes to many categories of women’s work clothes. Who are we kidding? The mere fact that many women wear high heels to work kind of says it all. And that’s fine, but let’s freaking acknowledge it.

On the other hand, it’s pretty hard to look sexy in a plus-sized suit (although not impossible), and the idea of high heels at work is just nuts. This ends up being a weirdly good thing for me, though: people take me more seriously because I have taken myself out of the sex game altogether – or at least the traditional sex game.

By the way, I’m not saying all fat women have the same perspective on it. I’m lucky enough to have figured out pretty early on how to separate other people’s projected feelings about my body from my own feelings. I am an observer of fat hatred, in other words. That doesn’t make me entirely insulated but it does give me one critical advantage: I have a lot of time on my hands to do stuff that I might otherwise spend fretting about my body.

It also might help partly explain why some girls get on the math team and others don’t. Being fat is something you don’t have control over (the continuing and damaging myth that each person does have control over it notwithstanding) but joining the math team is something you do have control over. And if you aren’t already excluded for some other reason (being fat is one but by no means the only way this could happen of course), you might not want to start that whole thing intentionally. Just a theory.

Categories: rant, women in math

On being a mom and a mathematician: interview by Lillian Pierce

This is a guest post by Lillian Pierce, who is currently a faculty member of the Hausdorff Center for Mathematics in Bonn, and will next year join the faculty at Duke University.

I’m a mathematician. I also happen to be a mother. I turned in my Ph.D. thesis one week before the due date of my first child, and defended it five weeks after she was born. Two and a half years into my postdoc years, I had my second child.

Now after a few years of practice, I can pretty much handle daily life as a young academic and a parent, at least most of the time, but it still seems like a startlingly strenuous existence compared to what I remember of life as just a young academic, not a parent.

Last year I was asked by the Association for Women in Mathematics to write a piece for the AWM Newsletter about my impressions of being a young mother and getting a mathematical career off the ground at the same time. I suggested that instead I interview a lot of other mathematical mothers, because it’s risky to present just one view as “the way” to tackle mathematics and motherhood.

Besides, what I really wanted to know was: how is everyone else doing this? I wanted to pick up some pointers.

I met Mathbabe about ten years ago when I was a visiting prospective graduate student and she was a postdoc. She made a deep impression on me at the time, and I am very happy that I now have the chance to interview her for the series Mathematics+Motherhood, and to now share with you our conversation.

LP: Tell me about your current work.

CO: I am a data scientist working at a small start-up. We’re trying to combine consulting engagements with a new vision for data science training and education and possibly some companies to spin off. In the meantime, we’re trying not to be creepy.

LP: That sounds like a good goal. And tell me a bit about your family.

CO: I have three kids. I got pregnant with my first son, who’s 13 now, soon after my PhD. Then I had a second child 2 years later, also while I was a postdoc. I also have a 4 year old, whom I had when I was working in finance.

LP: Did you have any notions or worries in advance about how the growth of your family would intersect with the growth of your career?

CO: I absolutely did worry about it, and I was right to worry about it, but I did not hesitate about whether to have children because it was just not a question to me about how I wanted my life to proceed. And I did not want to wait until I was tenured because I didn’t want to risk being infertile, which is a real risk. So for me it was not an option not to do it as a woman, forget as a mathematician.

LP: What was it like as a postdoc with two very young children?

CO: On the one hand I was hopeful about it, and on the other hand I was incredibly disappointed about it. The hopeful part was that the chair of my department was incredibly open to negotiating a maternity leave for postdocs, and it really was the best maternity policy that I knew about: a semester off of teaching for each baby and in total an extra year of the postdoc, since I had 2 babies. So I ended up with four years of postdoc, which was really quite generous on the one hand, but on the other hand it really didn’t matter at all. Not “not at all”—it mattered somewhat but it simply wasn’t enough to feel like I was actually competing with my contemporaries who didn’t have children. That’s on the one hand completely obvious and natural and it makes sense, because when you have small children you need to pay attention to them because they need you—and at the same time it was incredibly frustrating.

LP: It’s interesting because it’s not that you were saying “I won’t be able to compete with my contemporaries over the course of my life,” but more “I can’t compete right now.”

CO: Exactly, “I can’t compete right now” with postdocs without children. I realize—and this is not a new idea—that mathematics as a culture frontloads entirely into those 3 or 4 years after you get your PhD. Ultimately it’s not my fault, it’s not women’s fault, it’s the fault of the academic system.

LP: What metrics could departments use to be thinking more about future potential?

CO: I actually think it’s hard. It’s not just for women that it should change. It’s for the actual culture of mathematics. Essentially, the system is too rigid. And it’s not only women who get lost. The same thing that winnows the pool down right after getting a PhD—it’s a whittling process, to get rid of people, get rid of people, get rid of people until you only have the elite left—that process is incredibly punishing to women, but it’s also incredibly punishing to everybody. And moreover because of the way you get tenure and then stay in your field for the rest of your life, my feeling is that mathematics actually suffers. The reason I say this is because I work in industry now, which is a very different system, and people can reinvent themselves in a way that simply does not happen in mathematics.

LP: Do you think industry, in terms of the young career phase, gets it closer to “right” than academia currently does?

CO: Much closer to right. It’s a brutal place, don’t get me wrong, it’s brutal. I’m not saying it’s a perfect system by any stretch of the imagination. But the truth is in industry you can have a 3 year stint somewhere that is a mistake. Forget having kids, you can have a 3 year stint that was just a mistake for you. You can say “I had a bad boss and I left that place and I got a new job” and people will say “Ok.” They don’t care. One thing that I like about it is the ability to reinvent yourself. And I don’t think you see that in math. In math, your progress is charted by your publication record at a granular level. And if you’re up for tenure and there’s a 3 year gap where you didn’t publish, even if in the other years you published a lot, you still have to explain that gap. It’s like a moral responsibility to keep publishing all the time.

LP: How are you measured in industry?

CO: In industry it’s the question “what have you done for me,” and “what have you done for me lately.” It’s a shorter-term question, and there are good elements to that. One of the good elements is that as a woman you can have a baby or a couple babies and then you can pick up the slack, work your ass off, and you can be more productive after something happens. If someone gets sick, people lower their expectations for that person for some amount of time until they recover, and then expectations are higher. Mathematics by contrast has frontloaded all of the stress, especially for the elite institutions, into the 3 or 4 years to get the tenure track offer and then the next 6 years to get tenure. And then all the stress is gone. I understand why people with tenure like that. But ultimately I don’t think mathematics gets done better because of it. And certainly when the question arises “why don’t women stay in math,” I can answer that very easily: because it’s not a very good place for women, at least if they want kids.

LP: You mention on your blog that your mother is an unapologetic nerd and computer scientist; the conclusion you drew from that was that it was natural for you not to doubt that your contributions to nerd-dom and science and knowledge would be welcomed. How do you think this experience of having a mother like that inoculated you?

CO: One of the great gifts that my mother gave me as a Mother Nerd was the gift of privacy—in the sense that I did not scrutinize myself. First of all she was role-modeling something for me, so if I had any expectations it would be to be like my mom. But second of all she wasn’t asking me to think about that. I think that was one of the rarest things I had, the most unusual aspect of my upbringing as a girl. Very few of the girls that I know are not scrutinized. My mother was too busy to pay attention to my music or my art or my math. And I was left alone to decide what I wanted to do—it wasn’t about what I was good at or what other people thought of my progress. It was all about answering the question, what did I want to do. Privacy for me is having elbow space to self-define.

LP: Do you think it’s harder for parents to give that space to girls than to boys?

CO: Yes I do, I absolutely do. It’s harder and for some reason it’s not even thought about. My mother also gave me the gift of not feeling at all guilty about putting me into daycare. And that’s one of my strongest lessons, is that I don’t feel at all guilty about sending my kids to daycare. In fact I recently had the daycare providers for my 4-year-old all over for dinner, and I was telling them in all honesty that sometimes I wish I could be there too, that I could just stay there all day, because it’s just a wonderful place to be. I’m jealous of my kids. And that’s the best of all worlds. Instead of saying “oh my kid is in daycare all day, I feel bad about that,” it’s “my kid gets to go to daycare.”

LP: Where did this ability not to scrutinize come from? Where did your mother get this?

CO: I don’t know. My mother has never given me advice, she just doesn’t give advice. And when I ask her to, she says “you know more about your life than I do.”

LP: How do you deal with scrutiny now?

CO: It’s transformed as I’ve gotten older. I’ve gotten a thicker skin, partly from working in finance. I’ve gotten to the point now where I can appreciate good feedback and ignore negative feedback. And that’s a really nice place to be. But it started out, I believe, because I was raised in an environment where I wasn’t scrutinized. And I had that space to self-define.

LP: The idea of pushing back against scrutiny to clear space for self-definition is inspiring for adults as well.

CO: Women in math, especially with kids, give yourself a break. You’re under an immense amount of pressure, of scrutiny. You should think of it as being on the front lines, you’re a warrior! And if you’re exhausted, there’s a reason for it. Please go read Radhika Nagpal’s Scientific American blog post (“The Awesomest 7-Year Postdoc Ever”) for tips on how to deal with the pressure. She’s awesome. And the last thing I want to say is that I never stopped loving math. Cardinal Rule Number 1: Before all else, don’t become bitter. Cardinal Rule Number 2: Remember that math is beautiful.

Categories: math, women in math

Survivorship bias for women in men’s fields

I like this essay written by Annie Gosfield, a self-described “composeress”, which is her word to mean a female composer. She finds it slightly absurd to be singled out for her femaleness. Her overall take on being a woman in a man’s world is refreshing, and resonates with me as a woman in math and technology.

From her essay:

I’ve never considered myself a “woman composer,” but I suspect that over the years being female has helped more than it’s hurt. Being a woman (and having high hair) has made me easier to recognize, easier to remember and has spared me from fitting into the generic description of a composer: “medium build, dark hair, glasses, beard.” I will admit to liking the invented honorific term “composeress.” (It sounds archaic, grand, and slightly ridiculous, just as a gender-specific title for a composer should.)

So, great for her, and wonderful that from her perspective she feels propelled rather than suffocated by her otherness status. To some extent I agree from my own experience.

But having said that, it doesn’t mean that other women, possibly many other women, haven’t been squeezed out, or have selected out, because of their female status. After all, we hear way more from the people who stay and “succeed”, which tends to give us massive survivorship bias.

Indeed, and to be nerdy and true to form, we can almost think about measuring the extent to which there is a weeding-out effect of women by asking the survivors the extent to which they identify as “women” versus the population at large. I think we’d find that the women who survive in nearly all-male environments have developed, or were born with, coping mechanisms which allow them to ignore their own otherness.

I know that was true of me – when I was in grad school at Harvard, I went through a distinct phase of wanting to wear men’s clothing, or at least gender neutral clothing – so jeans, t-shirts, leather shoes, never dresses – to be externally more consistent with how I felt inside. Not that I was sexually identified with men, but that I didn’t want to be seen as primarily feminine. Instead I wanted to be seen as primarily a mathematician.

Does it make me a freak, to wear men’s clothing and (sometimes) wish I could grow a beard? Possibly, although over time it’s changed, and nowadays I take pride in my femininity, and in fact I think much of my power emanates from it.

But it does give me pause when I hear successful women in men’s fields talking about how great it is to be a woman and how surprising all the attention is. We still seem to be contorting ourselves in an effort to not seem too womanly, and this makes me think it’s entirely un-coincidental, and possibly a crucial part of what allows us to succeed. Besides talent and hard work, of course. And I don’t think it’s undue attention at all – I think it’s just something we train ourselves not to consider because focusing on it too much could be paralyzing.

By the way, I’m not doing justice to Annie Gosfield’s essay, which you should read in its entirety and has nuanced things to say about otherness in the field of composing.

Categories: women in math

Radhika Nagpal is a role model for fun people everywhere

Can I hear an amen for Radhika Nagpal, the brave woman who explained to the world recently how she lived through being a tenure-track professor at Harvard without losing her soul?

You should really read Nagpal’s guest blogpost from Scientific American (hat tip Ken Ribet) yourself, but here’s just a sneak preview, namely her check list of survival tactics that she describes in more detail later in the piece:

  • I decided that this is a 7-year postdoc.
  • I stopped taking advice.
  • I created a “feelgood” email folder.
  • I work fixed hours and in fixed amounts.
  • I try to be the best “whole” person I can.
  • I found real friends.
  • I have fun “now”.

I really love this list, especially the “stop taking advice” part. I can’t tell you how much crap advice you get when you’re a tenure-track woman in a technical field. Nagpal was totally right to decide to ignore it, and I wish I’d taken her advice to ignore people’s advice, even though that sounds like a logical contradiction.

What I like the most about her list was her insistence on being a whole person and having fun – I have definitely had those rules since forever, and I didn’t have to make them explicit, I just thought of them as obvious, although maybe it was for me because my alternative was truly dark.

It’s just amazing how often people are willing to make themselves miserable and delay their lives when they’re going for something ambitious. For some reason, they argue, they’ll get there faster if they’re utterly submissive to the perceived expectations.

What bullshit! Why would anyone be more efficient at learning, at producing, or at creating when they’re sleep-deprived and oppressed? I don’t get it. I know this sounds like a matter of opinion but I’m super sure there’ll be some study coming out describing the cognitive bias which makes people believe this particular piece of baloney.

Here’s some advice: go get laid, people, or whatever it is that you really enjoy, and then have a really good night’s sleep, and you’ll feel much more creative in the morning. Hell, you might even think of something during the night – all my good ideas come to me when I’m asleep.

Even though her description of tenure-track life resonates with me, this problem, of individuals needlessly sacrificing their quality of life, isn’t confined to academia by any means. For example I certainly saw a lot of it at D.E. Shaw as well.

In fact I think it happens anywhere where there’s an intense environment of expectation, with some kind of incredibly slow-moving weeding process – academia has tenure, D.E. Shaw has “who gets to be a Managing Director”. People spend months or even years in near-paralysis wondering if their superiors think they’re measuring up. Gross!

Ultimately it happens to someone when they start believing in the system. Conversely the only way to avoid that kind of oppression is to live your life in denial of the system, which is what Nagpal achieved by insisting on thinking of her tenure-track job as having no particular goal.

Which didn’t mean she didn’t work hard and get her personal goals done, and I have tremendous respect for her work ethic and drive. I’m not suggesting that we all get high-powered positions and then start slacking. But we have to retain our humanity above all.

Bottomline, let’s perfect the art of ignoring the system when it’s oppressive, since it’s a useful survival tactic, and also intrinsically changes the system in a positive way by undermining it. Plus it’s way more fun.

Categories: math, musing, women in math

Book out for early review

I’m happy to say that the book I’m writing with Rachel Schutt called Doing Data Science is officially out for early review. That means a few chapters which we’ve deemed “ready” have been sent to some prominent people in the field to see what they think. Thanks, prominent and busy people!

It also means that things are (knock on wood) wrapping up on the editing side. I’m cautiously optimistic that this book will be a valuable resource for people interested in what data scientists do, especially people interested in switching fields. The range of topics is broad, which I guess means that the most obvious complaint about the book will be that we didn’t cover things deeply enough, and perhaps that the level of pre-requisite assumptions is uneven. It’s hard to avoid.

Thanks to my awesome editor Courtney Nash over at O’Reilly for all her help!

And by the way, we have an armadillo on our cover, which is just plain cool:

book

Guest post: Kaisa Taipale visualizes mathematics Ph.D.’s emigration patterns

This is a guest post by Kaisa Taipale. Kaisa got a BS at Caltech, a Ph.D. in math at the University of Minnesota, was a post-doc at MSRI, an assistant professor at St. Olaf College 2010-2012, and is currently visiting Cornell, which is where I met here a couple of weeks ago, and where she told me about her cool visualizations of math Ph.D. emigration patterns and convinced her to write a guest post. Here’s Kaisa on a bridge:

Kaisa

Math data and viz

I was inspired by this older post on Mathbabe, about visualizing the arXiv postings of various math departments.

It got me thinking about tons of interesting questions I’ve asked myself and could answer with visualizations: over time, what’s been coolest on the arXiv? are there any topics that are especially attractive to hiring institutions? There’s tons of work to do!

I had to start somewhere though, and as I’m a total newbie when it comes to data analysis, I decided to learn some skills while focusing on a data set that I have easy non-technical access to and look forward to reading every year. I chose the AMS Annual Survey. I also wanted to stick to questions really close to my thoughts over the last two years, namely the academic job search.

I wanted to learn to use two tools, R and Circos. Why Circos? See the visualizations of college major and career path here – it’s pretty! I’ve messed around with a lot of questions, but in this post I’ll look at two and a half.

Graduating PhDs

Where do graduating PhDs from R1 universities end up, in the short term? I started with graduates of public R1s, as I got my PhD at one.

EmploymentOfPublicR1Grad

The PhD-granting institutions are colored green, while academic institutions granting other degrees are in blue. Purple is for business, industry, government, and research institutions. Red is for non-U.S. employment or people not seeking — except for the bright red, which is still seeking. Yellow rounds things out at unknown. Remember, these figures are for immediate plans after graduation rather than permanent employment.

While I was playing with this data (read “learning how to use the reshape and ggplot2 packages”) I noticed that people from private R1s tend to end up at private R1s more often. So I graphed that too.

EmploymentOfPrivateR1Grad

Does the professoriate in the audience have any idea if this is self-selection or some sort of preference on the part of employers? Also, what happened between 2001 and 2003? I was still in college, and have no idea what historical events are at play here.

Where mathematicians go

For any given year, we can use a circular graph to show us where people go. This is a more clumped version of the above data from 2010 alone, plotted using Circos. (Supplemental table E.4 from the AMS report online.)

2010RoughByType

The other question – the question current mathematicians secretly care more about, in a gossipy and potentially catty way – is what fields lead to what fate. We all know algebra and number theory are the purest and most virtuous subjects, and applied math is for people who want to make money or want to make a difference in the world.

[On that note, you might notice that I removed statistics PhDs in the visualization below, and I also removed some of the employment sectors that gained only a few people a year. The stats ribbons are huge and the small sectors are very small, so for looks alone I took them out.]

2010BigCircosPicHigher resolution version available here.

Wish list

I wish I could animate a series of these to show this view over time as well. Let me know if you know how to do that! Another nice thing I could do would be to set up a webpage in which these visualizations could be explored in a bit more depth. (After finals.)

Also:

  • I haven’t computed any numbers for you
  • the graphs from R show employment in each field by percentage of graduates instead of total number per category;
  • it’s hard to show both data over time and all the data one could explore. But it’s a start.

I should finish with a shout-out to Roger Peng and Jeff Leek, though we’ve never met: I took Peng’s Computing for Data Analysis and much of Leek’s Data Analysis on Coursera (though I’m one of those who didn’t finish the class). Their courses and Stack Overflow taught me almost everything I know about R. As I mentioned above, I’m pretty new to this type of analysis.

What questions would you ask? How can I make the above cooler? Did you learn anything?

On being an alpha female, part 2

Almost a year ago now I wrote this post on being an alpha female. I had only recently understood that I was an alpha female, when I wrote it, and it was still kind of new and weird.

For whatever reason it’s been coming up a lot recently and I wanted to update that post with my observations.

Who’s burning which bridges?

Last week I wrote an outraged post about seeing Ina Drew at Barnard.

Mind you, I had anticipated I’d find the event objectionable. I had even polled my Occupy friends for prepared questions for her. But when I got there I realized pretty quickly that I wouldn’t be able to ask her anything. I was just too disgusted with the tone and conceit of the event to participate in it reasonably. Instead I live tweeted the event and seethed.

I lost sleep that night fuming about Drew-as-role-model, and I was grateful to be able to get some of my frustration out on my blog.

One of the first comments I received was this one,  which said:

Boy Cathy, you sure do know how to burn bridges.

This was, for me, kind of a perfect alpha female moment. My immediate reaction was to think to myself,

They burned bridges with me, you mean.

Since that sounded too arrogant, at the moment anyway, I said something else just slightly less obnoxious. Three points to make here:

  1. Anyone who doesn’t agree with me about whether Ina Drew should be celebrated can go suck it.
  2. That post got linked to from Reuters, FT.com, and Naked Capitalism. Which doesn’t happen when you’re worrying about burning bridges.
  3. When I’m in a certain kind of mood, I’m simply not concerned with other people’s judgments. I think that’s just part of being an alpha female, and I’m grateful for it.

Why grateful? Because lots of shitty things happen when people go around worrying about “burning their bridges” instead of speaking up about bullshit or evil-doing. Or, as Felix Salmon tweeted recently:

Taking notes from an uber alpha female

A few months ago I got an email inviting me to speak in a Python in Finance conference. The email was somewhat weird and kind of just came out and said they need women speakers. I was put in a position of being asked to be a token woman, which is a mindset I don’t enjoy.

I thought about it though, and although I use python, and I used to work in finance, I don’t work in finance any more, and I don’t really think about python too much, I just use it. So I said to the organizer, no thanks, I don’t have anything to say at that conference.

Fast forward to the week before the conference, when I got wind of the agenda. It turned out my friend Claudia Perlich, Chief Data Scientist at m6d and one of the contributors to my upcoming book with Rachel Schutt, was the keynote speaker. I decided to go to the conference essentially because I wanted to see her.

Well, it turned out Claudia had gotten a similar email, and she had accepted the invitation, even though she doesn’t work in finance and doesn’t even use python (she uses perl).

She gave a great talk about modeling blind spots, which everyone enjoyed. It was quite possibly the best talk of the day, in fact. Plus, she wasn’t at all token – having her on the schedule was what made me come to the conference, and I probably wasn’t the only one. And judging by the crowd at the Meetup I gave last night, I would have drawn my own crowd too, if I had been speaking.

I made an alpha female note to myself that day to accept any invitation to a conference that I’d enjoy, even if my expertise isn’t completely within the realm of the conference. I’m learning from Claudia, a master alpha female. Or is it mistress?

Alpha females and self-image

Chris Wiggins recently sent me this essay entitled “A Rant on Women” by Clay Shirky, a writer and professor who studies the social and economic effects of Internet technologies. Here’s the first paragraph:

So I get email from a good former student, applying for a job and asking for a recommendation. “Sure”, I say, “Tell me what you think I should say.” I then get a draft letter back in which the student has described their work and fitness for the job in terms so superlative it would make an Assistant Brand Manager blush.

Guess what? That student is male.

Shirky goes on to vent about how women don’t oversell themselves enough compared to men and how it’s a problem. An excerpt:

There is no upper limit to the risks men are willing to take in order to succeed, and if there is an upper limit for women, they will succeed less. They will also end up in jail less, but I don’t think we get the rewards without the risks.

This made me think about my experience. First, as a Barnard professor, I certainly saw this effect. I’d have men and women come talk to me about letters of recommendations, and not only would I prepare myself for the difference in posture, I’d try to address it directly, by encouraging women to learn how to brag about their accomplishments. I might have tried to convince men a couple of times to stop bragging quite so much, but quickly found that to be a huge waste of time.

But beyond corroborating that this is typical behavior, the essay made me remember myself as a college student.

When I met my thesis advisor, Barry Mazur, who was on sabbatical at UC Berkeley, I remember telling him a math problem I had worked on and solved. He expressed something about liking the problem and being impressed that I’d explained it so well, and I said back,

“Yeah, I’m awesome”

I remember this because of his reaction. At the time, the word “awesome” was widely used among teenagers, but evidently he hadn’t gotten the teenager memo, and he was taken aback by the way I used it. At least that’s what he said. But now that I think about it, maybe he was taken aback that I’d said it at all.

Alpha females and body image

My friend and guest poster Becky recently sent me this video:

It’s about how women have a biased view on their looks, or at least describe their looks to other people in a consistently negatively biased way.

There’s a great critique of this video here (hat tip Avani Patel), wherein fashion and style guru Jennifer Choy complains that the underlying message to the above video is that, in any case, beauty is about all women have going for them, so they should not underestimate their beauty. Plus that all the women in the video were skinny, young, and white.

Great points, but my take was somewhat different.

My immediate reaction to the video was to say, these women need to spend less time thinking about being fat or ugly, and more time thinking about what they think is sexy and attractive. Why is it always about finding flaws in ourselves? Why don’t we spend more time thinking about what turns us on or what we think is beautiful?

I’ll be honest: I think if I had been interviewed in that setting, I would have said something like, “Gorgeous and sexy as hell” and gone on to list my best features. I am not sure I’d have even been able to describe what I look like in any detail, with any accuracy. Most likely I would have just started bragging about my sexy grey streaks. Even more likely: I wouldn’t have had the time to sit down for this interview at all.

Don’t get me wrong, I’ve dabbled in being insecure in my looks: puberty sucked, as did all three post-natal periods until the baby was weaned*, in addition to any time I was ever on the pill**. I’ve concluded that my inherent arrogance is directly related to my hormones, which in turn makes it undeniably tied to my alpha femaleness.

Suffice it to say, when my hormones are not messed up I have “body eumorphia,” where I ignore or downplay any non-perfect parts of my body. It’s a nice feeling.

It kind of makes me want to develop an alpha female hormone treatment. Business model?

UPDATE: Please watch this new spoof video, it’s perfect (except it should be alpha females and men, not just men):

* It gets better when you know it’s going to go away. By the third kid I was like, “gonna cry every day at 3:00pm for the next six weeks. Must schedule that into my calendar.”

** Note to doctors: you need to tell women that the real reason birth control pills work so well is that you lose interest in sex when you’re on them!

Categories: musing, women in math

Guest post by Julia Evans: How I got a data science job

This is a guest post by Julia Evans. Julia is a data scientist & programmer who lives in Montréal. She spends her free time these days playing with data and running events for women who program or want to — she just started a Montréal chapter of pyladies to teach programming, and co-organize a monthly meetup called Montréal All-Girl Hack Night for women who are developers.

asked mathbabe a question a few weeks ago saying that I’d recently started a data science job without having too much experience with statistics, and she asked me to write something about how I got the job. Needless to say I’m pretty honoured to be a guest blogger here 🙂 Hopefully this will help someone!

Last March I decided that I wanted a job playing with data, since I’d been playing with datasets in my spare time for a while and I really liked it. I had a BSc in pure math, a MSc in theoretical computer science and about 6 months of work experience as a programmer developing websites. I’d taken one machine learning class and zero statistics classes.

In October, I left my web development job with some savings and no immediate plans to find a new job. I was thinking about doing freelance web development. Two weeks later, someone posted a job posting to my department mailing list looking for a “Junior Data Scientist”. I wrote back and said basically “I have a really strong math background and am a pretty good programmer”. This email included, embarrassingly, the sentence “I am amazing at math”. They said they’d like to interview me.

The interview was a lunch meeting. I found out that the company (Via Science) was opening a new office in my city, and was looking for people to be the first employees at the new office. They work with clients to make predictions based on their data.

My interviewer (now my manager) asked me about my role at my previous job (a little bit of everything — programming, system administration, etc.), my math background (lots of pure math, but no stats), and my experience with machine learning (one class, and drawing some graphs for fun). I was asked how I’d approach a digit recognition problem and I said “well, I’d see what people do to solve problems like that, and I’d try that”.

I also talked about some data visualizations I’d worked on for fun. They were looking for someone who could take on new datasets and be independent and proactive about creating model, figuring out what is the most useful thing to model, and getting more information from clients.

I got a call back about a week after the lunch interview saying that they’d like to hire me. We talked a bit more about the work culture, starting dates, and salary, and then I accepted the offer.

So far I’ve been working here for about four months. I work with a machine learning system developed inside the company (there’s a paper about it here). I’ve spent most of my time working on code to interface with this system and make it easier for us to get results out of it quickly. I alternate between working on this system (using Java) and using Python (with the fabulous IPython Notebook) to quickly draw graphs and make models with scikit-learn to compare our results.

I like that I have real-world data (sometimes, lots of it!) where there’s not always a clear question or direction to go in. I get to spend time figuring out the relevant features of the data or what kinds of things we should be trying to model. I’m beginning to understand what people say about data-wrangling taking up most of their time. I’m learning some statistics, and we have a weekly Friday seminar series where we take turns talking about something we’ve learned in the last few weeks or introducing a piece of math that we want to use.

Overall I’m really happy to have a job where I get data and have to figure out what direction to take it in, and I’m learning a lot.

Leila Schneps is a mystery writer!

I’m back! I missed you guys bad.

My experience with Seattle in the last 8 days has convinced me of something I rather suspected, namely I’m a huge New York snob and can’t exist happily anywhere else. I will spare you the details (they have to do with cars, subways, and being an asshole pedestrian) but suffice it to say, glad to be home.

Just a few caveats on complaining about my vacation:

  1. I enjoyed visiting the University of Washington and giving the math colloquium there as well as a “Math Day” talk where I showed kids the winning strategy for Nim (as well as other impartial two-player games) following my notes from last summer.
  2. I enjoyed reading Leon and Becky’s guest posts. Thanks guys!
  3. And then there was the time spent with my darling family. Of course, goes without saying, it’s always magical to get to the point where your kids have invented a whole new language of insults after you’ve outlawed certain words: “Shut your fidoodle, you syncopathic lardle!”

Of all the topics I want to write about today, I’ve decided to go with the most immediate and surprising one : Leila Schneps is now a mystery writer! How cool is that? She’s written a book with her daughter, Math on Trial: How Numbers Get Used and Abused in the Courtroom, currently in stock and available on Amazon. And she wrote an op-ed for the New York Times talking about it (hat tip Chris Wiggins).

I know Leila from having been her grad student assistant at the GWU Summer Program for Women in Math the first year it existed, in 1995. She taught undergrads about Galois cohomology and interpreted elements of H^1 as twists and elements of H^2 as obstructions and then had them do a bunch of examples for homework with me. It was pretty awesome, and I learned a ton. Leila is also a regular and fantastic commenter on mathbabe.

I love the premise of the book she’s written. She finds a bunch of historical examples where mathematics is used in trials to the detriment of justice, and people get unfairly jailed (or, less often, let free). From the op-ed (emphasis mine):

Decades ago, the Harvard law professor Laurence H. Tribe wrote a stinging denunciation of the use of mathematics at trial, saying that the “overbearing impressiveness” of numbers tends to “dwarf” other evidence. But we neither can nor should throw math out of the courtroom. Advances in forensics, which rely on data analysis for everything from gunpowder to DNA, mean that quantitative methods will play an ever more important role in judicial deliberations.

The challenge is to make sure that the math behind the legal reasoning is fundamentally sound. Good math can help reveal the truth. But in inexperienced hands, math can become a weapon that impedes justice and destroys innocent lives.

Go Leila!

Categories: math, modeling, women in math

Nasty reader comments and blogging

I’m pretty sure you guys know this already, but I love my regular readers and commenters. It’s a large part of why I blog – I feel like I’m having a super interesting cocktail party every morning in my underwear. I’m investing in the quality of the rest of my day, stealing a moment before my family wakes up so I can articulate one single idea. The payoff is, most of the time, dependably good conversation that lasts all day, or even more than a day, as your comments and emails come in.

Of course, there are sometimes nasty people and comments in addition to thoughtful ones. Not everyone interprets me as trying to figure stuff out, they think I’m being intentionally asinine or manipulative. Or sometimes they just don’t agree with me, and instead of explaining their reasoning they just yell. Or sometimes they are just jerks, getting out their aggression on a stranger.

My first rule is to allow comments that disagree with me, as long as the reasons are articulated and as long as the comment isn’t abusive. Rude is ok, “you are stupid” is not ok.

My second rule is to have a thick skin. I can completely ignore the sentiment of an abusive commenter calling me names, because first of all I’ve heard it all before and second I’m pretty sure it’s not about me.

I’m not saying it doesn’t bother me at all, because obviously it’s a pain to have to go through my email and make sure people are being civil.

For example, whenever I get onto the top 10 of Hacker News, which has been a few times now, I’ve noticed a huge wave of nasty comments. Of course this could be a direct result of how many people I get (thousands per hour), but I don’t think so – the ratio of interesting to abusive comments coming from Hacker News traffic is tiny. It creates nasty work for me, which I feel compelled to do because letting nasty comments stay on my blog makes me feel violated and intentionally misunderstood.

This morning I found this article via Naked Capitalism regarding reader comments, and how nasty ones make subsequent readers evaluate the message differently, and in particular, more negatively. In other words, my intuition was right – it’s super important to curate comments.

My experience with Hacker News has also given me sympathy for Izabella Laba‘s position that she doesn’t accept comments on her blog (read this post for example). She puts herself out there, with strong opinions, and many of her posts are important and thought-provoking. And by the same token people can get pretty threatened by what she has to say. I can well imagine what her experience has been. What if every day was a Hacker News day? What if a majority of comments contained ridiculous and personal attacks? Yuck.

Makes me even more grateful to have you guys.

Categories: musing, news, women in math

Gender bias in math

I don’t agree with everything she always says, but I agree with everything Izabella Laba says in this post called Gender Bias 101 For Mathematicians (hat tip Jordan Ellenberg). And I’m kind of jealous she put it together in such a fantastic no-bullshit way.

Namely, she debunks a bunch of myths of gender bias. Here’s my summary, but you should read the whole thing:

  1. Myth: Sexism in math is perpetrated mainly by a bunch of enormously sexist old guys. Izabella: Nope, it’s everyone, and there’s lots of evidence for that.
  2. Myth: The way to combat sexism is to find those guys and isolate them. Izabella: Nope, that won’t work, since it’s everyone.
  3. Myth: If it’s really everyone, it’s too hard to solve. Izabella: Not necessarily, and hey you are still trying to solve the Riemann Hypothesis even though that’s hard (my favorite argument).
  4. Myth: We should continue to debate about its existence rather than solution. Izabella: We are beyond that, it’s a waste of time, and I’m not going to waste my time anymore.
  5. Myth: Izabella, you are only writing this to be reassured. Izabella: Don’t patronize me.

Here’s what I’d add. I’ve been arguing for a long time that gender bias against girls in math starts young and starts at the cultural level. It has to do with expectations of oneself just as much as a bunch of nasty old men (by the way, the above is not to say there aren’t nasty old men (and nasty old women!), just that it’s not only about them).

My argument has been that the cultural differences are larger than the talent differences, something Larry Summers strangely dismissed without actually investigating in his famous speech.

And I think I’ve found the smoking gun for my side of this argument, in the form of an interactive New York Times graphic from last week’s Science section which I’ve screenshot here:

Gender bias through testing internationally

What this shows is that 15-year-old girls out-perform 15-year-old boys in certain countries and under-perform them in others. Those countries where they outperform boys is not random and has everything to do with cultural expectations and opportunities for girls in those countries and is explained to some extent by stereotype threat. Go read the article, it’s fascinating.

I’ll say again what I said already at the end of this post: the great news is that it is possible to address stereotype threat directly, which won’t solve everything but will go a long way.

You do it by emphasizing that mathematical talent is not inherent, nor fixed at birth, and that you can cultivate it and grow it over time and through hard work. I make this speech whenever I can to young people. Spread the word!

Advice for young women math professors

I’ve been here at the Nebraska conference for undergrad women in math for a couple of days now. There are quite a few grad students and young professors as well and I’m finding myself giving a few pieces of advice over and over again to the new female professors. I thought I’d write them down here too.

Obviously you can take this advice or leave it.

  1. Ban guilt from your child-rearing experience. The tenure system being what it is, it’s just impossible for you to work enough, including research, and to spend 4 hours a day with an awake baby. Instead think of it this way: it takes a village to raise a child, and this is the time when it’s more village than mom, which is ok. Make sure they are in loving environments, have super nice babysitters, get the best daycare you can, and stop worrying about being a crappy mom. Turns out you’ll have plenty of time to do awesome things with your kids and in the meantime they need you to be a role model, which means pursuing your dreams.
  2. I’m not suggesting working too much either – having a really set schedule which allows time for work during daycare and then time for family before and after is great, and your students and colleagues will just need to accept that you are available during working hours and not otherwise. Don’t apologize for this, just do your job, and don’t assume people are judging you for it either. 
  3. I met a ton of women who seem to have taken on all of the household duties and are overwhelmed by them, especially when they also have small children. First of all, lower your standards. Houses can be messy, it doesn’t actually kill anyone if you ignore an upturned lego box because you want to go think about math. Second, budget a housecleaner – one woman described how she and her husband decided to sell their car but kept their housekeeper, and I fully endorse this trade-off. Third, sit down with your partner and write a list of chores and split them up. It’s not sexy but it works. Finally, be sure your kids help as soon as they can. Turns out kids can make their own school lunches starting when they’re 8 if the ingredients are readily available.
  4. Personally I never do more volunteering at the kids’ schools than my husband as a matter of principle. And it also turns out my husband never does any. This makes me a bitch but also saves me a ton of time. Consider it.
  5. Make time for something other than kids and work. Carve it out with a knife if necessary. It will be worth it and will keep you sane and remembering why you made this plan.
  6. Also don’t forget to have dates with your partner.
  7. Finally, if you ultimately decide it’s not working, remember you have lots of options with a math Ph.D. – don’t underestimate yourself and your options.

I hope that’s helpful!

Categories: women in math