Meanwhile, there’s a growing crop of men who, having declared themselves as feminists, proceed to lecture women on how they should go about equity-related matters. At a recent tech conference, a panel of male allies told women that they should just apply themselves a little bit more; another male panelist implored them to wait quietly for their good karma. Closer to home, I’ve been told repeatedly and earnestly that sexism in math would be solved if we only had unmoderated comments on research articles, or anonymous journal submissions, or some such. We’re instructed on what level of anger befits a feminist (low to nonexistent), which fights we can pick without belittling our cause (not many, and most of them were in the past), and how to address men in order to not alienate them (politely and with due deference). We’re offered advice that’s worse than useless in that we have to spend our time rebutting it. We have policies and procedures pushed on us that promote, at our expense, some alien, estranged concept called “women” that does not include us.

This is all of a piece with the culture that casts men as leaders and experts, and women as supporting characters and understudies. In feminism, as in everything else, men believe that their superior knowledge and understanding bestows upon them a natural authority and responsibility. Our equality will be measured, apportioned and dispensed to us by polite, congenial men, men who will invite us to advise and support them as needed, but will always reserve the right to overrule us should they deem it necessary.

Basic things are basic. You spoke over women in committees, silenced them in faculty meetings, denied their requests, and then you don’t understand why they don’t accept your valiant leadership with gratitude? Golly gee, the world can be so unfair. That said, we do need allies. We could use more help. And there are men who, I’m sure, have all the best intentions. And that makes it so much more disappointing when these men dismiss our hard-earned insight in favour of their own solutionism, where each problem has an easy answer and those that do not are declared nonexistent.

Consider the large body of research on unconscious racial and gender bias. Have you also paid attention to the public responses to such studies? Most men, and some women, might read a study on gender bias with astonishment and disbelief, having had no previous intimation that this was going on. They might argue back that not all men do this, and that some women succeed in tech, and women have babies and girls play with dolls. Above all, they will demand more proof. If it’s a lab study, it needs to be repeated and checked against real life statistics. If it’s statistics, then individual cases must be examined for other possible explanations. If it’s individual stories, that’s just anecdata, we need statistics and/or a lab study. To ensure appropriate collegiality, all this must be provided without hurting men’s feelings or contradicting their beliefs.

Many women, meanwhile, respond to the results of the same study with a collective “duh” on social media. It’s hardly news to them that X happens, even if the numbers might still surprise them. They see it all the time; they also see Y, Z, W, and much more. They had talked about it between themselves, thought about it, written about it at length. Nonetheless, they are the first to point out the importance of the study, to praise and publicize it. They do so because it legitimizes their own experience in the eyes of others, opens up a window in which they might be permitted to speak out. It offers evidence other than the flimsy, useless threads of their own words.

None of their knowledge is available to those who insist on conducting every conversation as it if were a criminal trial. There’s no chance of normal discourse. Why did I say “they see it all the time” when there was this one time it didn’t happen? And that other time, too? Who are “they,” anyway? Can we have their names and institutional affiliations? Have we heard the other side of the story? And so women are studied as if we were baboons, endangered for some reason but incapable of articulating what it is that ails us, so that researchers have to rely on statistics, experiments and third-party accounts.

Do you care about proof, or about progress? You can read all the peer-reviewed research, attend all the official panels, and you’ll still only see the tip of the iceberg. You’ll see the isolated facts but you’ll have no idea how to connect them. You’ll see the molehill that can be proved in a scientific paper, but not the mountain that we are forbidden to talk about for confidentiality reasons, and not the one that we stopped talking about because nobody believed us, either.

This post, unlike most of what I write, has no hyperlinks. This is on purpose. There are many related links in my earlier posts, and more in my Twitter feed linked on the sidebar. It’s easy enough to google around and find more. Alternatively, you could entertain the possibility that what I’m telling you is the actual truth of my experience. That would be a good start.

]]>

The program covers various aspects of dimension theory and dynamics, from ergodic theory to hyperbolic dynamics to computation. In my own research, I’ve been increasingly attracted to connections between dimension theory and dynamical systems on one hand, and harmonic analysis and additive combinatorics on the other. I look forward to doing more work in that direction in the next few years.

]]>

]]>

According to a new psychology paper, our political passions can even undermine our very basic reasoning skills. More specifically, the study finds that people who are otherwise very good at math may totally flunk a problem that they would otherwise probably be able to solve, simply because giving the right answer goes against their political beliefs.

I was reminded of it while reading the article “Does Diversity Trump Ability? An Example of the Misuse of Mathematics in the Social Sciences” in the Notices of the AMS. The author, Abigail Thompson, takes on a well known and widely cited paper:

“Diversity” has become an important concept in the modern university, affecting admissions, faculty hiring, and administrative appointments. In the paper “Groups of diverse problem solvers can outperform groups of high-ability problem solvers” [1], L. Hong and S. Page claim to prove that “To put it succinctly, diversity trumps ability.” We show that their arguments are fundamentally flawed.

Why should mathematicians care? Mathematicians have a responsibility to ensure that mathematics is not misused. The highly specialized language of mathematics can be used to obscure rather than reveal truth. It is easy to cross the line between analysis and advocacy when strongly held beliefs are in play. Attempts to find a mathematical justification for “diversity” as practiced in universities provide an instructive example of where that line has been crossed.

Thompson proceeds to shred both the “mathematical theorem” and the numerical examples from the Hong-Page paper. The actual paper is available here, and I have satisfied myself that Thompson is not unfair in her mathematical analysis. Her article, however, does not exist in a vacuum. It will be read in mathematics departments, organizations and committees where “diversity” is viewed as a bureaucratic imposition made on them by distant administrators who don’t understand research, even as their few women faculty often find themselves alienated and sidelined. That’s why I would like to add a few things.

First, there are many sound reasons for diversity that have nothing to do the article in question. (I will restrict this post to the benefits of diversity *per se*, independently of how that diversity was achieved. Affirmative action has its own reasons and will get its own post soon.) It should be common sense, not a mathematical theorem, that there are advantages in having a wider perspective and more than one problem-solving approach. In business, the lack of diversity among designers and decision-makers courts a mismatch between the product and its clientele, from the non-functionality of women’s clothing to drugs tested primarily on white men and “health apps” oblivious to the basics of women’s health. Women, too, have been guilty of not looking past their own noses. The cosmetics industry has long had women leaders, going back to Elizabeth Arden who died in 1966, yet it had little or nothing to offer to women of colour before Iman created her own product line in 1989. It should not be rocket science that catering to the preferences of your actual clientele, and not just your own, makes good business sense.

You’ll say that diversity does not matter in mathematics because arithmetics and algebra do not depend on gender or skin colour. I will reply that solving mathematical problems is only one part of what we do. We also teach undergraduates, supervise graduate students and postdocs, perform administrative functions and participate in committees. In all of these, diversity does matter. Women and minority students benefit from having women and minority professors. An administrator who is a woman or a person of colour is more likely to be aware of the sexism and racism in the faculty ranks. But even if you don’t believe that sexism and racism exist, and if solving mathematical problems is all you care about, you might still want to read this:

Katherine W. Phillips, senior vice dean at Columbia Business School, and her colleagues gave three-person groups complex murder mysteries, and then asked them to work together on solutions. Each member received clues that her or his companions didn’t possess, giving an edge to groups with the ability to share information. Racially diverse teams significantly outperformed those with similar members. Other studies confirm this result: A diverse team is more innovative on average.

What is going on, Phillips thinks, is that diversity changes the dynamics of a group in a way that makes it more innovative. When we work with others who are like us, we tend to assume they hold similar points of view and share similar information. That makes for easy and comfortable interactions, and it works well when the task at hand is routine. But when a team is trying to do something new that requires knowledge and experience surpassing what any one member can supply, a more challenging social situation leads to better outcomes. When we have to try harder to communicate with collaborators who are different from us, we better articulate our ideas. “Diversity jolts us into cognitive action in ways that homogeneity simply does not,” Phillips writes.

My own problem-solving processes have very little in common with the naive algorithms from the Hong-Page paper. It’s not even close. Phillips, however, strikes a chord. I have noticed, and have mentioned it here, that I often work better when I collaborate: aside from any ideas and expertise that the collaborators might or might not contribute, engagement in collaboration enhances my own mental processes. This is especially pronounced when the collaborators do not share my thinking patterns and force me to articulate them better, in accordance with Phillips’s argument. If you think that it’s only the mathematical and not personal backgrounds that should matter, I will say that the two are not always easily separated, at least not in my experience. I’ll also refer you to the work of James H. Austin on creativity, especially his notion of “Chance IV” (hat tip to Marc Andreessen and his now-deleted blog post “Luck and the entrepreneur”):

[You] have to look carefully to find Chance IV for three reasons.

The first is that when it operates directly, it unfolds in an elliptical, unorthodox manner.

The second is that it often works indirectly.

The third is that some problems it may help solve are uncommonly difficult to understand because they have gone through a process of selection.

We must bear in mind that, by the time Chance IV finally occurs, the easy, more accessible problems will already have been solved earlier by conventional actions, conventional logic, or by the operations of the other forms of chance. What remains late in the game, then, is a tough core of complex, resistant problems. Such problems yield to none but an unusual approach…

[Chance IV involves] a kind of discrete behavioral performance focused in a highly specific manner. [...]

Chance IV favors those with distinctive, if not eccentric hobbies, personal lifestyles, and motor behaviors.

Complex, resistant problems that do not succumb to conventional methods but might sometimes be solved by weird people with eccentric habits? Why, that almost sounds like math research. Before you trivialize my point, no, this does not mean that I choose my collaborators based on the colour of their skin, the more “exotic,” the better. It does mean that I would like to work towards a world where having for example a black collaborator in your own area of mathematics is common and unremarkable, not only because it’s the right thing to do, but also because research progress might be a little bit faster and more exciting in that world.

If “the feminist approach to mathematics” still makes you giggle, you might want to read about the benefits of the feminist approach to computer programming:

What led me to a creative, simple, and extremely fast solution was being part of a feminist community in which people felt comfortable sharing their technical problems, wanted to help each other, and respected each other’s intelligence. Those are all feminist principles, and they make file systems development better.

Please spare me the argument that mathematicians–unlike those horrible computer programmers and gamers–are already respectful, collaborative and open-minded. I happen to agree with Matilde Marcolli that the actual picture is far less rosy than that.

Second, mathematicians are just as likely as social scientists to confirm their political beliefs through incorrect mathematical reasoning. They are especially likely to do so when arguing about issues of gender and diversity. In no particular order:

**50/50 equals 80/20 equals whatever.** According to a study I’ve heard of, when a group has 17% women, this is often perceived as a 50/50 split, and 33% of women is perceived as a majority. This is perfectly consistent with the arguments about “50/50 quota” that I hear from mathematicians all the time. Feminists, supposedly, demand 50/50 gender quota everywhere, even when they are in fact disputing an existing 95/5 or 100/0 split and pointing out that 80/20 or 85/15 might be more desirable. Of course it is possible that, in a specific situation, 80/20 might be unreasonable or unrealistic. It still would not equal 50/50.

**The magical all-purpose bell curve.** We could start with Larry Summers’s theory of “greater male variability”:

It does appear that on many, many different human attributes-height, weight, propensity for criminality, overall IQ, mathematical ability, scientific ability-there is relatively clear evidence that whatever the difference in means-which can be debated-there is a difference in the standard deviation, and variability of a male and a female population. And that is true with respect to attributes that are and are not plausibly, culturally determined. If one supposes, as I think is reasonable, that if one is talking about physicists at a top twenty-five research university, one is not talking about people who are two standard deviations above the mean. And perhaps it’s not even talking about somebody who is three standard deviations above the mean. But it’s talking about people who are three and a half, four standard deviations above the mean in the one in 5,000, one in 10,000 class. Even small differences in the standard deviation will translate into very large differences in the available pool substantially out.

Steven Pinker explains the same theory in much greater detail, complete with graphs and slides. Notably, Pinker makes it very clear that he is talking specifically about the bell curve, not just about some general function whose graph has a bump, and discusses its particular properties such as “a normal distribution falls off according to the negative exponential of the square of the distance from the mean.” He also mentions another version of the bell curve argument where small differences in the mean lead to relatively large differences at the extreme ends. John Allen Paulos, a mathematician, has used that one to explain why, in a corporation employing Koreans and Mexicans, the Koreans might hold all the top posts even if the Mexicans are only a little bit more stupid. Hypothetically, of course. I’ve heard both versions of the argument many times, including in comments here on this blog. Every time, it is assumed that ability, mathematical or otherwise, is clearly described by a bell curve, because of course it is.

I submit that it is not, and here’s a proof. The bell curve is symmetric about its mean value. This means that the two extremes should be about equidistant from the mean. In other words, the average person’s mathematical ability should be exactly halfway between the two extremes, or equivalently, the average person should have one half of the mathematical ability of the very best mathematicians at the level of, say, the Fields Medal or Abel Prize. I don’t believe that there’s any definition or quantification of mathematical ability for which this would be true, even in the roughest approximation. I don’t even believe that the average person has half of the mathematical ability of a typical Ph.D. in mathematics, and then it gets much steeper after that.

Here’s what we do, then: we imagine a bell curve placed so that its maximum more or less coincides with “average” mathematical ability, whatever that may be. On one side, we cut off the far left tail altogether and consider this to be a negligible error. On the other side, though, we look at the tiniest shivers and tremblings of the extreme far right tail, way past the point where we made the cut on the left, and we believe that this will tell us something really deep and meaningful about why there are so few women at the top levels of mathematics. (Click to enlarge.)

Even Summers and Pinker seem to realize that this is way off, because they are always quick to add something about criminality or risk-taking. Because criminality is the negative of math ability? Alrighty, then.

(If you’d like to get more technical: in probability, the bell curve is the limiting distribution of a large number of independent identically distributed variables. On the other hand, the main variables on which high-level mathematical ability might depend–logical thinking, facility with computation, geometrical visualization skills, ability to modularize complex arguments, level of comfort with abstraction, quantitative instincts–are often correlated, and moreover the value of having two or more of these skills seems much higher than the sum of their individual values. Are you already trying to explain it away by coming up with unknown ghost variables and modified bell curves? Chances are that you are only attempting to find a mathematical justification for what you believe already for other reasons.)

**Bayesian priors: now you see them, now you don’t.** A Yale study found that scientists ranked the same job applicant higher, and offered a higher salary, when the candidate’s name was male. In various comment sections around the internet, I saw way too many responses defending such decision-making, based either on bell curves as above or on arguments such as this:

1) The woman on average worked harder to get the same qualification, leaving a man with a greater potential for growth.

As mentioned before, women are more conscientiousness. Across my student years, many just got better marks, because they did homework well and studied more regularly. Even though some got better marks than myself for example, I always felt they were closer to their limits. [...]

2) Women get pregnant. This is a real disadvantage and risk for any project leader. I witnessed myself that a project leader hired a woman with all good intentions, but she got pregnant just after, promised to keep working, but then left. His project was delayed significantly and he said “never again”.

So given the same qualifications, I would rationally go for the man.

This particular comment is anonymous, but I’ve also seen non-anonymous mathematicians making the same arguments on social media and calling them “Bayesian priors.”

Meanwhile, I’ve said a few times that I’m not interested in hanging out on Math Overflow or in publishing my papers in journals that have mandatory comment sections. Part of my rationale is the common sexism of internet comments, from the cesspit of sexism and racism at Hacker News, to situations where two very similar articles generate very different types of comments depending on the gender of the authors, to examples such as this:

[Female] authors are reviewed personally alongside their books, in a way that rarely happens to men. The author Jennifer Weiner tweeted several examples the other day, including “reviews” of herself, Fifty Shades of Grey author E.L. James, and one of my own book: In The New York Times, lead book critic Michiko Kakutani took three paragraphs even to get around to mentioning my book, and on the way there, she quoted — somewhat extensively! — from anonymous comments left on a 2010 essay that I wrote. In a review of, supposedly, my novel.

These are all mainstream sites well frequented by academic audiences, not “obscure gaming sites” or other dark corners of the internet. (There, it gets much worse.) I have already linked to many more such examples, here and and on twitter. I see them every day. And an internet commenting situation, where a post is exposed to many readers and many potential commenters, is certainly a good testing ground for Bayesian priors and the law of large numbers. Yet every time, mathematicians told me that my priors were not valid. These sexist commenters were not mathematicians; or if they were, then it did not happen on a dedicated site for mathematicians only; or if it did, it was a rare exception that I should ignore. And if my general experience with mathematicians has not been great, I should ignore it anyway, because #notallmathematicians.

If nothing else, you should at least acknowledge that if you can have your Bayesian priors, I can have mine.

**The dog ate my logic.** The bell curve arguments, even if interpreted charitably and not obviously wrong on a quantitative level, can only say this: there exists a mathematical model that does not contradict your conclusions. This is at best corroborating evidence, but it’s often treated as a conclusive proof, including by mathematicians. Also along the lines of faulty logic, whenever the subject of female underrepresentation or innate ability comes up, I’m asked whether I really believe that there are no differences between men and women. No, I don’t, why should I? Because “women have to wait longer than men to get promoted and this might indicate unconscious gender discrimination” must necessarily imply “men and women are exactly identical”? Really?

And that’s why I’m writing this post. Because I’m worried that mathematicians will see the Notices article and mistake it for a mathematical “proof” that it should not be necessary to invite women to speak at conferences. A few female graduate students in attendance, yeah sure, but certainly not plenary speakers because diversity is a boogieman.

Please, just for once, prove me wrong.

]]>

This book has been in the works for some years now, and I’m thrilled to finally have a demo copy to show you. The book will be published by the American Mathematical Society. The demo copy has been produced (impressively quickly!) by the Hungarian publisher Ab Ovo. I’m very grateful to Anna Kepes Szemerédi for envisioning this project in the first place, and for all the hard work she has put into it.

I have contributed an essay on photography. You can download it here, and here is the gallery of the photos I offered to be used in the book. The photo on the cover is also mine. I hope that this will encourage you to purchase the book when it becomes available; I’m only one out of many contributors (see the cover for the list of names), and the book format will add further value through graphic design. If you’re expecting “mathematical art” as exemplified for example by the Bridges conference, I must warn you that this is not what I do. (In the essay, I explain why.) There is some overlap with one of my blog posts from last year: the post was adapted from an earlier version of the essay, and then I used it in writing the final version.

Anna first approached me about this in late 2011. I was much less confident then, both in my photography and in my writing. I have worked on both since then. One thing I wish I’d seen before I submitted my contribution is this classic piece by Linda Nochlin on the absence of great women artists in the history of art. Here’s what she says about “the lady’s accomplishment”:

In contrast to the single-mindedness and commitment demanded of a chef d’ecole, we might set the image of the “lady painter” established by 19th century etiquette books and reinforced in the literature of the times. It is precisely the insistence upon a modest, proficient, self demeaning level of amateurism as a “suitable accomplishment” for the well brought up young woman, who naturally would want to direct her major attention to the welfare of others–family and husband–that militated, and still militates, against any real accomplishment on the part of women. It is this emphasis which transforms serious commitment to frivolous self-indulgence, busy work, or occupational therapy, and today, more than ever, in suburban bastions of the feminine mystique, tends to distort the whole notion of what art is and what kind of social role it plays.

This got me thinking back on what I wrote about photography and wondering for a moment if I might have fallen into the trap of “suitable accomplishment.” In the end, it clarified for me the distinction between the commitment to the process of getting better, and the expectation of achieving a certain level of excellence, and the expectation of gaining public acclaim. I have always been anything but unambitious. Nonetheless, I have never aimed to be a “great artist.” I am not altogether indifferent to success in art, as evidenced by this self-promotional post, but what made me pick up the camera is the pleasure I find in taking photographs. My enjoyment of it is not conditional on finding an audience, receiving public recognition, or on any presumption of greatness. Instead, it comes from trying to get better at it. The pleasure is not in taking the same photographs over and over again, but in expanding my range, improving my technique, seeking out new ideas and solutions. The seriousness of my commitment is in my engagement in the process.

I suppose that this does not make me a lady.

]]>

]]>

The official press release on Mirzakhani’s research is available, as are the citations for the other Fields medalists. I’d like to speak to what the selection of a female Fields medalist means to me as a woman and a mathematician. In that, I would like to paraphrase something that Melissa Harris-Perry has said about the election of President Obama. Mirzakhani’s selection does exactly nothing to convince me that women are capable of doing mathematical research at the same level as men. I have never had any doubt about that in the first place, and I have said so here many times. What I take from it instead is that we as a society, men and women alike, are becoming better at encouraging and nurturing mathematical talent in women, and more capable of recognizing excellence in women’s work. I’ve said here before that the highest level of achievement within the age limit set for the Fields medals requires a confluence of both exceptional talent and favourable circumstances. Talent must be recognized, nourished, directed in productive ways, accomplishment must be acknowledged and promoted. Among the setbacks I experience every day and hear about from other women, Mirzakhani’s award offers a reason for guarded optimism, a point of evidence that sufficient dents have been made in the many layers of glass ceilings that a woman could break through all of them to the highest level.

]]>

The problem with science is that, for all its wonders, it lacks narrative and story-line. Science (and maths) is about facts, and the laboratory testing of elements.

It is not primarily about people.Women – broadly speaking – are drawn to the human factor: to story, biography, psychology and language.

This self-proclaimed people specialist keeps referring to women as “females,” the noun more often than the adjective. For instance: “Biology and nature, he suggested, will generally nudge females away from [science and engineering].” Here’s to biology, I guess. And to consistency.

Here’s one good rebuttal, with further links. This essay in particular matches a great deal of my own experience. But I also want to question the “science is not about people” line from a different angle–the one that scientists adapt enthusiastically and unquestioningly in every funding application, from individual grants with a training and/or collaborative component, to conference funding, to large institute grants. For example:

The mandate of PIMS [Pacific Institute for Mathematical Sciences] is to:

- promote research in and applications of the mathematical sciences of the highest international caliber
- facilitate the training of highly-qualified personnel at the graduate and postdoctoral level
- enrich public awareness of mathematics through outreach
- enhance the mathematical training of teachers and students in K-12
- create mathematical partnerships with similar organizations in other countries, with a particular focus on Latin America and the Pacific Rim.

NSERC pays 1.15M per year for this, and that amount does not include provincial funding or support from participating institutions. I suppose one might argue about the precise meaning of “primarily,” but the “human factor” does not exactly seem unimportant. You could also look at the webpages of individual institute programs:

The purpose of this programme is to bring together researchers in these diverse areas of mathematics, to encourage more interaction between these fields, and to provide an opportunity for UK mathematicians to engage with an important part of the mathematical computer science community.

This is very standard language. Every conference, workshop and institute program aims to bring together researchers, encourage interactions, promote the exchange of ideas, contribute to training, engage the community. Every conference proposal and grant application emphasizes it. Every funding agency demands it. Every mathematics institute derives its very existence from this notion.

And how do women score here? In light of their natural, biologically determined talents and inclinations, surely we should be looking for women scientists in particular to manage all those human interactions, or at least to participate in them significantly? PIMS has never had a female director or deputy director. Among the more than 120 participants in the program I linked above, there are 3 that I recognize as women. There are many more such examples, more that I could ever have the time to list. Women are often underrepresented at conferences (read the comment section for testimonials), both as speakers and as organizers, and when they are represented proportionally or better, this is often framed as an affirmative action gimmick rather than genuine appreciation of their contributions.

We sing the importance of communication, interaction and connection-making at the bean counters, then ignore it in our own deliberations. We take pride in choosing conference speakers based on “scientific merit,” defined as a best paper contest with an all-male jury, even when good arguments can be made that the “human factor” should in fact count towards scientific merit. And heavens help anyone who might raise the idea of inviting more women to conferences based on their alleged skills in interpersonal communication. And I don’t see women being overrepresented among institute directors, deputy directors, or other high profile research facilitators, all positions for which women should be particularly well qualified by the virtue of biology and nature.

Consistency, indeed.

]]>

Well, why Ukrainian boys and not mathematicians? I didn’t get to chat with Eugene. However, here is a conversation that I might or might not have had with an internet user that we’ll call Boris. I’ll let you decide.

IL: Hi Boris. I’m Izabella Laba and I work at UBC.

BORIS: Hi Izabella, it’s nice to meet you. I’m Boris. So what classes do you teach this semester?

IL: Actually, it’s summer and I don’t teach.

BORIS: That’s very interesting. So how many students do you have?

IL: I’ve just told you I don’t teach in the summer. But tell me about your research.

BORIS: As you probably know, I work on modulated gvoorups on questable aussifolds. I have proved that if a modulated gvoorup has a subquestable chain of hyperchenettes, then the aussifold must be oubliettable. This links several areas of mathematics and should have implications for the rapidly developing field of quasialgebraic oubliettability. You can read my papers to learn more about this interesting and exciting area of research.

IL: That sounds fascinating. What is a gvoorup?

BORIS: You can read my papers to learn more about it.

IL: … OK. But can you tell me why you are interested in gvoorups?

BORIS: It is a very interesting and exciting area of research. So what do you work on?

IL: Well, harmonic analysis on fractal sets.

BORIS: It is a very difficult area of research in which it is very difficult to have any new ideas.

IL: How do you know that?

BORIS: This is well known to everyone in the field, even if it has never been published. So who do you work with?

IL: Uhm, I’ve been a full professor for some time now. Are you assuming that I’m a junior researcher because I’m a woman?

BORIS: Women are more interested in teaching than in research. If you’re looking for more women, you should go to a teaching related forum.

IL: I’m pretty sure I’m more interested in research than in teaching.

BORIS: That’s great. So what classes do you teach this semester?

IL: You’re repeating yourself. I’ve answered this already.

BORIS: That’s very interesting. Have you seen my paper on gvoorups from 1995? It may be relevant to your work.

IL: Honestly, I doubt it.

BORIS: It’s been nice meeting you. Please let me know if you have any questions about my paper.

]]>

]]>