Ambient belonging: How stereotypical environments impact gender participation in computer science

21 Jun 2010

This paper made a bit of a splash when it was first published last year. To quote the MSNBC article:

The stereotype of computer scientists as geeks who memorize Star Trek lines and never leave the lab may be driving women away from the field, a new study suggests. And women can be turned off by just the physical environment, say, of a computer-science classroom or office that's strewn with objects considered "masculine geeky," such as video games and science-fiction stuff.

I decided, however, to hold off blogging about it until I actually had the chance to read it. I'm glad I did, as it actually contains a little more nuance than makes it into the popular press.

The paper actually has four individual studies in it, but the last three are really there to refine and shed light on the first one. If you were to watch the first study, here is what you see:

On some weekend day, a volunteer (an undergraduate who is not in CS and not a senior) enters the CS building of Stanford University to complete what they think will be a 'Career Development Center' survey. They are taken to a room, told to 'pay no attention to the stuff in the room' as it belongs to another group (and not the experimenter) and given a minute to themselves (while the experimenter goes to 'get the materials'). The volunteer then completes a six-minute word-stem completion task, a 18-question CS test 'to assess for stereotype threat' and then a questionnaire about their perceptions of the test. Then the volunteer fills out a questionnaire on their perceptions of computer science and how interested they are in it. When done with this, the volunteer is brought to the lobby for a debrief.

Most of this, of course, is smoke to distract the volunteer from the real purpose of the experiment: do the objects in the room affect the interest of women in computer science? Half the time, the room contained items judged 'stereotypical' of computer scientists (read: geek) and half the time, the room contained neutral objects. Did it matter? Seems to: women who saw the stereotypical objects were much less interested in computer science than the women who saw the 'non-stereotypical' objects.

Now, here's where the popular press will jump right to the 'Conclusions' section. But not only are there three other studies in this paper, I haven't even finished telling you about the first one! First of all, and just to poke at the validity of the experiment a bit, how did the experimenters choose the stereotypical and non-stereotypical objects? Could something fishy be going on there? And supposing that the experiment is valid, what does it mean? Why do these objects have this effect?

First, the objects: yes, they were chosen carefully. One group of volunteers was asked to (individually) list items found in the office/dorm of a 'stereotypical computer scientist' or 'stereotypical computer science major.' The experimenters kept the most common items, added similar but non-apparently-stereotypical objects, and asked a separate group to rate them on how much they associated the objects with computer scientists.

  • The most associated: a Star Trek poster, comics, video game boxes, soda cans, junk food, electronics, computer parts, software, technical books and magazines.
  • Unassociated: nature poster, art, water bottles, healthy snacks, coffee mugs, general-interest books and magazines.

Okay, so did the objects have an effect on women's interest in computer science? Oh my yes. A lot. If you look at the relevant diagram of the paper (Figure 1), you'll see that that it had a big effect. (It also had an effect on the men, too, but I can't tell if it is a statistically-significant one. I'll come back to both the statistics and the men below.) But all this only begs the next question: why?

The next three quarters of the paper are directly aimed at this question. One possibility, raised by a cited paper, is that the objects remind women that CS is a male-dominated field and that they might be the target of discrimination. Another possibility, which I came up with during my read of the paper, is that the stereotypical objects might convey unhealthiness. (Junk food and soda cans, versus water bottles?) But the hypothesis of the experimenters is that the objects influence the volunteers' senses of 'ambient belonging.'

Okay, what the heck is that? The core idea, I think, is that two things combine. First, people will infer things about a stranger or a group from the objects in that stranger's/group's environment. Thus, the objects act as what they call 'ambient identity cues.' Second, people want to feel like they belong. They want to be in situation where they 'fit,' and feel uneasy when they get the sense that they don't belong. Based on this, the authors define 'ambient belonging' as '...the feeling of fitting into an environment' and believe that their volunteers are gauging ambient belonging (into the field of CS) from the objects in the room.

Okay, but that only re-phrases the question. Why do the stereotypical objects tell women (as a population) that they will not belong? Because (the authors claim) the objects are gauged to be masculine. In other words, the objects tell women that CS = men, and they conclude that they don't belong.

The next three studies in the paper poke at this idea in various ways. Unlike the first study, the next three don't actually take place in the real world. Instead, the experimenters have the subjects read some text on a computer and answer questions. Basically, the subjects get to read about two companies / teams / etc., and rate their interest in each. The two groups are always exactly the same except for the objects mentioned in their descriptions-- one includes the stereotypical objects, the other uses the non-stereotypical objects. However, the three studies vary this basic idea in different ways:

  • In one study, both teams have a 50-50 gender ratio, and another study has both teams be all women.
  • One of the studies has the volunteer choose between the two potential employers, while another study has the volunteer rate their interest in each company individually.
  • Also, the three studies tried to measure this sense of masculinity and ambient belonging directly. One asked volunteers to rate the masculinity / femininity of each company as a whole, for example, while another asked volunteers to individually rate the masculinity / femininity of each object mentioned. Also, some of the studies asked volunteers to rate how much they identified with the teams, and so on.

In short, the next three studies confirmed that the objects mentioned will affect the interest of women (as a population) in a particular work-environment. And (using heavy-duty statistics I don't really understand) they confirmed a few things:

  1. Their 'ambient belonging' measure ('I belong here' / 'I don't belong here') better explained the reported interest of female volunteers than other explanations (such as the fear of future discrimination. Unfortunately, they didn't test my 'healthy' / 'unhealthy' hypothesis ;-)
  2. In women, the sense of ambient belonging was correlated with perceived masculinity and femininity of the objects.

(This might be a good time to re-iterate that I don't really understand the statistics, and may be a little off in my phrasing, here.)

So where is this going? The topic of 'women in computer science' is waaaay bigger than this one paper, and I still don't have anything new to say about it. The paper does point the way to one possible tactic we can use in the future: change the environments of undergraduate CS labs and classrooms. I'd be in favor of this on general grounds (man, some of the labs at my school were filthy!) but the paper suggests that this might at least reduce the entry-barrier for women. And since the 'CS nerd' stereotype is pretty damn exaggerated (as the paper notes) we might be able to make some progress just by *not* driving women away.

I have no evidence against this idea, but I have my doubts. It seems like a panacea. It's too easy, and I'm suspicious of things that are too easy. I can't believe that the massively disproportionate gender ratio we have in CS is due to a few pizza boxes and Star Trek posters. I'd be overjoyed if that were true, but I somehow suspect that there is something deeper going on here, and that we can redecorate all we want without seeing much effect. My studies continue. (But hey-- please, prove me wrong!)

Some other thoughts:

  • Man, psychology is HARD. The paper goes into great detail about all the little intricacies of their methodology, and the great pains they took to avoid biasing the volunteers / avoid confounding factors / screen for bad data / etc. It all sounds like a tremendous amount of work, and all in the hope of getting one statistically significant answer to one tiny yet/no question about one aspect of a very, very large and nebulous problem. I'm glad someone is doing this kind of work... and I'm glad it isn't me.
  • Again, I am completely unqualified to understand the statistics of this paper. I am aware that 'real' statistics is actually much less powerful than we see on TV, but I do wish I could understand this (discussing the first study):

    Can environments stereotypically associated with computer science deter women's participation? In a 2 (gender) $ \times $ 2 (environment: stereotypical, non-stereotypical) ANOVA on interest in computer science, we found no main effect on gender $ F(1, 35) < 1 $, ns, or environment $ F(1, 35) = 2.56 $, ns. However, there was significant interaction of gender and environment $ F(1,35) = 6.91 $, $ p < .05 $, $ \eta^2_p = .17 $. As predicted, in the stereotypical environment, women were less interested in computer science than were men (women: $ M = -.55 $, $ SD = 0.38 $; men: $ M = 0.22 $, $ SD = 0.85 $), $ F(1,35) = 4.58 $, $ p < .05 $, $ \eta^2_p = .12 $. However, in the non-stereotypical environment, there was no gender difference in interest in computer science (women: $ M = -.52 $, $ SD = 1.03 $; men: $ M = -0.04 $, $ SD = 0.81 $), $ F(1,35) = 2.50 $, ns.

    In particular, can anyone tell me if this indicates now much of an effect the environment had? Can we use these statistics to estimate much of the gender disparity in CS is due to the effect being measured?

  • While the studies were designed to test the effects of these environments on women, there were a few interesting tidbits about the effects they had on men. For example: in one of the 'virtual' studies (read a description and answer questions) men also seemed to be turned off by the stereotypical objects (Study 3). However, this effect disappeared in the 'real world' (first) study, and men displayed the opposite behavior in one of the other virtual studies (Study 4). In that study, the stereotypical objects had no effect on men (when judged against a pre-study baseline) but found that men were actively turned off by the non-stereotypical environment. So, the paper didn't uncover a consistent effect on men, but then again, that wasn't its purpose.
  • Not being a psychologist, I can't quite figure out how to regard this theory of 'ambient belonging.' I agree that we can directly observe some things: the objects in the room, the reported interest in computer science, reported masculinity/femininity of the objects, etc. But in what sense are we observing ambient belonging? One answer is that we are observing a relationship between inputs (objects) and outputs (interest levels, self-reported senses of belonging, etc.) and concluding that there must be this intermediate thing called 'ambient belonging.' I'm okay with that-- I'm happy to believe in lots of intermediate things that cannot be directly observed. (Energy. Money. Facebook.) But is this paper claiming that ambient belonging is real in the sense that a joule of energy is real? That someday, we will some day be able to observe the 'ambient belonging' center in an fMRI? Or are they saying that 'ambient belonging' is a convenient simplification that will later be broken down into more concrete components?
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I find this "ambient

I find this "ambient belonging" idea very powerful, as I think it precisely describes what I did not feel vis-a-vis CS (or math). Although, personally, I didn't code any of that stuff as "masculine", nor was I particularly turned off by the idea that a field might be largely masculine (hello, I mocked my mom when she suggested I apply to Wellesley, and I went to Mudd). I can, of course, likely be treated as an outlier here.

(For me, I agree with you that "healthy/unhealthy" is a more salient description of how I would read that room; some of that stuff would appeal to me (mmm, Star Trek), but in the aggregate it suggests "loser". Take out the soda and/or junk food, add any evidence whatsoever that the person ever leaves the room, and it's a different story...but for me as an undergrad, "CS" meant "living in an underground room on a nocturnal schedule and never engaging with the -- yikes! -- sunny world outside", which was just a dealbreaker. Even though I enjoyed, and did well in, CS 6.)

It really bothers me that (and this is in all fields that have been around for long enough to cohere, certainly not just CS) people associate "the skills you need to do the job well" with a certain set of personality traits (which varies by field), and then if you don't exhibit those (or can't deal with a room full of people exhibiting them) you are presumed to be not cut out for the field, regardless of your skills and aptitudes. But I do not know how to hack around this human failing.

Posted by Andromeda on Jun 21st, 2010 at 4:00 pm.

Still a gender-related effect

Re healthy/unhealthy vs. masculine/feminine: We can rephrase the difference between the two rooms all we like, but at the end of the day, we need to somehow explain the fact that men and women (as populations) reacted to the rooms differently. So if we decide that the right words are 'healthy' and 'unhealthy', we still need to explain why this repelled women more than men. And won't that land us back to where the paper started, explaining why 'health' is feminine and 'unhealth' is masculine?

Posted by Jon on Jun 21st, 2010 at 9:37 pm.

Stats

I can give you a little bit of background on the statistics. I apologize in advance if some of this is a bit elementary.

ANOVA is a technique for sorting the variance of observed results into bins corresponding to the experimental variables ("treatments") observed or introduced in the study. It says, "of the variance among these observed results, how much is due to treatment A, versus treatment B, versus other factors outside of this computation."

ANOVA works by making a number of very strong statistical assumptions -- that the data are normally distributed, and that the treatments have additive, normally distributed effects. Almost no experimental design or real phenomenon actually satisfies these assumptions, and on cursory examination this paper seems to be no exception. Fortunately ANOVA is moderately robust against having its assumptions violated, but be aware.

(There are also several Sobel mediation tests described, but these are both hard to describe and too sensitive to small sample size for their results to stand much chance of being relevant.)

Mnay of the paper's statistical significance finding look strong to me, but I am concerned by a few things. With respect to their analysis:

(0) I am having a hard time correlating their graphs to their text. In figure 1 the text describes a much larger SD for the male population, whereas the graph shows similar male and female error bars. I may be misreading, though.

(1) "Statistical significance" is not the same as significance -- statistical significance simply means that two samples are distinguishable. I don't fully understand the questionnaire or its coding that would give insight into what a difference between a -0.55 and 0.52 means, but it may be that this is describing a total change of one notch on a seven-point agree-disagree scale. If that is the correct interpretation, one might reasonably object that many of these differences are "statistically significant insignificances."

(2) The number of statistical tests described is enormous -- I count at least 60 distinct statistical tests, and that's just the ones they listed in the paper. Under those circumstances, p<0.05 and p<0.01 results are simply not unexpected -- saying that something would only happen by chance one time in 20 is unimpressive if you did 20 different tests to get that result. I strongly object to papers of this sort -- the "we ran every possible test that we'd ever heard of on every possible combination of variables, then blindly published anything better than p<0.05" sort. In my view only the p<0.001 results in this paper merit any confidence whatsoever.

With respect to their experimental design:

(3) I wonder a bit at their much smaller male than female sample sizes. Since males have higher variance on most metrics, I would have expected most experiment designs to prefer the opposite.

(4) "There was no significant interaction of gender and environment ... suggesting that men and women did not differ in the extent to which they associated the objects with computer science majors" suggests to me that they got the object choice wrong, and that the male and female participants instead associate the objects with something else entirely. I wonder slightly why they did not instead draw their items from actual computer science companies that are more or less male dominated; in my experience asking people what they consider stereotypical is just about the worst way to find out what stereotypes people actually hold.

On the whole I would say that a number of this paper's results are serious and worthy of consideration -- the "ambient belonging" looks strongly predictive (albeit of what may be a fairly small effect in a somewhat contrived experimental setup). Many of its more complex conclusions however may just be noise from analytical overfitting. This is the sort of paper that begs for more rigorous, larger followup studies, and it would be interesting to know whether such studies have replicated these results.

Posted by Grant Gould on Jun 21st, 2010 at 4:36 pm.

Re: stats

So an ANOVA can estimate the magnitude of an effect? Do I read that right? If so, how much of the difference between men and women (in that paragraph I quoted) was due to the objects?

Re (0): I didn't catch that. Now I wonder what's going on, too.

Re (1): I wondered the same thing about their scale. I'll have to show this to some actual research psychologists to see what they think.

Re (2): I note that for some tests, the paper reports $p< 0.01$. Is it safe to assume, then, that they would have stated that $p<0.001$ if it had been true?

Re (3): I believe that the volunteers were describing as participating for credit, which leads me to believe that they were Psych majors. And the field of Psych skews heavily female, my Psych-professor friends tell me. So you might be right that the experimenters would have preferred more men, but (1) there may not have been enough male Psych majors to go around, and (2) the experiment was designed to test the effect of the objects on women. I can believe that you need to also test the effects of the objects on men as well to make the ANOVA work, but how many male volunteers would they need to draw conclusions about the women?

Re (4): Why does that statement suggest to you that they got the object choice wrong? I don't follow.

Also re (4): I agree with you that CS stereotypes may not actually hold in a CS environment, and the experimenters are willing to believe it too (p. 1058). But the experiment was not designed to test how women react to an actual CS environment, it was designed to test (1) how women react to a stereotypical CS environment and (2) why. Given that the experimenters consciously sought a stereotypical CS environment (not a real CS environment) is there a better way to determine what is stereotypical than to ask people?

Also, the paper was published in 2009. If there has been a larger follow-up study, I haven't heard of it (and don't see it on the first author's webpage).

Thanks.

Posted by Jon on Jun 21st, 2010 at 9:55 pm.

Standardized = z-scores

Jon wrote:

Re (0): I didn't catch that. Now I wonder what's going on, too.

Figure 1 is apparently showing z-scores. There isn't any obvious way to transform them back to the 1-to-7 scale used in the experiment. I've written to the contact author of the paper asking for this data, and we'll see if she finds the time to write back.

Posted by Jon on Jun 24th, 2010 at 8:46 am.

Dr. Cheryan, being most

Dr. Cheryan, being most generous with her time, graciously wrote back with answers to our questions. My mail to her:

Professor Cheryan--

I am sure that you are thoroughly sick of dealing with questions
regarding your paper, Ambient Belonging: How Stereotypical Cues Impact
Gender Participation in Computer Science. However, I can promise you
that I am not part of the popular press. Instead, I am merely a
Computer Science ex-Professor, discussing the issues you raise with
other Computer Science professors.

We have two technical questions regarding your results that you may be
able to answer offhand. Well, okay, probably not, but we cling to the
hope that you might find a moment to dig up the answers for total
strangers at some point over the summer:

1) We note that Figure 1 shows z-scores. For our purposes, however,
we'd like to know how large the effect was on the original 1-to-7
scale. Is there any chance you might recall the means and deviations
of Figure 1's data, before they were standardized?

2) We found it worrisome that some of the 'stereotypical' objects
might be strongly associated with males-- particularly the technical
books, technical magazines, and electronics. Star Trek posters and
video games, sure. But if the technical documents and components of
our field are strongly associated with males, we have a much tougher
job ahead of us. (How can we change the environment if our *textbooks*
are associated with males?) Fortunately, we note that you asked your
subjects of Study 3 to rate the masculinity/femininity of each item.
Prithee, do you recall if the technical magazines were as strongly
gendered as the other stereotypical objects?

Again, we are well aware of how busy Assistant Professors are, and
that we are total strangers asking you for a favor. But if you do
happen to have a chance to find the answers, we would very much
appreciate knowing exactly how badly we are serving our female
students.

Thanks again. (And by the way-- I very much enjoyed the paper. Thank
you for writing it.)

Her reply (posted with permission):1

Hello Dr. Herzog,

I am sure you have lost all hope of getting a response to this message now that it's been several months, but I kept your message in my inbox and knew I would respond someday. That day is finally here!

First of all, thanks so much for your interest in my work and for reaching out to me. It's been great for me to see people outside of social psychology respond to my work, and I'm happy to facilitate that any way I can (even if it takes me a while).

To answer your questions-

1. For Study 1, I have the means/SDs for the question of how much they considered majoring in CS. Women went from M=1.17, SD=.39 in the stereotypical room to M=3.40, SD=1.96 in the non-stereotypical room. Men ratings did not differ across room type (stereotypical: M=3.00, SD=2.07, non-stereotypical: M=2.33, SD=1.94). I have started included more easily interpretable effect sizes (Cohen's d) in my more recent publications. I'm attaching one of them.

2. Regarding the masculinity of these objects, I would argue that CS objects are not inherently masculine but have come to be constructed that way by society and could therefore come to be constructed as less masculine. Second, many fields (e.g., biology, chemistry, math) currently have masculine objects associated with them too (e.g., microscope, calculator), yet women have entered these fields to the point where they are the majority of graduates in biology and nearly 50% in chem and math. Research has shown that women are willing to engage with some degree and some types of masculinity. Diekman et al. (2010, Psych Sci) has an interesting perspective on this: Masculine fields that women have entered (e.g., medicine) are ones that are perceived as serving humanity and affording interpersonal interaction. Thus, changing students' perceptions of CS so that more women feel there is a fit between what they are looking for in a career and what the field affords them may be key to drawing more women (and some men!) into the field.

I discuss this exact issue, and other related topics, in a public televised lecture I gave last month. If you are interested, you can find the lecture here:

Stereotypes of Computer Scientists and Their Consequences for Women’s Participation," Sapna Cheryan. http://www.uwtv.org/programs/displayevent.aspx?rID=33000

One final thing to note is that you mentioned relating this paper to your female students. Although it's possible women who are already in the field would respond similarity to these stereotypes, our work has only tested the recruiting question (i.e., how to draw women in who have not already expressed an interest). Women in the field, because of self-selection or a change over time, will respond differently to these stereotypes. We are investigating that question now.

Hope that answers your questions. Please let me know if you have further questions!

Right. So did you catch that? When the subjects were asked to rate their interest in computer science on a scale of 1 to 7, the environment alone changed their answers from 3.4 (plus or minus 2) to 1.17 (plus or minus .4). I'm no statistician, but that seems like a pretty big change to me.

(And thanks again to Professor Cheryan for taking the time to talk with us!)

  • 1. I took the liberty of adding a link from her mention of the Diekman et al. paper to our discussion of it. Also, I'm not sure that I have permission to re-post the 'attached' paper, and so won't do so. It will probably get its own post on this blog, though, soon enough.
Posted by Jon on Mar 21st, 2011 at 8:17 pm.

One more question about stats

Grant Gould wrote:

(2) The number of statistical tests described is enormous -- I count at least 60 distinct statistical tests, and that's just the ones they listed in the paper. Under those circumstances, p<0.05 and p<0.01 results are simply not unexpected -- saying that something would only happen by chance one time in 20 is unimpressive if you did 20 different tests to get that result. I strongly object to papers of this sort -- the "we ran every possible test that we'd ever heard of on every possible combination of variables, then blindly published anything better than p<0.05" sort. In my view only the p<0.001 results in this paper merit any confidence whatsoever.

Well, hold on. The main hypothesis (that the objects of the environment affected who would be interested in the field/company/team) was supported by all four studies. And the $ p $-values of the tests in question were less than 0.05, 0.001, 0.001, and 0.001 respectively. So though you might quibble with their mediation analysis, do you doubt that they confirmed their main hypothesis?

More generally, your objection above-- that 60 statistical tests almost guarantees some Type 1 error-- assumes that all 60 statistical tests are independent. But really, there's only four data-sets here: one from each study. Should we regard this paper, then, as having 60 statistical tests or 4?

Posted by Jon on Jun 22nd, 2010 at 8:37 pm.

The study assumes the stereotype it is studying...

The biggest problem I see with this study is that it assumes the very stereotype it is trying to study. They asked people to stereotype the objects that computer scientists have in their rooms, and then placed those objects in a room?! I don't see how that proves anything. When was the last time you saw a Star Trek poster or comics anywhere? (And when did you ever see it in a classroom or CS lab?) Lots of people play video games or eat junk food, and conversely I know lots of computer scientists who east healthy foods and exercise. And if technical manuals and computer parts are scaring people away from CS, um, exactly what are we supposed to do about that? (Will we change the way chemistry is done if we find that women don't like working with solvents?)

If anything, the study shows that we must work at changing the perception of computer scientists, rather than changing anything about the field itself.

Posted by Jonathan Katz on Jun 22nd, 2010 at 7:29 am.

I think the point of the paper got lost...

To reply in reverse order:

Jonathan Katz wrote:

If anything, the study shows that we must work at changing the perception of computer scientists, rather than changing anything about the field itself.

And the authors of the paper agree with you (about the first part, at least). To quote the paper (p. 1058):

Those actually in the field claim that present stereotypes of computer scientists are highly exaggerated and inaccurate (Borg, 1999). However, the stereotype discourages those who do not relate to it from trying computer science, which in turn decreases he prevalence and salience of nonstereotypical environments. Breaking the cycle may therefore involve intentionally and overtly changing the stereotypes. Once women enter the field in greater numbers, the process will hopefully build on itself by further changing environments and stereotypes associated with computer scientists and subsequently attracting more women.

And as the authors point out in the Introduction, it is especially worrying that stereotypes and environments have this kind of effect as they will discourage the affected populations from even bothering to learn what the reality of the field is. But let me point out that the second part of your statement does not follow from the first. It is very possible (and my gut instinct, at this point) that our field's problems are not limited only to the stereotypes. (Or did you just mean the paper was silent about non-stereotype issues?)

Jonathan Katz wrote:
The biggest problem I see with this study is that it assumes the very stereotype it is trying to study. They asked people to stereotype the objects that computer scientists have in their rooms, and then placed those objects in a room?! I don't see how that proves anything.

I think you are mis-characterizing the study here; I must not have explained it very well. The paper does not directly explain the gender ratio of CS, no, but that was not its goal. To repeat: the goal of the study was not to explain why our field has such a dismal gender ratio. The goal of the study was to demonstrate the phenomena of 'ambient belonging': that the physical environment alone can affect who chooses to enter a group. The main hypotheses of the paper are (again, quoting):

  1. (Main hypothesis) Environment can determine who enters a group.
  2. People infer stereotypes of a group upon exposure to that group's environment
  3. (a) The inference of group stereotypes incompatible with one's identity leads to avoidance of that group, and (b) this process is mediated by feelings of ambient belonging.
  4. A lack of ambient belonging predicts lack of interest in a domain and explains why some populations express less interest in a domain than do others.

Note that computer science is not mentioned. So, given these goals, I'm not surpised that they wanted 'laboratory conditions' for their experiment.

But given that the study used exaggerated stereotypes of computer scientists, can we safely dismiss it as irrelevant? No, of course not. It can still help us understand and change the gender imbalance of our field, but we first need to understand it on its own terms. The authors successfully showed that if the environment screams "Men!" then women are less likely to join. (And they showed this is true even if the subjects are told it is actually an all-female environment.) So how applicable is it to 'real world' situations? Well, to the effect that real-life CS labs and student-lounges are masculine environments. Which leads us to...

Jonathan Katz wrote:

When was the last time you saw a Star Trek poster or comics anywhere? (And when did you ever see it in a classroom or CS lab?)

1997, which was the last time I was in an undergraduate computer science lab.

But more generally, the paper never claimed that there was anything magical about a Star Trek poster or the comics. The paper claimed that these items had an effect to the extent that they were stereotypical and masculine. So that is what we need to consider, not the presence or absence of any particular item.

Okay, so how masculine are real, current CS labs / classrooms / lounges? I don't know. It's been a long time since I was in an undergraduate environment. If only--- If only! I say-- If only I could think of a CS professor who could take photographs of real, live undergraduate CS environments so that we could see for ourselves!

More seriously: If we want to evaluate the possible real-world effect of this 'ambient belonging' business, we need to evaluate the actual masculinity/femininity/neutrality of 'live' CS environments. And of all my readers, you've got the best access to these places. But (and I mean no offense by this) you and I may not be the best people to *judge* the masculinity of these environments, being male computer scientists. What is highly gendered to other people may be invisible to us.

So, any chance I can talk you into photographing some undergraduate CS spaces around University of Maryland? I'll happily post them to get some non-CS opinions. And for comparison, it would be useful to see the equivalent spaces for the Biology department, given that that field skews in the other direction.

Jonathan Katz wrote:

Lots of people play video games or eat junk food, and conversely I know lots of computer scientists who east healthy foods and exercise.

I'm not quite sure what your point is.

Jonathan Katz wrote:

And if technical manuals and computer parts are scaring people away from CS, um, exactly what are we supposed to do about that?

The paper, unfortunately, did not state how masculine the subjects found each individual object. We have nothing to contradict the possibility that the manuals were regarded as neutral, and that the bulk of the effect came from the Star Trek posters and video games.

But in any case, the obvious answer to your question is that we could start by asking why.

Jonathan Katz wrote:

(Will we change the way chemistry is done if we find that women don't like working with solvents?)

Again, I'm not quite sure what your point is. Can you explain?

Posted by Jon on Jun 22nd, 2010 at 8:29 pm.

What is highly gendered to

What is highly gendered to other people may be invisible to us.

Aw, you get big smooches for knowing this.

Posted by Andromeda on Jun 22nd, 2010 at 9:11 pm.

Thanks for the reply...

Given the way you state the conclusions of the article, my criticisms no longer apply. I guess I was more questioning what we are supposed to do with these conclusions, since we can't change stereotypes that don't exist.

Posted by Jonathan Katz on Jun 23rd, 2010 at 7:31 am.

Step 1: decide your goal

Well, I've always found that "decide your goal" is a good first step. Do you care about this? If so, do you care about this more than other things? As I said on your blog, there's a million things worth doing but only time enough for a few. And given that I have no reason to believe that this particular issue is part of your job description, it's really up to you.

Posted by Jon on Jun 24th, 2010 at 8:43 am.

I don't see how assuming the

I don't see how assuming the stereotype is necessarily problematic, given that prospective entrants' perception of a field is at least as important as reality in governing their choice of whether to enter that field.

Posted by Andromeda on Jun 22nd, 2010 at 9:09 pm.

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[...] to leave or avoid math-intensive fields? What are the operational preferences here? Are women concluding that CS labs are 'male' environments? Are they choosing to avoid CS because they've concluded (falsely, I assert) that CS does not [...]
Posted by Sex Differences in Math-Intensive Fields | Jonathan Herzog on Nov 27th, 2010 at 3:36 pm.