Skip to content
 

Research benefits of feminism

Screen Shot 2014-11-02 at 4.18.31 AM

Unlike that famous bank teller, I’m not “active in the feminist movement,” but I’ve always considered myself a feminist, ever since I heard the term (I don’t know when that was, maybe when I was 10 or so?). It’s no big deal, it probably just comes from having 2 big sisters and growing up during the 1970s.

And most of the time this attitude is pretty much irrelevant to my professional life. It comes up every now and then when interpreting research claims (see here, for example) in which the male perspective is taken as the baseline. And when I teach I try to avoid overuse of stereotypically male-interest topics such as sports.

And my feminism has made me somewhat immune to simplistic gender-essentialist ideas such as expressed in various papers that make use of schoolyard evolutionary biology [see definition below] that we’ve discuss over the years on this blog.

But it doesn’t affect my approach for partial pooling in hierarchical models, or my approach to inference from non-random samples, or the ways in which I monitor convergence for Hamiltonian Monte Carlo, or my models for voting, etc etc etc. Most of my research, even in political science, is basically “orthogonal” to feminism. Even studies that could have some sort of feminist interpretation—for example, my analysis with Yair of differences in attitudes toward abortion, or our estimate of geographic variation in the gender gap—doesn’t have any feminist content at all, at least not that I notice.

Recently, though, I had a research project where a feminist perspective made (a bit of) a difference. It was from my paper with Christian Hennig on going beyond objectivity and subjectivity in statistical thinking.

It came up near the beginning of the paper. We start off by discussing the usual dichotomy in statistics between objective and subjective approaches:

Statistical discourse on objectivity and subjectivity is at an impasse. Ideally these concepts would be part of a consideration of the role of different sorts of information and assumptions in statistical analysis, but instead they often seemed to be used in restrictive and misleading ways.

One problem is that the terms “objective” and “subjective” are loaded with so many associations and are often used in a mixed descriptive/normative way. Scientists whose methods are branded as subjective have the awkward choice of either saying, No, we are really objective, or else embracing the subjective label and turning it into a principle. From the other direction, scientists who use methods labeled as objective often seem so intent on eliminating subjectivity from their analyses, that they end up censoring themselves. This happens, for example, when researchers rely on p-values but refuse to recognize that their analyses are contingent on data (as discussed by Simmons, Nelson, and Simonsohn, 2011, and Gelman and Loken, 2014). More generally, misguided concerns about subjectivity can lead researchers to avoid incorporating relevant and available information into their analyses.

And then we say this:

A perhaps helpful analogy is to gender roles in social interactions. To get respect, women often need to choose between claiming stereotypically-male behaviors or affirming, or “taking back,” feminine roles. At the same time, men can find it difficult to step outside the restrictions implied by traditional masculinity. Rather than point and label, it can be better in such situations to identify the positive aspects of each sex role and then go from there. Similarly, good science contains both subjective and objective elements, and we think it would be best to understand how these perspectives can complement each other.

I suspect that, to many readers, that paragraph won’t fit in at all. But to me it makes a lot of sense. Conventional labels, whether of objectivity and subjectivity, or of masculine and feminine, can be a trap. The labels are not empty, they reflect real differences (being a feminist is all about understanding, not denying, the real differences that exist on average between the sexes—along with recognizing that averages are just that, and don’t represent all cases), but people can also get stuck in these boxes, or get stuck trying to rearrange these boxes. So, to me, a feminist attitude gave me a useful perspective on how to think about the important topic of objectivity and subjectivity in science and statistics. (And it’s a topic with real applications; see for example this paper which discusses how we use model checking to incorporate both subjective and objective elements into a Bayesian analysis in tosicology.)

Just to be clear: I’m not claiming that feminism is purely a good thing for a researcher, or even that it’s purely good for my research. There may well be important work that I’m missing, or misunderstanding, because of my political biases. I think everyone must have such blind spots, but that doesn’t excuse me from the blind spots that I have.

At some level, in this post I’m making the unremarkable point that each of us has a political perspective which informs our research in positive and negative ways. The reason that this particular example of the feminist statistician is interesting is that it’s my impression that feminism, like religion, is generally viewed as a generally anti-scientific stance. I think some of this attitude comes from some feminists themselves who are skeptical of science in that is a generally male-dominated institution that is in part used to continue male dominance of society, and it also comes from people such as Larry Summers who might say that reality has an anti-feminist bias.

Feminism, like religion, can be competitive with science or it can be collaborative. See, for example, the blog of Echidne for a collaborative approach. To the extent that feminism represents a set of tenets are opposed to reality, it could get in the way of scientific thinking, in the same way that religion would get in the way of scientific thinking if, for example, you tried to apply faith healing principles to do medical research. If you’re serious about science, though, I think of feminism (or, I imagine, Christianity, for example) as a framework rather than a theory—that is, as a way of interpreting the world, not as a set of positive statements. This is in the same way that I earlier wrote that racism is a framework, not a theory. Not all frameworks are equal; my point here is just that, if we’re used to thinking of feminism, or religion, as anti-scientific, it can be useful to consider ways in which these perspectives can help one’s scientific work.

P.S. It would also be fair to say that I talk the talk but don’t walk the walk: a glance at my list of published papers or the stan-dev list reveals that most of my collaborators are male. I don’t know what to say about this—it could be interpreted as evidence that I’m not a real feminist because I’m not committed enough to equality between the sexes in my own professional life, or as evidence of the emptiness of feminism: like a Christian Scientist who talks tough but then goes to the doctor when he gets sick, I’m a feminist who, when given the choice of how to spend my hard-earned research dollars, generally hires men. I don’t think I’m under any obligation to explain myself at all on this one, but to the extent I do, I guess I’d say that there are more men than women working in computational statistics right now, that I hire the people who seem best for the job, and these people often happen to be male—a set of observations, or opinions, that can be interpreted in any number of ways.

P.P.S. As promised, here’s my definition of “schoolyard evolutionary biology”: It’s the idea that, because of evolution, all people are equivalent to all other people, except that all boys are different from all girls. It’s the attitude I remember from the grade school playground, in which any attribute of a person, whether it be how you walked or how you laughed or even how you held your arms when you were asked to look at your fingernails (really) were gender-typed. It’s gender and race essentialism. And when you combine it with what Kahneman and Tversky called “the law of small numbers” (the attitude that any underlying pattern should reproduce in any small sample) has led to endless chasing of noise in data analyses. In short, if you believe this sort of essentialism, you can find it just about anywhere you look.

P.P.P.S. And, just to clarify further, of course there are lots of systematic differences between boys and girls, and between men and women, that are not directly sex-linked. To be a feminist is not to deny these differences; rather, placing these differences within a larger context is part of what feminism is about.

68 Comments

  1. Alex Godofsky says:

    As promised, here’s my definition of “schoolyard evolutionary biology”: It’s the idea that, because of evolution, all people are equivalent to all other people, except that all boys are different from all girls.

    To be fair to this perspective, the populations of boys and girls were separated much longer ago than any other human populations, anywhere from ~160 million years to ~1.2 billion years ago depending on how you count.

  2. BMMillsy says:

    I think, as a feminist, one should be careful about referring to sports as a “male interest topic.” Sure, avoiding overuse is a good idea. But in the case that it’s “stereotypically male interest”, I’m not sure why a feminist would want to use a (increasingly false) stereotype as a reason to avoid a topic.

    • Andrew says:

      Bmm:

      I agree that it can at times be counterproductive to point too hard to a stereotype, even when trying to avoid it. Let me just say that I want to avoid overdoing it with the sports examples, I don’t want to avoid the topic entirely. What happens with me is that the sports examples just flow out naturally, so it makes sense for me to work at varying the topics a bit (as here).

      • Phil says:

        You may have missed it, but in the comments about the shirtstorm post, someone said she felt a bit weird when you apologized for using a sports example and said something like “maybe I should use an example based on shopping instead.” [I may have this detail completely wrong, but the flavor is right] It’s obvious (to me, anyway) that you were being sarcastic about the stereotype that men are interested in sports while women are interested in shopping or whatever it was, but I can see how coming anywhere near the subject is can lead to misunderstandings or awkwardness.

      • BMMillsy says:

        I have trouble avoiding the sports examples, too. But I’m lucky enough to work in a sports-specific department. I do understand the point generally, as not everyone likes sports.

  3. skeptickle says:

    Jesus Christ. I would keep up on this blog because I was interested in data science and statistics. And yet you, like so many science writers, demand on pushing your ‘progressive’ politics in every context. Well, time to un-sub from the RSS feed. Go to h*** and Merry Christmas!

    • Andrew says:

      Skep:

      You seem to be a bit incoherent here. “Go to hell” and “Merry Christmas” point in opposite directions, no? Or this the rhetorical analogy to the economic plan of a loose fiscal policy and a tight monetary policy, that somehow you get something from banging in both directions at once?

      To get to the substance of your comment: I certainly don’t push politics in every context; if you think that, you obviously haven’t been reading the blog very often. But, yes, sometimes one’s political perspective affects scientific work. That should be no surprise, given that science has a political direction and that political attitudes can be informed by science.

  4. paul alper says:

    Andrew worked very hard but how many in his audience understood his reference:

    “Unlike that famous bank teller, I’m not ‘active in the feminist movement.’”

    • Bill Jefferys says:

      Hi Paul, I missed that sly comment. :)

    • Martha says:

      I got it (or at least unless there’s another reference that I’m not aware of). Wild conjecture-ish question based on sample of two (Bill and me): Are women more likely to get the reference?

      • Corey says:

        Well, the Linda example comes from the Heuristics’n’Biases program of study, so I’d expect the chance of getting the reference is independent of gender after controlling for interest in cog psy.

      • I got the reference, but I think it’s because I’ve been reading and commenting on this blog for around 10 years. Outside of this blog I don’t think I’ve come across that example more than maybe once.

        • paul alper says:

          Actually, the Linda example is part of the folklore of statistics. Andrew was very subtle because “Linda” is named in the graph and the “bank teller” is in his first line. This represents the so-called Tversky and Kahneman conjunction fallacy: http://en.wikipedia.org/wiki/Conjunction_fallacy
          ###############
          Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

          Which is more probable?

          Linda is a bank teller.
          Linda is a bank teller and is active in the feminist movement.
          ###############
          In order to explain why the second line is preferred by many, the conjunction “and” is interpreted in ordinary English instead as the “inclusive or.”
          Try this line: “I invited males and females to the party.” Clearly, though “and” is written, “or” is intended.

          • Paul, I’d be very interested to see the results of such a survey with the following responses:

            which is more probable?

            Linda is a bank teller who may or may not be active in the feminist movement
            Linda is a bank teller who is active in the feminist movement.

            ——

            I’m with you in thinking that non-technical usage in English is at odds with technical usage. People may very well interpret the original to mean that the first option has the implied “and is not active in the feminist movement” because of the wording of the second option. Being very clear in the wording would go a long ways towards clearing up whether there is a linguistic bias or a misunderstanding of probability.

            • Steve Sailer says:

              Right, Kahneman and Tversky were just being Aspergery.

              Of course, Linda doesn’t, actually, exist. She was made up by K&T. Now, most people don’t read about other people, real or fictional, in the context of psychology experiments where the professors are attempting to pull the wool over their eyes. They read about other people in novels, journalism, history and so forth where writers try to select details to communicate larger, more interesting points. So, they’ve gotten pretty good at figuring out what larger message the author is trying to communicate by selecting details. As a commenter says, it’s Chekhov’s Gun: If Linda cleans her gun in Act I, you better believe her gun is going to go off at some point in the play.

              So, the point is that Kahneman and Tversky went to the trouble of telling their subjects these specific details. The subjects didn’t observe these details, they read them in a piece of prose that K&T crafted. So their subjects assumed that Kahneman and Tversky weren’t tossing in random details to yank their chains and waste everybody’s time. Subjects assumed good faith on the part of the professors. If a novelist gives you a bunch of details about a character, which is what Kahneman and Tversky were imitating, the novelist isn’t going to throw in random details. But, of course, time-wasting and chain-yanking were exactly what K&T were trying to do.

              • Andrew says:

                Steve:

                I think you’re being a bit harsh on Kahneman and Tversky. Yes, it’s true, their work is sometimes advertised as showing the biases in how humans think, etc., in which case I agree with you that it’s quite reasonable to take a Gigerenzian position that maybe people aren’t so stupid as all that.

                But, remember, the starting point of a lot of Kahneman and Tversky’s work started with their finding back in the early 1970s that research professionals—psychology Ph.D.’s who did quantitative research studies—misunderstood some basic ideas regarding hypothesis testing and probability. Researchers were making real mistakes in real problems, overrating the strength of evidence. It is my impression that they created and interpreted their stripped-down examples (such as Linda the bank teller who is active in the feminist movement) in the context of trying to understand the well-documented mistakes in quantitative reasoning that even experts were making.

                So, no, I disagree with your statement that “time-wasting and chain-yanking were exactly what K&T were trying to do.” They may well have overinterpreted some of their findings, but I think theirs was a serious and important research program.

              • Corey says:

                “Right, Kahneman and Tversky were just being Aspergery.”

                Nope.

                A further experiment is also discussed in Tversky and Kahneman (1983) in which 93 subjects rated the probability that Bjorn Borg, a strong tennis player, would in the Wimbledon finals “win the match”, “lose the first set”, “lose the first set but win the match”, and “win the first set but lose the match”. The conjunction fallacy was expressed: “lose the first set but win the match” was ranked more probable than “lose the first set”. Subjects were also asked to verify whether various strings of wins and losses would count as an extensional example of each case, and indeed, subjects were interpreting the cases as conjuncts which were satisfied iff both constituents were satisfied, and not interpreting them as material implications, conditional statements, or disjunctions; also, constituent B was not interpreted to exclude constituent A. The genius of this experiment was that researchers could directly test what subjects thought was the meaning of each proposition, ruling out a very large class of misunderstandings.

              • Steve Sailer says:

                “A further experiment is also discussed in Tversky and Kahneman (1983) in which 93 subjects rated the probability that Bjorn Borg, a strong tennis player, would in the Wimbledon finals “win the match”, “lose the first set”, “lose the first set but win the match”, and “win the first set but lose the match”.”

                Do these fallacies show up in sports betting with substantial money on the line? Can you reliably make a living off of sports betting in, say, Britain based on the Conjunction Fallacy? Or do you quickly run out of serious punters who fall for it?

                According to Richard Feynman, that’s how famous gambler Nick the Greek made his living — not by betting against the casino, but by constructing complicated sucker bets for tourists looking to be able to tell friends they out-bet Nick the Greek. But those were one time bets.

                We have minds that evolved to interpret stories that other people telling us under a general impression of good faith. So malign conmen and conwomen find it easy to trick people. Look how practically nobody in the media for ten days noticed that Sabrina Rubin Erdely’s Night of Broken Glass cossack pogrom overwhelmingly blond gang rapist hate fantasy was self-evidently absurd.

                On the other hand, once something becomes a job with real money on the line, people get pretty logical.

            • Corey says:

              These sorts of critiques (e.g., non-technical vs technical usage) were made at the time the Linda paper on the conjunction fallacy was published 30 years ago. K&T addressed them shortly afterward with a different scenario that was not nearly as snappy as the Linda version but was much more airtight.

              • Thanks Corey. I suspect what’s going on is a combination of the two effects, both nontechnical usage, and confusion about probability. The Red/Green die problem is pretty airtight though.

            • City Walker says:

              Daniel, I’ve used the Linda puzzler in my class for 5 years. The students are physicians. Their responses split about 50/50 between the 2 choices.

  5. Bill Jefferys says:

    Andrew, what’s ‘tosicology’? The Web doesn’t know.

    It suggests ‘toxicology’.

  6. j says:

    “The reason that this particular example of the feminist statistician is interesting is that it’s my impression that feminism, like religion, is generally viewed as a generally anti-scientific stance.”

    Yeah, I would place most of the blame for this on feminists. In college there were many things that irritated me about campus feminism, but anti-science attitudes would have to top the list. STEM is male-dominated, ergo oppressive; if you really cared about the movement, you’d be majoring in women’s studies; stop trying to turn this bastion of the liberal arts into a vocational-technical school… Never mind the fact that the vast majority of STEM research has nothing to do with feminism, or the fact that getting more women into STEM is the single best way to fight the wage gap. It’s a vicious cycle because the more ignorant and hostile that feminists appear to be toward science, the less that STEM folks want to identify as feminist. Plus we’d have a lot more credibility criticizing crappy ev-psych studies if we weren’t viewed as generically anti-science.

    All of this is to say that I’m always happy when I find out a STEM person identifies as feminist!

    “It would also be fair to say that I talk the talk but don’t walk the walk: a glance at my list of published papers or the stan-dev list reveals that most of my collaborators are male.”

    I don’t know a single statistician, male or female, for whom this isn’t the case. Which is not to say everyone is off the hook, but there is a serious pipeline problem.

    • Martha says:

      j:
      Imagine the awkwardness (to use that good word brought up in the Shirtgate discussion) of a woman in STEM dealing with those feminists (not intended to include all who describe themselves as feminist) who do seem anti-science. It’s like negotiating between Scylla and Charybdis.

      Brings to mind the Dean who said to some college dorm-mates, after meeting me and later being told I was a math major: “But she can’t be a math major. She doesn’t look like a math major, she doesn’t talk like a math major.”

    • Chris Waigl says:

      Well, dunno. I’m one of those who had to “deal” with “those feminists” as a female STEM hatchling, but frankly, even then I was over the fallacy that “I heard a woman say something stupid once” is an argument of any kind. Sure, back then we tended to have a reflexive belief that meritocracy would work in our favour and that no one any more, really, was sexist when there’s so much fascinating WORK to do. But over time you mature and learn and see what thinkers outside STEM, and yes, that includes feminists, have to contribute to complete your internal representation of how the world works.

      The status of women in public life has undergone a remarkable and deep change in the enlightenment-driven (vulgo, Western) disciplines and professions, and it would take a very naive person to think that all of this change is going over without resistances, difficulties, and even re-definitions of what we’re doing. Or to think that sexism is dead among the enlightened. Being mentally prepared makes for a more serene life and for better science.

  7. Queue Steve Sailer in…. 3…. 2…. 1…

    All joking aside, I definitely tend to associate the term “feminist” as something different from “giving consideration to both genders” and the sentiment you describe as: “To be a feminist is not to deny these differences; rather, placing these differences within a larger context is part of what feminism is about.”

    It seems, in practice, more about giving special consideration to the dominant role that males have played and to an attempt to bring women into discourse through constructing a special kind of counter-balancing role for them, and/or calling out masculine “default” conceptions of social constructs. This may be a largely academic thing though.

    I don’t know if that’s really fair. I have nothing either really for or against feminism as a socio-political construct, and I admit to being fairly ignorant of the current feminist ethos, especially for someone whose grandmother was the publisher for an important 1970’s journal called “Feminist Issues”. I am happy to see more women contributing to things like Engineering, and sciences, but I think relatively few of them actually self-identify as “feminist”.

    In any case, I definitely associate the word “Feminist” with a particular and fairly narrow conception of political power and its relationship to gender roles.

    • To give an example, googling for feminism related things brings up a link to “The International Journal of Feminist Approaches to Bioethics”.

      The existence of a special “feminist” approach to bioethics is a good example of what I’d like to think of as a transient role that “feminism” will play in history. Ultimately, I’d like to arrive at a *good* approach to bioethics, regardless of label.

      Historically, it seems we have a kind of transient period, between when women were essentially the property of their husbands prior to say 1900, to an eventual full integration when women have opportunities to be involved in every aspect of society with equal rights and considerations (even if not equal numbers, as they themselves may find certain areas of society more interesting and attractive to their attention). In between these two longer-term equilibria, you have a big ball of turmoil, which I’d guess will last a couple hundred years, from suffragists in the 1920’s to Rosie the Riveters in the 1940’s to academics in the 1970’s, to boardroom glass-ceiling breakers in the 1980’s-2000’s to maybe some time in the 2050’s or 2100’s or whatever when we reach some new equilibrium.

      In a world where women are considered a “normal” part of most professions, areas of discourse, and soforth, I think the concept of “feminism” as different and special will seem quaint. A little like say “atomists” within physics now that everyone accepts the existence of an atom. During the transition period though, you expect people advocating for a new kind of equilibrium to be a pretty important voice, and also… for their voice and message to change throughout the transition period as different issues and frontiers become important.

      All that is to say that perhaps it shouldn’t be surprising that as time goes on what is considered “feminist” seems like a moving target.

      • Steve Sailer says:

        “to maybe some time in the 2050’s or 2100’s or whatever when we reach some new equilibrium.”

        We’ve been at a new equilibrium for a long time. Feminism was the New Thing in 1969 and it quickly — within a few years — came to be backed by everybody who was anybody. Feminists were pushing on an open door in the early 1970s. The impact on young people, especially at the upper end of society, was very quick. Feminism was already the orthodoxy when I entered college in Texas in 1976.

        But little has changed among young people for quite a few decades now (except that males in the lower half of society are slowly falling apart).

        • “We’ve been at a new equilibrium for a long time…”

          I don’t think so, perhaps a short-term equilibrium of stated intent, but not an equilibrium of actual effect. And remember, my prediction is that in the “final” equilibrium state, “feminism” will itself seem quaint, as women and men will think of it as pretty much totally normal to be in near-equal numbers in most portions of society.

          • Steve Sailer says:

            “women and men will think of it as pretty much totally normal to be in near-equal numbers in most portions of society”

            Won’t happen. Feminism triumphed ideologically a long, long time ago. So, we’ve been at a pretty steady state equilibrium among young people for 30 or more years, with little change since the later 1970s.

            The future will look like the present: women will tend toward the life sciences, men toward the death sciences (e.g., “I am become Death, destroyer of worlds” strikes most women as horrifying, while it strikes a fair number of young males as the most awesome thing any scientist ever said).

            Periodically, there will be giant hooplas when it is noticed that women don’t make up 50% of this or that field, such as with Larry Summers in 2005 over the dearth of mechanical engineering professors at Harvard. And various adventuresses will use the panics to promote their own career, like Doctor Faust got Larry to give her $50 million to buy support, which she then used to become president of Harvard herself. These kind of rackets will provide a nice living to the cynical forever, but there won’t be much overall change because males and females tend to find different things interesting.

            • Sure, men and women find different things interesting, but I still think there’s plenty of room for women to make headway into participating in areas they stereotypically LOVE to participate in. Your own “life sciences” example is a perfect one. What fraction of research level university profs in biology are male vs female? My experience is it’s about 80% male. Sure, tenure might have a lot to do with it, but while the “fast” transient may have happened between 1965 and 1980, the longer time-scale dynamics are still happening, and equilibrium is still decades out.

              My undergrad students in civil engineering had a pretty big mix of women. It might have even been slightly more than 50% women in some classes, that certainly wasn’t the case 20 years ago or especially 40 years ago. Until those women have been in industry for 20 years and incoming women find it “normal” to have a mix of male and female bosses and coworkers, the equilibrium is still not reached. And the fact that these women are coming into undergrad civil engineering in such numbers suggests that maybe the stereotypes about what women find interesting will change dynamically in time themselves. To give credit where it’s due, this is actually a point I’ve heard you make multiple times, about how cultural norms change and psych findings may be mostly chasing trend and fads.

              • Martha says:

                My understanding is that the percentage of women in biology has been steadily creeping up the pipeline — that more than half of biology undergraduates are now women, and that the percentage of women in biology faculty positions is increasing steadily.

                Also, I believe the percentage of women in biomedical engineering is high, as well as in civil engineering.

                (Sorry, I don’t recall the reference where I read the above recently, but will post it if I remember where it was.)

    • The pedant in me just can’t help it: it’s cue, not queue.

  8. numeric says:

    Relevant link:

    http://www.washingtonpost.com/local/women-flocking-to-statistics-the-new-hot-high-tech-field-of-data-science/2014/12/19/f3e2e486-62ed-11e4-9fdc-d43b053ecb4d_story.html

    Headline: Women flocking to statistics, the newly hot, high-tech field of data science

    It appears from this article that statistics is the most inviting STEM field for women–something statisticians should be proud of.

    (incidentally, the new, improved TNR today ran a headline that implies they think the United States was involved in WWI in 1914 (see “How ‘Silent Night’ Became the Most Popular Christmas Carol of All Time–Did the song unite the German and American troops during World War I?” The famous “Christmas truce” took place in 1914, of course (the body of the article has only British and German troops participating, so my guess is an intern stuck the sub-headline on and given the collapse of editing, it got through).

    • Steve Sailer says:

      Market research, which is the old unsexy name for data science, had a huge fraction of females in many decades ago.

      • numeric says:

        One potential warning signs for statisticians–fields which have become “feminized” (a higher proportion of women entering them) tend towards lower salaries and prestige (corporate PR being an example, and now medicine).

        • Steve Sailer says:

          Right, market research was always a genteel, low paying field.

          Some entrepreneurs, however, made a lot of money in it because there wasn’t that much competition. The founder of one company I dealt with in Texas (although he lived in Pebble Beach) told me that most market research firms had been founded by “housewives or college professors,” so he found it a pretty easy field for a hard charging businessman like himself.

  9. Martha says:

    To get back to the topic of subjective vs objective: This has long seemed to me to be an instance of seeing things in black and white terms rather than shades of gray.

    For example, consider the “objective test”. I’ve had students complain that my grading was subjective because I didn’t use “objective” tests (i.e, tests where answers were “right” or “wrong”). I would usually point out that such tests were indeed subjective — that, for example, the choice of questions was subjective, and often omitted important points such as the students’ reasoning or clarity of explanation.

    But I wonder if the traditional view of men as “objective” and women as “subjective” has conflated some people’s views on objective vs subjective. So what Andrew and Christian present as an analogy is not so much an analogy as a confounding factor. (For example, were students more likely to see my grading as “subjective” because I am a woman? In contrast perhaps with how they responded to the male colleague who told students, “I give you the grade I believe you deserve, based on all the evidence I have about your work.” I don’t know, but it is a possibility.

  10. Elin says:

    I’m not really getting what is feminist about what you wrote. Seems like a standard pop sociology analogy.

  11. Lee Sechrest says:

    This URL will take you to a (descriptive, not evaluative) review of an article appearing in the Dec. 20 issue of Psychological Science (they do publish some good stuff). Very interesting and pertinent to this thread.

    http://www.huffingtonpost.com/2014/12/08/women-success_n_6219586.html?1418049227

    Also given some favorable comments in Dec. 3 issue of Nature.

  12. Steve Sailer says:

    The ironic thing is that the field most hated by card-carrying feminists, evolutionary psychology — which is pretty much the study of sex differences — is the single field where having a roughly equal balance of male and female scientists is most important. Not surprisingly, it was inaugurated by a husband-wife team, and continues to be highly attractive to women scientists.

  13. Steve Sailer says:

    Andrew says:

    “P.P.S. As promised, here’s my definition of “schoolyard evolutionary biology”: It’s the idea that, because of evolution, all people are equivalent to all other people, except that all boys are different from all girls. It’s the attitude I remember from the grade school playground, in which any attribute of a person, whether it be how you walked or how you laughed or even how you held your arms when you were asked to look at your fingernails (really) were gender-typed. It’s gender and race essentialism. And when you combine it with what Kahneman and Tversky called “the law of small numbers” (the attitude that any underlying pattern should reproduce in any small sample) has led to endless chasing of noise in data analyses. In short, if you believe this sort of essentialism, you can find it just about anywhere you look.”

    Nah, the history of evolutionary psychology is that it was dreamed up by Tooby and Cosmides and taken up by Pinker in the early 1990s as a more politically correct replacement for E.O. Wilson’s sociobiology, which had driven Gould, Lewontin, and their friends into such a paroxysm of rage.

    EP would ban thinking about hereditary differences among humans along lines of racial descent. But, to give scientists something to think about — because you need similarities and differences to have information, just as you need 1s and 0s to have data — it would allow consideration of sex differences, on the theory that sex differences transcend race. It proved highly used because the sex category of identity really is important. It’s not everything, but male v. female is, relatively speaking, a big deal in the human sciences.

    Of course, by the end of the 1990s, evolutionary psychology was already being undermined by the rising human biodiversity concept, which had the advantage of not ruling out a priori any types of scientific analyses for political or PR reasons.

    • Jegar says:

      A good summary of the background of EP research within the United States specifically. There is a lot that happened outside U.S.A. over the last 20 years that does not really fit into what you describe though. I particularly disagree with the idea that EP “would ban thinking about hereditary differences among humans along lines of racial descent” – as far as I know this is not a formal restriction, and if there is a cultural/social restriction on this sort of research, I don’t believe it is as strong outside U.S.A.

      I feel the main focus of evolutionary psychology (maybe outside USA?) is comparative experiments with other animals that have very little or nothing to do with gender or race. That doesn’t mean to say that nobody outside USA has tried to deny differences based on race or that nobody in USA has ever done comparative experiments, just that the focus has been different.

      From what I gather (through friends and colleagues in the area in UK and Australia), the new term many are using is Human Behavioural Ecology, which puts a much greater focus on biological elements of cognitive development. From this perspective researchers examine race from a biological, genetic basis rather than the social construct or identity of ‘race’, which is really a political science variable (i.e. based on beliefs, lifestyle etc. rather than genetic heritage).

      This is not my area though, so I’m happy to hear examples of why I’m wrong!

  14. Jake says:

    And yet another example of Lewis’s Law (“the comments on any article about feminism justify feminism”) in action.

  15. RDN says:

    The comparison of objective vs. subjective approaches in statistics and feminism makes for a weak analogy, at least if you believe that prior knowledge should more commonly be incorporated into statistical analyses. The problem that feminism addresses is that prior “knowledge” is *too commonly* incorporated into assessments of male and female roles. Although the comparison was made to support the point that a mixture of both objective and subjective approaches is often appropriate, the goals of increasing subjectivity in statistics (all necessary caveats apply) and decreasing subjectivity in societal expectations of male and female roles are anti-analogous.

  16. Erin Jonaitis says:

    I don’t have anything super constructive to say, but as a long time reader (albeit one who missed the Linda reference) I am pleased to see you talking about this.

    Well, here’s one tangential anecdote. When I was a student in the stat department, I remember having the subjective sense that women and men were about equally represented in the grad student body. Then I counted. We were at about 33%. Subjective sense of probability can be a little strange. Always count.

  17. Mayo says:

    Andrew:
    1. Ah, “objectivity/subjectivity” one of my favorite philosophical topics and on which I’ve written quite a lot, mostly masculine. I realize you’re not asking for my femopinion, but I really think you might want to be a little more hard-headed with respect to trying to illuminate subjectivity/objectivity in statistics/science by reference to an analogy between gender roles. The analogy is all wrong, and decreases the chance you can say anything objective about the objective/subjective distinction. Does anyone say, “This is just my feminine belief about the priors” or “before the FDA approves a drug they strive to get a masculine analysis of the risks”? I know it’s an analogy but one that is misleading as to what is really at stake in science.

    If you’re planning to illuminate objectivity/subjectivity as these terms arise and matter in science, and in methods of learning, then you ought to genuinely clarify the relevant and important roles these terms play, rather than immediately turn them into wishy-washy distinctions, neither bad nor good, nice to have both, gotta have a little of each, it’s yin/yang, the soft heart with the hard heart, and all that squishy stuff. Be more masculine, I mean more objective, about handling these philosophical terms; they are serious and deeply important. What I mean is, sure you can do the yin/yang number, and then you invariably land up with everything’s a bit of both. It’s not that it can be faulted as wrong, but it entirely skirts what’s important about objectivity in science, and thus can be faulted on philosophical grounds.

    2. Objectivity in science means being prepared to reorient your positions by taking evidence seriously, deliberately striving to subject claims to tests capable of unearthing flaws, avoiding biases, wishful thinking, distortions of evidence, tailoring data and questions to avoid subjecting beliefs to severe criticism; having integrity and caring enough to communicate knowledge gaps to others, etc. etc.

    3. By the same token, don’t trivialize “subjective” by alluding to a sense that would automatically make all learning subjective. All human enterprises are engaged in by “a subject”, they rest upon “judgments”, there is discretion, there is the invariable entry of particular “perspectives”, backgrounds, languages, prior experience, decisions, anticipations, fears, interests. To equate your use of “subjective” with those obvious facts about all human activity, only trivially renders all human enterprises subjective. Then, of course, they also, trivially, have objective elements––you can’t just make it all up, you’ve got societal rules, disciplinary norms, you can’t walk through walls, etc. Note how different these obvious “objective” facets are from the ones listed in 2. (One of my many posts on objectivity is
    http://errorstatistics.com/2012/03/14/2752/)

    4. And what’s all this about “scientists who use methods labeled as objective often seem so intent on eliminating subjectivity from their analyses, that they end up censoring themselves. This happens, for example, when researchers rely on p-values but refuse to recognize that their analyses are contingent on data”?

    What? People who rely on p-values don’t recognize p-values depend on data and so they wind up censoring themselves?
    Sorry, I intended to just write a short note on the last point, as it’s puzzling. But then my feminine side came out, and made me want to protect you from superficiality as regards the overall philosophical topic.

    • Keith O'Rourke says:

      Mayo: Well put, but …

      Though 2 is the sense of objectivity that researchers _should_ have, few doing research likely have it (in my statistical collaboration/consulting career maybe I have met a half dozen who do.)

      So as pointed out above [Andrew: Pop sociology it is.] its about how many/most researchers deal with their senses of objectivity/subjectivity (and it reflects much of my experience.)

      However, I think you are right that it almost completely avoided any purposeful discussion of what sense of objectivity/subjectivity would be less wrong in getting a better logic of discovery.

      Also, I even googled “Christian Hennig” and “Andrew Gelman” and did not find a paper by them – guess its in the cue?

      • Mayo says:

        Keith: I really appreciate your comment. I hope Andrew will consider mine as a serious constructive remark rather than accusing me of claiming ” how wrong and trivial we are”, which I haven’t done.

        • Andrew says:

          Mayo:

          In item 1 you wrote that my analogy “is all wrong” and in item 3 you used the word “trivial” three times. So perhaps you can see how I would write, “Before you jump to saying how wrong and trivial we are . . .” I just think you’re making a mistake to sling around words such as “wrong” and “trivial” here. I just don’t think this sort of thing is so helpful.

    • Andrew says:

      Mayo:

      What I posted here is a single paragraph. Before you jump to saying how wrong and trivial we are, I suggest you read our article, which I think has a lot of good and important stuff. I think the objective/subjective thing is a disaster, and I think in our article we’ve moved the discussion forward in a useful way.

      Sorry I can’t share the article yet—it’s not quite finished. I’ll post it when we’re done with it. Just keep an eye on my unpublished articles page.

      • Mayo says:

        Andrew: I certainly didn’t claim you are “wrong and trivial” but I regret taking the time to write my comment. It was written quickly,just as regards this one point, which I never imagined was the whole of your paper, which I realize is in development (else I would have read it before commenting). I’m sure it has “a lot of good and important stuff” in it. This is a philosophical issue with potentially a lot at stake. People will take what’s said in your paper seriously. If I were writing on a topic of broad interest and importance, with any facets at all outside my field,say, that you’d written on, and you gave me feedback on something I’d blogged (which you have), I’d want to think through your comments constructively (which I very often have and do), not dismiss them out of hand. That’s the only kind of objectivity that matters. Good luck.

  18. Christian Hennig says:

    Just to leave a note here that I’m following this. The paper is not yet finished and you never know whether what’s written here can have an impact on it. The specific bit posted here is not exactly central to me personally, but I like to see it discussed.

  19. […] of simplistic gender-essentialist ideas such as expressed in various papers that make use of schoolyard evolutionary biology—the idea that, because of evolution, all people are equivalent to all other people, except […]

Leave a Reply