I completely agree with your implied meaning, but the linked article gave me pause:
Dorothy Stein, the first of Lovelace’s biographers with sufficient training to seriously assess Ada’s frequent proclamations of her own extraordinary mathematical genius, concludes that Lovelace was scarcely the prodigy she imagined herself to be, and struggled to grasp concepts that would be standard fare in a modern high school course in AP calculus.
Judging mathematical genius between separate centuries seems fundamentally flawed.
Indeed, it is difficult (although of course that's a sword that cuts both ways: since AFAIK Lovelace's work lead to zero practical work, zero people building on it, and had zero influence on later mathematicians or engineers or logicians like Turing, and her claim to fame is solely our judgment of her genius and historical priority), but let's not exaggerate the difficulty: she wrote her program in 1843, and the AP exams began in 1955 or so (hard to find dates), so that's 112 years. Was the teaching of calculus so revolutionized during that span that Ada's "frequent proclamations of her own extraordinary mathematical genius" (taking Stein at face value that Ada was something of a braggart) are consistent with her difficulty?
the AP exams began in 1955 or so (hard to find dates), so that's 112 years.
Except the quote was:
that would be standard fare in a modern high school course in AP calculus.
So that's some more years, but I don't think it's really germane. I'm not saying that the time gap proves she's a genius; rather, the time gap makes it harder to ascertain.
On another not-imo-germane-to-the-discussion-note, mathematics education was more or less overhauled during the post-war period in many countries. Mathematics education as an academic discipline, I believe, was an innovation of Klein's that fell out of his work in geometry.
She's not the hero we deserve, but she's the one we need right now.
EDIT: Well, that's the last time I make a Batman joke.
Rear Admiral Grace Hopper is much a more inspiring computer scientist, imho.
The most important thing I’ve accomplished, other than building the compiler, is training young people. They come to me, you know, and say, “Do you think we can do this?” I say, “Try it.” And I back ‘em up. They need that. I keep track of them as they get older and I stir ‘em up at intervals so they don’t forget to take chances.
When Grace Hopper gets mentioned, there tends to be an uncomfortable silence about COBOL. COBOL is actually quite interesting, since it was a serious effort to make programming more accessible and a commercial success. It's also universally reviled by people who do programming for fun.
Beyond the gender stereotype of women being bad at tech, there is also the stereotype that women don't do technical tinkering for fun. It's a bit unfortunate that Hopper's most famous accomplishment ended up becoming the shorthand for programming as dreary, unfun 9-to-5 bureaucratic grind.
Ehhh ... ok, you do realize not having a better mascot is weak evidence in favour of positions on talent distribution and performance considered sexist right?
Emmy Noether? Grace Hopper (maybe, as discussed above)? Rosalind Franklin?
It's true that it's evidence that there are so few, but given the historical status of women in academia, it is quite weak.
They probably aren't used because "First Computer Programmer" sounds cooler than "Valuable Contributor to Field X".
Yeah, because instead of a false example we could use a real example, such as a woman who wrote the first compiler... but then, most people (including our target group) would just ask: "what is a compiler?"
Therefore, a false hero may be politically preferable. Until the truth becomes known, and then we either have to accept that this strategy backfired, or make the truth forever our enemy. Which happens often when politics comes first.
From the National Bureau of Economic Research: Powerful Women: Does Exposure Reduce Bias? (2008).
India randomly assigns some provincial villages to be governed by women (hoorah for policies implemented by random assignment!). These researchers found that exposure to women leaders shifted some stereotypes
We exploit random assignment of gender quotas across Indian village councils to investigate whether having a female chief councillor affects public opinion towards female leaders. Villagers who have never been required to have a female leader prefer male leaders and perceive hypothetical female leaders as less effective than their male counterparts, when stated performance is identical. Exposure to a female leader does not alter villagers' taste preference for male leaders. However, it weakens stereotypes about gender roles in the public and domestic spheres and eliminates the negative bias in how female leaders' effectiveness is perceived among male villagers. Female villagers exhibit less prior bias, but are also less likely to know about or participate in local politics; as a result, their attitudes are largely unaffected. Consistent with our experimental findings, villagers rate their women leaders as less effective when exposed to them for the first, but not second, time. These changes in attitude are electorally meaningful: after 10 years of the quota policy, women are more likely to stand for and win free seats in villages that have been continuously required to have a female chief councillor.
My opinion of India's government just went up several notches. Controlled random trials on entire villages? We need to elect more mad scientists!
My methods prof brought this study and a few others on natural opportunities for experiment the first day. I think it was to try and get the polisci majors to govern more like mad scientists if they ended up in applied politics instead of theoretical.
Maybe quotas would be easier for voters to swallow if they came with time limits. "X% of the council has to be women for the next ten years, but after that you can vote for all men again." And then ten years later the stereotypes have been reduced, and the quota isn't needed as much.
Or if they were symmetric. N% of seats are required to be held by men, N% by women. Symmetry does wonders for perception of unfairness.
Though I agree this post might be better suited for the Open Thread, The Science Babe, physics Ph.D. Dr. Deborah Berebichez, comes to mind.
However, I am questioning the merit of generally emphasizing minority groups in order to reduce their associated disadvantages. I wonder if this emphasis perpetuates a sense of having to differentiate between groups of people. Ideally, any gender or race based disparity would merely be a statistical coincidence rather than a consequence of racism and sexism. My hopes are that the primary reason for combating racism and sexism is rooted in a very humane understanding and compassion and NOT in further emphasizing the "obvious" difference in the groups yet at the same time calling for a certain "equality". My hopes are to diminish the conscious recognition of differences, solely based on characteristics like gender and race, in people in the first place.
Did you check out the study above on quotas shrinking stereotype and competence gaps?
When it comes to gender, until we get a whole lot more transhuman, we will still need to be aware of biological differences related to pregnancy. We need a different model to reintegrate women into their jobs after leaves (or we need mandatory paternity leave to compensate for the biological difference). Trying to get to the point where we can ignore gender too fast really means asking women to fit the male model.
Something I posted to Facebook earlier today; please bear that audience in mind when reading it:
It's Ada Lovelace Day, a day for celebrating and publicising the achievement of women in the sciences, and since I talked about the Nobel Memorial Prize in Economics yesterday, I figure I'd go two-for-two and talk about Elinor Ostrom today.
In March of this year I had the pleasure of attending a lecture by Elinor Ostrom, about her work in common pool resources, which won her a Nobel Prize in 2009. To date, she is the only woman to win a Nobel Prize in this category. I wanted to ask her a question about organised crime.
Imagine you own one of several fishing boats on a lake. The fish are a common pool resource. Without any kind of governance, the lake will be over-fished, because no single fishing boat has any incentive to restrict their catch unless all of them do, and it's too easy for any single boat to defect from any mutual agreement, so no agreement ever gets made. This is known as the Tragedy of the Commons.
There are a few options that tend to arise from this situation. The first is government intervention, where legislation is passed to limit how many fish any one boat can catch. This tends to go wrong, because legislators don't know very much about the fishing industry.
The second option is to merge all the fishing boats into one big fishing company. It now won't over-fish, but it will cause monopoly problems. Fish consumers will pay relatively more money for relatively less fish, and some mechanism has to exist to stop anyone else setting up their own rival fishing company. This is not optimal.
Elinor Ostrom's work concerns the third option: stable self-governance between multiple parties. This is ridiculously hard to achieve in real-world situations. Ostrom carried out extensive field studies in developing countries to find out under what circumstances a common pool resource could be sustainably managed by the people using it, and by extention, how we might design systems to let people do this. It has important implications for the development, welfare, politics and environmental protection of poor and wealthy countries alike.
During the Q&A of the lecture, I wanted to ask her if she had considered extortion in organised crime as a potential area of study. It fits the criteria of a common pool resource, and economists love organised crime, so there's a wealth of data about it. Unfortunately I wasn't picked to ask my question.
In June of this year, ten weeks later, she died of pancreatic cancer, and now I will never get to ask it.
If you want people to write blogs on day N, perhaps it would be better to say it on day N-7. Even better to say it on LW on day N-14, so at day N-7 there is enough data in the discussion.
I'm a big fan of the mathematician Matilde Marcolli. In string theory, Eva Silverstein (cosmology) and Mina Aganagic (string math). Anastasia Volovich does twistors.
Two book recommendations:
I think this should have been a link in the Open Thread to the post on your own blog, not a crosspost.
I see someone has stated their disagreement with a downvote, but let me state mine with a comment instead: I think this post is too valuable to be hidden in the Open Thread.
this post is too valuable to be hidden in the Open Thread
Could you make explicit your argument and reasoning for the high value of this post?
I see someone has stated their disagreement with a downvote, but let me state mine with a comment instead: I think this post is too valuable to be hidden in the Open Thread.
Where do you see that, exactly?
I thought the recommendations here might be a lot more highly technical than those for the general audience on my blog. Also, I had a worried feeling that linking would decrease engagement and make it look like I was just being self-promotional (since I get paid based on pageviews).
If Ada Lovelace is the best example of a notable woman in computing 50 years from now, I will eat my hat.
It's obvious there are more notable men in STEM history than women. Thus a question that arises is if the notable women who do exist in STEM history are there because they're better than the men, having overcome despite discrimination, or if they're being retroactively singled out, a desperate lowering of the bar to identify SOME example.
However, this question of retroactive affirmative action is not the issue recognizing Ada Lovelace is trying to address. I don't know enough history to know if Lovelace is a worthy example, but I think it is important for people in general to identify with successful people similar to themselves so that they can imagine being like those people someday. Personally, I don't particularly need to look at someone's gender to identify with and be inspired by them. When an impoverished immigrant Jew like Einstein overcomes Nazis and scornful teachers and whatever else, I, despite being a Chinese woman from Pittsburgh, identify with his struggles and don't let people thinking I'm stupid because I'm smiley or shy or a woman or whatever deter me. However, many people do need role models to help them realize nascent interests in STEM subjects, especially if the peer group they identify with are not typically interested in those topics. For most, it's easier and more enjoyable to hang out with your friends doing girl things than go off on your own to explore programming or science in a room full of boys who ignore you.
Regardless of innate or learned differences in men and women, by far the first factor in this result for past populations is the number of men in STEM vs women historically, which is why the present is such an exciting time for women in STEM- there are a lot more females in STEM now! There may well be more notable women in STEM in our lifetimes than have ever existed. This idea inspires and motivates me to become one of them!
Do some men find posts singling out notable women offensive/ annoying because they think elevating a perhaps undeserving woman is unfair to all the deserving men? The suggestion of discrimination and affirmative action towards one set often upsets people in the complement of that set because humans have a strong instinct for fairness and hate injustice. Affirmative action is unfair to people who had nothing to do with past injustices, even if they're benefiting from them, so I sympathize with the negative comments, although I don't know whether two wrongs make a right in practice. My hope that we will soon have a bevy of women undeniably worthy of recognition and honor in STEM history.
Rather than writing about a specific person, I wrote a blog post on Why Ada Lovelace Day is Important. It includes a review of a thorough study on gender bias among science faculty published a few months ago. It's really distressing to me that even in 2012 there exists this much male privilege in science academia.
Why should the origin of the y-axis be 0 rather than 15000, or wherever the average minimum wage falls, or what the average 5th percentile lab manager wages are? When comparing two values, deciding which proportion to report can determine which values are actually being compared.
At the very least the y-axis should match the caption which says "The scale ranges from $15000 to $50000".
Upvoted. Several times I've seen recommendations to start graphs' y axes at zero by default, but it's a tip that's starting to grate on me for several reasons.
Usually, when I look at a graph, the y values' variation is at least as relevant as the values themselves. I want that variation to be clear & obvious; if someone's going to represent it on a graph, I want it spread across the available space. Cramming it into a small range near the top is a waste.
Visually compressing variation can be just as misleading as visually expanding it. Which is more misleading is case-dependent.
Sometimes I want to read numbers off a graph as accurately as I can. If the plotter stretches the y axis because they think I'm too dumb to read labels, that makes my task harder.
If the y axis is on a log scale, you can't make it go to zero without some distracting gimmick like making the axis discontinuous.
People can't decide whether this rule applies to bar charts specifically or graphs in general.
For me points 1 & 2 apply here. (Although, as it happens, I don't like that figure 2. It's too close to a dynamite plot for comfort, and it's a space-hungry way to show me two averages & two standard errors. You could communicate the same information with a small table, or even a line of prose. And Kindly's right about the caption. But starting the y axis at $25k is the least of that chart's problems.)
These are excellent points. Unfortunately, I'm a bit hampered by the fact that I stole the chart in question from the original study (pdf), and they used only "dynamite plots" in their paper. After reading your links on the topic, I can definitely see why this is bad. I'm appending a short note to this effect as an edit to my original article.
Thank you for bringing this stuff to my attention.
Normally I'm not so stuck on having 0 be the bottom of a graph, but this is a case where there's no reason for anything else. You're comparing only two things, so you aren't zooming in to help the reader pick out fine gradations of detail.
Today is Ada Lovelace Day, when STEM enthusiasts highlight the work of modern and historical women scientists, engineers, and mathematicians. If you run a blog, you may want to participate by posting about a woman in a STEM field whom you admire. But I'd love to have people share women scientists/mathematicians/authors in the comments that they think we could all stand to read more about.
