Django Girls one year later
lwn.net
lwn.net
I was going to show this to my daughter but after reviewing the slides, I think I'd prefer not to focus on whatever negativity/discrimination occurs in the industry but rather the positive aspects of encouragement/camaraderie/sorority.
It's probably appropriate for women and girls who have encountered those setbacks but my daughter's old enough to benefit from programming but young/naive enough not to have seen much of the frustrations cited in the slides.
The pedagogic design is really good as well, see the Coaching Guide and Organiser's Manual. This is quality stuff.
I am not trying to attack you, more so just commenting on this type of phrasing.
Wouldn't it be more effective to simple say, "Going through their website, it seems like one of the best Django tutorials I've seen" -without the gender comment at all?
Reading that comment, it made me think that normally you consider gender when you consider the quality of a tutorial, but in this specific incidence, it doesn't even matter.
Just something minor to think about.
I didn't follow it through though :P I mean to learn it someday but other stuff keeps getting higher priority.
I suppose that could attract a certain audience but I think a number of girls could feel a bit uncomfortable being pigeon-holed as liking all things "girly".
When I was in High School I would have been aghast if someone held a "guy's programming workshop" with weight-lifting and sports-talk.
One of the deeper issues that will probably never go away for many people in tech (no matter their gender) is the realization that completely fitting in is unlikely to ever happen, and that maybe this is a good thing. To pick up one of the metaphors used in the article: yes, if you're a squirrel, at first glance it may seem that all the other creatures in the forest are completely identical badgers - but upon further investigation it turns out they're all aliens from thousands of different planets, each wearing badly-made badger costumes [which, by the way, is also almost exactly the narrative of the original presentation - just watched it].
The issue isn't really the things, but in feigning interest in the things that don't interest you. You don't have to pretend to like something, but at the same time you can still find ways to share time with those that do. You cannot design an event which is all things to all people, the answer to being inclusionary is not to be dull, instead it's about inspiring people, and you might as well have some fun trying to do it.
There are games and activities that don't gender stamped all over them, yes. But cupcakes and yoga are pretty close to the activities which have some gender-attachments.
Male hackers rise up against those who would steal thy cupcake-loving birthright!
Do I like cupcakes? Sure. Do women enjoy laser tag? They kick my butt plenty often. But it makes the workplace less accessible to people who don't like cupcakes or laser tag.
Really I wonder if we're just seeing that a workplace naturally has a culture, not everyone always fits in, and because in this case the divide roughly aligns with a protected class we are caught off-guard and concerned.
(Getting rid of culture in workplaces doesn't seem like a solution)
So it was cupcake tasting this week. You don't like cupcakes? That's fine. Next week it's yoga. Don't like yoga? That's fine. The week after that it's etc...
The way you want to paint it is that you have to like certain things to be 'one of us', the real message is that you can be different and still be 'one of us'. As I said before, you can't be all things to all people. The idea is to make things inclusionary by being fun, and I hope they continue, even if people want to make a point of being offended about eating cupcakes at a programming class.
As would I. I found the PyCon2015 talk by Ola and Ola rather too cutesy, but I liked the djangogirls' tutorial online just fine. I can imagine there are others who find the online tutorial too dry, and would like some of the cutesy stuff to maintain attention or interest. All we can conclude is that these techniques are not for the likes of you and me.
> I don't think those sort of tricks have a net positive impact on your numbers.
These are all didactic methods. Not everyone learns something best in the same way. As far as I'm concerned, there are still some people whose learning needs are not met by current mainstream methods. Any variation that attracts more people into the field ought to have a net positive outcome.
Consider this too: books for young children have lots of pictures in them, whether they're storybooks or textbooks. I can clearly recall a time when I was 6, and the first thing I'd do with a new science textbook is look at all the pictures. Back then, I found the books for older children rather dull. I grew out of that phase, as did millions of other children. Who is to say that these cutesy addons don't perform an analogous role in the early stages of some programming newbies?
But in general, women can bear "girliness" even if they don't like it, and it feels a lot less threatening than machoism and more attractive than, say trekki-ism.
There are a lot of men too who find the mono-culture in the industry hard and feel like outsiders. I'm not sure that's helpful to women feeling isolated; but we can hope the industry slowly recognises the problem and learns to attract a more diverse group of people with a more diverse set of skills that will enable a more diverse set of solutions.
Take the graphics in the presentation: in my last project, we struggled (and failed) to find anybody with both technical and artistic skills. People with artistic skills rarely show up for technical jobs it seems, and that's a pity.
When reading this kind article I wonder how useful it is to pitch it as a fight between badgers and squirrels. 87% of squirrels work in a profession hostile to badgers, and 88% of badgers work in a profession hostile to squirrels. Having been personally in both environments once, even if it was a very short time, I can't help to see a big lack of common understanding of each sides plight when they are a minority.
I was going to use X and Y before I thought about chromosomes.
It would certainly feel more natural if the squirrels and badgers were equally well represented. When we reach that point squirrel identity will become just as diluted as badger identity. As long as you're a minority, you can stick together by defining it as a common trait, but that sort of thing will dissolve very quickly in larger numbers. Being a squirrel (or being a badger) is not an identity, but it may seem that way as long as you're the only squirrel in a badger forest.
This is all a bit long-winded way of saying "I think it will be alright in the end".
And then you have the issue that in this forest, the job of maintaining the forest and the hobby of playing in the forest merge together, so groups that formed by badgers who play together carry over their group behaviors, including the exclusion of outsiders, into their work of maintaining and growing the forest. They likely don't even mean to do this most of the time.
And do we really believe that squirrels and badgers are fundamentally that different?
The ending of the fable seems a bit open ended, like a plot twist thrown in at the end but never resolved.
This is a good point, and I think this mindset could go a long way towards avoiding the sort of demonizing that often undermines conversations on this topic. Surely a large part of the dynamic is that the statistical majority can naturally come to regard itself as "normal" (in the normative as well as statistical sense).
I do think we miss something, though, if we overlook the fact that, taking a step back, the vast majority of professions (especially lucrative ones and those that come with a substantial amount of social power) are badger-dominated. This is probably not an accident and, whatever the cause, there are good reasons to think this situation is systematically unfair to squirrels. And while it doesn't doesn't come about because badgers are all jerks, we also need to remember that personally exonerating all the badgers is not really the point, and will not solve our problems.
You may have "exonerate" backwards in your head?
absolve (someone) from blame for a fault or wrongdoing
If we only look at CEO/president professions in different industries, the highest majority was in CEO for minor construction with 96% majority, followed by CEO for electric installation at 92% and CEO for health and child care at 84%. Badger, Badger, and Squirrel respectively.
The piece does a petitio principii in assuming that squirrels and badgers are both naturally predisposed as species to perform the same tasks. They may be, but it's a pertinent conclusion to the analogy and so can't be assumed.
(In my experience, if you want to talk about "groups" in programming companies, it's mostly geeks vs. non-geeks, with men and women in both groups.)
To make two separate groups equal? I don't understand what is complex about that. They are separate groups according to how they are often treated in the workplace.
For example, from my very rough memory:
- People were upset there weren't more women in the armed forces.
- The armed forces lowered PT requirements for women so that more women could make it in (less pushups, slower mile times, can sit down in formation)
- Currently people are mad because that treats women differently. Among other things, it gives a sense that all women are weak and need extra accommodations, and that can hurt them in the eyes of men in the force.
So we have this struggle of wanting to include more women, but we have to figure out how to do it without favoritism.
There are good reasons for increasing diversity, and if that means women, with their naturally lower muscle mass get a lower PT requirement, that is not really favouritism.
I do find this easy to say, in spite of the fact that my company has exactly 1 other person of my race (out of 100+) [1]. Though I am in the other "dominant group" (engineering)...
[1] This has been the case for most of my career, and my life was not significantly different in the few cases when it wasn't true.
Just because some of us (programmers) managed to unexpectedly strike gold (in this economy) doesn't make us "dominant" in most areas of life.
Programming is still lucrative enough for most people that they chose this over the job they were originally trained for. That is one of the reasons (and not the only one) women want to be part of such groups, and there they are the minority.
Also my perception is not that development teams are necessarily "dominated" by nerds. It's a cliche which is often wrong.
Again, the goal is not to make everyone the same, but to make sure there aren't any social groups that are somehow marginalized away from society's seats of power, and software happens to be one such seats of power.
The categorization into geeks and non-geeks, while perhaps useful for identifying social cliques, is not at all useful for correcting society's power imbalances.
Hint: what the powerful have in common is not sex, but money. If you really wanted to make a better society, you would focus on eradicating that discrimination and gap. But then, that probably won't win you any friends or popularity contests, so I guess I understand why you focus on the low-hanging fruit.
Because we should be able to happily enjoy our differences in one area (gender), and still not be judged in our ability to perform something completely unrelated (programming).
Obviously a social programme centered on cupcake tasting and yoga is catering to who one might consider stereotypical girls. But there are (I guess, I'm a white male in an engineering job after all) many ladies who don't want to disguise as androgynous (un-gendered?) trying to fit in, just to be able to have the job they want...
And, frankly spoken, I for one welcome a more gender balanced office. Because we are diverse and should enjoy interaction with each other. Work related (as equal peers) or not (as different gendeds).
This isn't true at all. Lots of fields had clear gender imbalances and explicit hostility, and yet the minority gender had little trouble entering. For example, medicine, law, pharmacy, HR, advertising, professor of subjects which don't use math, etc.
Any theory which predicts that math/physics/cs/EE has few women is inherently flawed if it doesn't also predict that medicine/law/advertising have plenty of women.
I am not sure where you're going with this, but you can't make such a comparison at a given moment in time. The reason is that struggles usually follow power, and so it is likely that at any point in time, a marginalized group would concentrate its efforts to penetrate positions that imbue power. As the power structure shifts, so does the struggle. You can't equate professions that hold different amounts of power at different times. Certainly up until some decades ago, law and medicine carried much more prestige and influence -- and hence, power -- than math and the physical sciences. In fact, software's gain of prestige correlates quite well with the drop in women participation. It is quite anomalous in that the existence of the field long predated its power. Law and medicine, OTOH, are professions that have been seats of power for almost a millennium.
A model that correlates low female participation with high power -- and later, increased participation after a struggle -- predicts both observations. It is not such a surprising or sophisticated theory; historians have seen this pattern so often that it is almost banal. This pattern is so regular, that it's relatively easy for us to predict the future: fifty years from now, assuming the power wielded by software remains high, women participation will equal men's, and it will be hard for people to believe that that hasn't always been the case. Unfortunately, even though the result of the fight is certain, we still need to fight it. That is the price history exacts from us.
(I.e., I have no idea why you consider academic physics to have more power than academic biology.)
I also have no idea what you mean by "a marginalized group would concentrate its efforts". Are you implying that women don't make individual career choices based on their interest and aptitude, but instead "concentrate [their] efforts" in some sort of collectivist power grab?
That's a bit scary. I always thought women were just people like me, making selfish individual decisions to maximize their money/lifestyle/career enjoyment.
Certainly. Non-hegemonic groups are marginalized from seats of power. After a long struggle, they may increase participation. Put another way: groups with more power tend to preserve and increase the power difference between them and less powerful groups, while the less-powerful groups may gain a share of the power after a struggle.
Sadly, it's not my theory, but one of the most elementary theories -- backed by countless evidence -- of the social sciences, supported by studies in anthropology, sociology and history (with some backup from social psychology, too).
Can you state your theory clearly, or, at the very least, state what evidence compels you to doubt the current scientific consensus?
> Make sure to include a clear definition of "power", and make sure this definition is clear enough that I can at the very least evaluate "more" and "less" power.
I have done so on numerous occasions in the past in our conversations. Please refer to them or look up "power" on Wikipedia. The short description is influence, and if you'd like a description with a more quantitative "feel", I'd say the power a person has is the number of people they can influence indirectly (i.e. graph reach) summed over the magnitude in the change of behavior they cause in each affected individual.
> I.e., I have no idea why you consider academic physics to have more power than academic biology
I don't. See my other response to you.
> Are you implying that women don't make individual career choices based on their interest and aptitude, but instead "concentrate [their] efforts" in some sort of collectivist power grab?
I'm stating the much-observed, well-known fact, that society pushes and directs us in various directions. What we see as "free choice" is, in fact, "free choice under societal pressures and restrictions". That behavior is not collective but individual, only biased. Just like any fair coin is free to make a choice how to land, yet we can make very accurate predictions on the result of a thousand coin tosses. Collective behavior is not always the result of collective decisions.
> I always thought women were just people like me, making selfish individual decisions to maximize their money/lifestyle/career enjoyment.
All of us make selfish individual decisions, but the (probabilistic) fitness function is largely determined by large-scale, emergent properties of the system. Think of individual particle movement and temperature or of Brownian motion. There are no collective decisions involved -- only individual "decisions" and local interaction -- yet the end result is that global factors heavily influence the distribution in behavior of the individuals. The effect of social influence on personal choice has been heavily studied in social psychology, and, in fact, in zoology too.
Or men figure out the "thankless" part equally quickly but aren't as bothered to receive encouragement from others as the women?
The definition you give here almost does that, but how do I assign a number to "magnitude in the change of behavior"? You've not defined a "hegemonic group" either.
Anyway, since I can't quite understand your theory, maybe you can clearly state a hypothetical observation which would prove your theory incorrect. That's usually a good way to illustrate what a theory does and does not predict.
For example, to disprove my "more math less women" theory, you should find a broad category of similar careers, run linear regression on math content vs % female, and find a flat or upward sloping line. I.e., the same analysis as was done on Scott Alexander's post (see my link), but with the opposite result.
You don't. Read what I wrote.
> You've not defined a "hegemonic group" either.
If you're interested, look it up. I feel a strong sense of deja-vu.
> maybe you can clearly state a hypothetical observation which would prove your theory incorrect
I think I've done it twice in the past when talking to you, so I'll only provide a short abstract here (and again, it's not my theory but the consensus theory): If groups with power were not to resist social mobility (i.e. for less powerful groups to obtain more power) we'd see a constant shift in power distribution, which would be very fluid, while what we observe is the complete opposite: a very stable power structure that then breaks and gets restructured relatively very rapidly during revolutions that are rare. So the pattern is long periods of stability and then quick changes brought about by some explosive event or a demonstrable pattern of slow power acquisition through many struggles. When it comes to women, the pattern is often the latter (there's a simple explanation for that), but you can see how women gain access to politics, law, medicine etc. only after very long fights against very strong opposition (that invariably cite innate ability as the barrier).
> For example, to disprove my "more math less women" theory, you should find a broad category of similar careers, run linear regression on math content vs % female, and find a flat or upward sloping line. I.e., the same analysis as was done on Scott Alexander's post (see my link), but with the opposite result.
Two problems with that. First, yours is not a theory but a description. Second, it is not a very relevant one because it doesn't explain the constant change in participation, nor the gender-gap in the software industry. Finally, while "more math less women" may have always held on average, the slope has changed. I don't think anybody minds if the gender distribution in physics is 60-40%, even if that difference is entirely due to innate ability. So your description does not even compete with mine because it doesn't even try to explain the same phenomenon, which is the one we care the most to explain.
That has little to do with the 4:1 or even 10:1 difference we see in the software industry.
Then we are back to power being a non-ordinal concept.
...more power...
If power is not an ordinal concept, this phrase is meaningless.
I'm also confused as to how you can even determine that such a "constant shift" isn't happening - in terms of edges in your influence graph, they shift regularly. Yesterday I met a new person at work and we now interact and influence each other. The power digraph has gained 2 edges. Could you explain how you quantify this?
You're reading things that I'm not saying. It is an ordinal concept, but we don't have the ability to measure it well, only notice large differences. You can think of it as a quantity for which we have very inaccurate measurement devices.
> I'm also confused as to how you can even determine that such a "constant shift" isn't happening - in terms of edges in your influence graph, they shift regularly. Yesterday I met a new person at work and we now interact and influence each other. The power digraph has gained 2 edges. Could you explain how you quantify this?
Because in this discussion we are talking about groups (social mobility in individuals is an interesting, yet somewhat different discussion), and when we look at a large number of people, it's easier to approximate power through proxies such as income, percentage of powerful roles such as CEOs, leading journalists etc. (it's harder to compare power in individuals, because it's hard to tell which is more influential, a media personality or the CEO of a large company, especially as the latter's influence might sometimes be hidden).
Shifts in power from nobility to the bourgeois class, or in the relative cultural and technological power of Europe, were sudden changes of relative homeostases. Similarly, you can track power distribution between men and women, or between whites and blacks in the US. They point at very stable states that are violently changed, or (usually in the case of women), a faster rate of smaller revolutions (or a more steady rate of change). The difference between male/female and race hegemonies is also well understood (and seen in many other cultures), because the classification of women as "strangers" is always very different from that of actual foreign ethnicities.
You now say this: "it's easier to approximate power through proxies such as income, percentage of powerful roles"
Lets work with this specific prediction. If a group has a tendency to enter a powerful role with probability p, and there are N members of this group, then the shifts in power distribution will have standard deviation (in percentage terms) of 1/sqrt(Np(1-p)).
That doesn't seem to agree with your "constant shift in power distribution" at all.
Also, I fail to see how your formula is meaningful at all, as it has nothing to do with power dynamics. At best, it describes the distribution of the number of powerful people in a random sample. Well, OK, how is that helpful? It cannot describe any shifts in power as it assumes independence, where our understanding of power is anything but (you are more likely to be powerful if you're close to powerful people). The actual dynamics is a collection of non-linear processes in a complex system. A very, very crude example of a somewhat similar process is that of segregation[1] with the addition of random populations during the run. It is processes with strong correlations between neighboring agents that tend to show stability pockmarked with rare bifurcations, which is exactly what we see in human society.
When I went to study history in graduate school, I dreamt of applying math to historical events. Playing with cellular automata to recreate certain shifts in history is fun, but eventually teaches us little, as we cannot say much more about the model than the same qualitative descriptions historians give anyway. It is sometimes cool to figure out the values of certain variables in the model and assign them meaning (like the "despair level prior to the French Revolution", but even these numbers don't tell us much because the models are so sensitive we can't be sure we got them right, and even if we did, it's virtually impossible to measure the values directly rather than figuring them out retrospectively. Therefore, speaking about events in broad qualitative terms is often the best we can do (compound cellular automata's Turing completeness with the non-linear ODEs defining the automaton's rules and the difficulty measuring variables directly and you get very little predictive ability).
This is clearly wrong - I demonstrated a stupidly simple alternate theory which disagrees with the consensus, but still lacks constant power shifts.
Rapid shifts in the composition of various fields would debunk basically every theory that presupposes human nature doesn't rapidly shift. As such, your theory proves very little, and other theories (e.g. mine) make the same predictions. So why cling to that theory, rather than, say, my theory of p=A - B x math_content + second_order_corrections?
My theory predicts more things (e.g., it predicts % women in academia, % women in finance, % women in tech vs non-tech roles) and is vastly simpler. How is that not a win?
Your theory didn't even explain the data (in the software industry), and had nothing to say about power. Basically, it can comfortably exist beside the consensus theory as a second-order effect (and the data actually looks like that is probably the case, explaining representation differences of up to 2:1).
> So why cling to that theory, rather than, say, my theory of p=A - B x math_content + second_order_corrections?
Two reasons: 1. your theory doesn't explain the anomalous software industry (neither the very low participation nor the sudden change) while the consensus theory does, and 2. your theory doesn't explain the lack of representation (and possible correction after well-documented struggles) in fields of high prestige and little math (such as law, medicine and politics). In all those fields: law, medicine, politics and software, women participation was (or is) far lower than 30%. It was/is lower than 20%.
You might think that singling out software is uninteresting from a statistical perspective, as in Scott Alexander's regression it was just a single (outlier) data point, but in fact, the software industry is larger than all "heavy math content" professions combined, and holds more power in today's society.
> My theory predicts more things (e.g., it predicts % women in academia, % women in finance, % women in tech vs non-tech roles) and is vastly simpler. How is that not a win?
Because it predicts fewer things, and not even what you claim it does. At best, it predicts fewer women than men in certain subjects, but that's it. However, we see that while the binary relation "fewer" may remain, how much fewer decreases over time. Second, it only holds (even as a binary prediction) when you look at the past few decades -- far too short to look at social change -- which means it does not explain the exclusion of women from law, medicine and politics. Third, it does not explain the way-too-low representation in CS, nor the drop in participation. The consensus theory explains all of it, for any time duration. It even explains interesting shifts we see in, say, education (more women as prestige drops, while in CS fewer women as prestige rises). Yes, it's more complicated, but fits reality better, plus it's supported by lots and lots of data.
1. Women had enormous trouble entering those fields (and, in fact, are almost as well represented in the physical sciences). They won their position after great struggles. You'll note that some of those fields where women have had better success (after a long battle) have high governmental regulation and/or high rate of government employment, which makes it easier to allow women in through regulation after a successful political battle. The private sector has always been more conservative and more resistant to social change.
See: https://en.wikipedia.org/wiki/Women_in_medicine, https://en.wikipedia.org/wiki/Women_in_the_United_States_jud...
2. Women did not use to be so under-represented in software. There's a clear trend of women leaving software, starting in the mid-eighties: http://www.npr.org/sections/money/2014/10/21/357629765/when-... Women participation in software is on the decline, unlike any other white-collar profession, requiring math or not.
According to belorn, the minority gender will be pushed out by the majority group. Based on what you say above, this effect should be larger in medicine/law/HR/advertising than in software. Hence, belorn's theory fails to predict reality.
Your theory of government employment fails to predict reality as well. Academic sciences also have large gender disparities; physics has very few women, while biology has lots. These gaps pretty clearly mirror the CS/medicine gaps outside academia. Yet government involvement in physics academia is pretty similar to government involvement in bio academia.
> Academic sciences also have large gender disparities; physics has very few women, while biology has lots.
Academia is less interesting to begin with because there is little difference in the power held by different fields (certainly between physics and biology today). Participation can therefore depend on many factors (perhaps side-products of some other process) that people have little interest to examine or change. Those differences are no different from the high participation of women relative to men in ballet dancing. It's hard to pinpoint the causes, and there's little reason or urgency to study them because there's little power imbalance involved (there is more funding directed to studying more serious diseases than less serious ones, unless there's some other good reason to study the less harmful ones).
If you claim that "power" drives everything, yet fields with no power difference have disparities which directly mirror the disparities you claim are driven by "power", that suggests there is an underlying theory that doesn't use power at all and which predicts more things.
By Occams razor, the latter theory is the one which should be used.
That's not always enough to fund sufficient research, especially as those avenues of research show no more promise in uncovering a more fundamental model or validating/rejecting theories better than the ones that are currently explored.
> yet fields with no power difference have disparities which directly mirror the disparities you claim are driven by "power", that suggests there is an underlying theory that doesn't use power at all and which predicts more things.
If only you were right about the facts then your (unique, I must say) theory -- which I can only guess at[1] because you won't state it clearly -- would merit a closer look, but you're not. You are equating existence of bias with existence of bias, but with no regard to effect size. Here are the facts: http://www.randalolson.com/2014/06/14/percentage-of-bachelor...
CS participation was the same or higher than math and physics, and now it's significantly lower. The difference today between participation in math and physics vs CS (and engineering) is far higher than the relative difference between biology and physics. Indeed, it is higher than the relative difference between English and physics.
The social power theory is currently the only theory that has enough evidence to support it, and it gathers more evidence every day, which is why it is the (current, at least) consensus of the scientific community. Your theory (whatever it is), describes neither the observed differences in academia nor in the industry and runs counter to the body of knowledge we've accumulated about power dynamics, group behavior etc.
[1]: If your theory claims innate ability is a major cause of the difference, then it has been disproven. No differences in innate ability were found to be even in the ballpark of the participation difference we see in society. At this point in time, we can say with a high degree of confidence that innate ability is not a major explanation. Even evolutionary theories would reject ability-based explanations, as there is little reason for such huge differences in ability (way beyond difference in physical strength) in a species where the two sexes play almost identical roles (compared to, say, insects). If you have another theory, please state it.
Yes - and this contradicts belorn's theory.
My theory is very simple: more math less women, with other factors being secondary. Here is Scott Alexander doing some pretty good regressions (r=-0.82, p=0.0003): http://slatestarcodex.com/2015/01/24/perceptions-of-required...
There is lots of evidence of innate ability playing a significant role in this. Here are some papers:
http://www.ams.org/notices/201201/rtx120100010p.pdf http://itp.wceruw.org/Hyde%20Science%2008.pdf http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3057475/pdf/nihm...
(Note that putting agreement with me into an abstract is career suicide, so you'll actually need to skip ahead to the data tables.)
My theory predicts % of women in academia in bio vs physics, % women in IT office work vs softer office work, % women in quant trading vs back office, and many more. Do you have any evidence at all which contradicts this?
Scientific consensus also disagrees with that theory. We believe that the reason is related to power disparity not simply being a minority group.
> Here is Scott Alexander doing some pretty good regressions (r=-0.82, p=0.0003).
Except that it explains little, as women participation in all fields is rising. So while it may always be the case that you'll find that correlation with mathematical ability, it matters little, as it explains smaller and smaller differences. In fact, a low analytical writing score may correlate better than a high math score. Where things get weird is in CS, and worse: the software industry.
> There is lots of evidence of innate ability playing a significant role in this. Here are some papers...
That's not what the papers show at all. The greatest difference I spotted was twice as many boys as girls over the 99th percentile. We are talking 5x-10x participation gap in software.
Fine, there might be an underlying theory that explains everything better than the "power" theory, BUT YOU HAVE TO PROVIDE IT before you can argue that it is superior.
http://philip.greenspun.com/careers/women-in-science
Obviously this is about averages, there will be several women here to whom the theory does not apply.
That theory is even wrong for science in general, especially considering that women participation has been increasing, and that some scientific fields -- that are just as demanding -- are actually dominated by women.
This predicts the % of women in academic physics relative to academic bio, IT relative to HR, and quite a bit more. Anyone who disagrees is welcome to try and find cases where this theory fails to fit the data.
That you continue to believe this theory despite so much contradictory evidence is perplexing.
Also, it's a bad theory in that it's a description rather than an explanation. Even supposing it fit the data better than it does, why would it be the case that more math = less women? I mean, no one suggests that men are 5x or 8x better at math than women as direct studies clearly show it is not the case. So even if it were a good description (though it isn't) it is not the least bit explanatory. The ultimate explanation of such a theory is still likely to be social.
It is probably true that women, on average, are more empathic than men, and therefore would prefer professions that involve working with others more, but that difference is nowhere near the actual participation rates that we find, so it can't be a major explanation.
A "theory" which fits the data -- on average, of course -- much, much better than yours would be "women choose professions with less money and less prestige". This "theory" is surprisingly predictive because, amazingly enough, women choose to be paid less money than men even while doing the very same job, so it must be right.
[1]: http://www.unwomen.org/en/what-we-do/leadership-and-politica...
[2]: https://www.american.edu/spa/wpi/upload/2012-Men-Rule-Report...
At first, I blamed the Editors.(I just figured the person/persons didn't understand the material, and only corrected serious grammatical errors?)
As years went by, books/tutorials became better, but even the better ones Left Out Steps? They just expected me to know what they are poorly writing about? If the information was free--fine? It bothered me when I paid $39.99 for a poorly written technical manual. (I will pay for thin books! I've never picked up a book, and felt weight equated with cost. The thinner the better?)
I went through Djanjo Girls tutorial and with every page--it felt good. It was to the point. It didn't leave out steps. Yes, I will repeat; it didn't leave out steps! It didn't go off on tangents.
I wish them well. To any future writers out there; less is more. I've thought about writing a technical manual, and I am seriously considering using a cartoon format. Maybe not literally, but less is more. There's no need for overly long sentences, and pages to explain what could fit in a well written paragraph. If a topic is important, put an askerick in the margin?(As a reader, I take those Tips seriously. I will read other material, until I grasp what you are trying to get across.)
To those of you just starting out in Computing--it is definetly easier to learn this stuff now.
Isn't this going to create bitterness and animosity between genders? Why don't men get a leg up?
What's to keep these from bestowing attitude of entitlement in women? I already hear some of the most vocal women in tech trying to ban the word merit.
It's amazing how people think that there are all these barriers to programming for certain groups of people which must be overcome. There aren't. Sit down, grab a computer and a book, and learn to code. If you're good at it, you'll get a job, and people will respect you.
If you can't learn to code on your own, you probably don't have the mental skills necessary to be a good coder. (Critical thinking, drive, determination etc).
I do not know whether you are in a position of power, but I note that this argument is often advanced by people in positions of power.
Or are they deleted from the Internet by those in power?
There is nothing to "solve" here. Let people do what they want to do.
The comparison with fashion design is also BS. For one thing, there are lots of male designers (especially the famous ones) and then the number of fashion designers is a lot lower than the number of programmers.
And this is not as irrelevant a choice as whether to play with dolls or lego: Programming is a skill which allows for social upwards mobility like nothing else. Just assuming women (and minorities) don't want that, is a bit too easy.
http://www.npr.org/sections/money/2014/10/21/357629765/when-...
http://www.randalolson.com/2014/06/14/percentage-of-bachelor...
http://www.nsf.gov/statistics/nsf13327/pdf/tab33.pdf
The first thing to note, is that both the number of men and women getting CS degrees dropped: the entire field went from ~42k BS degrees to ~24k degrees. There were about 10k less men, and about 8k less women graduating in 1996 compared to 1986. The number eventually rebounded for men, but didn't recover for women until 2003. So something drove men and women out of the field, and women stayed out of it longer.
The next interesting thing is the number of masters and PhDs per gender. Neither of them dropped (so the percentage of BS graduates getting MS and PhD actually increased!). So it was still desirable for men and women in the field to get their masters and doctorates.
So the question isn't why the number of women plunged, it's what drove both men and women out of CS, and what caused it to grow for men? I would probably hypothesis that CS was seen as a risky degree, so while men are generally less adverse to risk (see all the dangerous jobs they do) and got a degree, women choose more stable degrees (though those interested remained, as I think the number of PhD and Master degrees show). Now that CS is now seen as a stable career, we can see there is more interest to join. Of course, that is only looking at the data cited by what you linked, there could definitely be other circumstances.
I don't know about that. Men consistently study fields with higher income potential than women. The current theory is that when CS started gaining prestige and power, the same thing happened as with all professions that carry power and prestige -- women were pushed out (and by that I don't mean that there was some conspiracy, but society simply started directing women away from CS).
I still feel that saying "women were pushed out" is the wrong way to phrase it. We can see from the data, that both men and women were "pushed out" of the field, with men recovering from the drop earlier. After reading a bit more, it could be that marketing in the 80's (as suggested by the NPR article) negatively effecting both women and men (which was left out of the NPR article) entering the field, but women ended up more effected.
Side note: drops like this have occurred in other fields at different times. Psychology actually ended up losing a lot of men in the 70s, while women increased. I am sure we could find a few other examples as well.
Absolutely. Many researchers compare those shifts with changing attitudes towards certain professions (say, by counting certain words when they're described in the media etc.), with women participation usually correlated negatively with prestige.
In any case, much of the distinction between masculine and feminine professions is traced back to Victorian times. Of course, similar differences have existed much longer than that and in many cultures, but the Victorians elevated the distinction between gender roles into an elaborate system of social codes (e.g. they had certain rooms in the house more appropriate for men to spend time in, and other for women).
Second (and unrelated to the discussion, really), I don't know where you get your assumption that learning to code in college is too late. I've been in this business for twenty years and some of the very best developers I know only learned to program in college. If anything, I'd say that not going to school at all and having a weak background in algorithms/mathematics is a much greater stumbling block for some software achievements than not programming before school, but even that is probably a bad generalization. Excellent developers come from all backgrounds.
There is evidence which prooves discrimination and unfavorable bias against women in technology. Therefore, there is nothing wrong with creating organisations for women.
Fact is, several DjangoGirls "graduates" who have never done any programming have gotten programming jobs within a year. So apparently, there is some benefit to their on-boarding and motivational efforts.
People who have never done any programming? Attending some course and then getting programming jobs? I don't think this is a great idea.
There is absolutely no barrier to entry here. Learn to code, at home, on your own, like everyone else does. Make an OS. Make games. Publish them. Make open source projects.
If you're not already doing all of the above, chances are you'll make a terrible programmer, and the industry will get more bad programmers - as if it needs more.
IT simply attracts too many people of one kind and interest, and it's detrimental to the industry's output. For instance, we can't attract or keep people with creative design or artistic skills in the industry because of the mono-culture in many workplaces. It doesn't matter if those people are men or women; there are a lot of men who also get tired of working in a hardcore IT environment.
I have a friend who's a nurse; that sector simply can't attract men, even though there's a clear need for male power in some of the more physical demanding jobs. It's not about "equality" or "political correctness"; we need their skills.
I have no problem finding Python developers; but I can't find anybody who can do the design, usable interface and graphics while still having enough coding skills to support the project. We need more diverse skill sets and hence, a more diverse group of people. Not because they are women or black or gay or loopy artists; but simply because we could produce something better.
Projects like these might attract a more diverse group of people than stereotypical coders.
Why are girls special? Why do they get red carpet treatment?
That's going to give us a workforce of a lot of women who feel entitlement beats merit.
I generally think these kinds of "reverse discrimination" arguments are mainly BS. There definitely is discrimination or at least unfavorable biases about gender in technology. Diversity initiatives don't even come close to compensating these disadvantages.
Why onboard women? Why give them silver spoons? Why is this a thing?
DjangoGirls is no "silver spoon" by any means. It's hard work and many of the participants struggle to get through the tutorial in a day. Still, this "silver spoon" as you put it, doesn't come close to equalizing the evident discrimination.