Look, let's be honest here.
Bennett isn't doing a survey. He isn't doing science. He isn't even doing journalism.
Hardly. His effort, this one time, was a lot more thorough[1] than the numerous womens studies "research" that we routinely get here on slashdot. What exactly can you fault him for above, other than using MT? What would you do different?
[1] IOW, He didn't start with a conclusion and then try to find evidence to support it. He started with a question ("Is this about race or context?") and attempted to honestly find an answer using the cheapest method known to man. Could he have done this better? Sure - if he had more money to run a proper survey. In contrast, the numerous womens studies we've been seeing here have all been of the form "It's all mens fault - now to look for proof" which is not how science is done.
Or that states with high gun ownership have about the same rate of non-gun murders, but more than twice as many gun murders?
I assume that you are talking about US states? Everywhere in the world it is generally accepted (empirical data, and all that) that you're *less* likely to experience murder in areas with high gun ownership. I haven't seen stats for US states, but would welcome (not facetiously but seriously) a link to those stats as they seem out of line with all other recorded data.
Anyone who knows what EITHER of these systems are is not going to be confused.
Trademarks are not for people who already now off the system. It's not to protect the trademark holder but the consumer. In this case it's not only possible but probable that the consumer would be confused. For example, if groupon named their PoS system "Windows", that'd have gotten them sued, so why did they try that move with "Gnome"?
Groupon were being dicks, and it backfired.
The difference being the women are attacked because they are women, and the guys are being attacked because they're assholes. If you can't see the difference, you are part of the problem.
What makes you think that the women weren't attacked because they were assholes?
Yeah, that's all well and good, except for the fact that Facebook has reached a critical mass; resistance may not be futile but it's damn hard:
1) I have friends all over the world; literally, on every continent. Is there a better centralized method of communicating with them? Should I send out a broadcast e-mail to all of them every time something noteworthy happens in my life? (Noteworthy actually means noteworthy in my world, I'm not logging check-ins every time I go to the grocery store....)
Group chat doesn't work on your phone?
2) I have friends that only communicate via Facebook. They won't talk on the phone, they don't text, and they rarely check/answer e-mail.
I hate to be the bearer of bad news, but I'm afraid that those aren't friends.
3) Ever tried dating in the modern world without Facebook? It's instantly assumed that you're hiding something, which to be fair is frequently the case for people that refuse to share Facebook with would-be mates.
Actually, Yes. I have dated in the modern world (four to three years ago when facebook was at its peak). When denied facebook details (username, whatever) potential mates became more interested in me! There's a very good reason for this - women looking for a stable relationship are frequently turned off by attention-whores. Telling women that I don't do facebook merely increased my desirability as long-term partner.
> Do you realize that before pension you spend more of your active life [barring sleep] with your colleagues than with your family and friends? How many people understand this simple fact?
It's not 1950. Those people will likely be a different set of people 3 years from now. You don't need to be "pals" with these people. You just need to get the job done. They are quite disposable.
These are people that you TEMPORARILY work with. Playing with them is not required.
Your point is probably where all these "get girls into tech" issues stem from. Men get into tech, find out that there's little to no socialising and are okay with it. Women get into tech, find out that there's little to no socialising and feel "left out".
It's just that companies should try to advertise jobs in ways that attract more female applicants, and create a work environment that facilitates them.
What makes you think that the current advertisements are excluding/less attractive to females? And what is so special about females that you need a different environment to function in? You are insulting both men and women in one go, and you don't even notice...
Regression to the mean is, by definitive, a regression model that is applied to a set of data which fails to disprove the null hypothesis of "no correlation".
No. You're incorrect - from this link:
"In statistics, regression toward (or to) the mean is the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and, paradoxically, if it is extreme on its second measurement, it will tend to have been closer to the average on its first."
This definition is directly contradictory to what you thought the definition was.
You keep throwing out ad hominem attacks, but I have to wonder if you have even taken the standard freshmen and sophmore level math ciriculum for the sciences (statistics, linear algebra, discrete math, single and multivariate calculus, and differential equations) based on what you are writing.
It is not ad hominem to point out that you are making a mistake even HS students don't make. And your error of understanding is not just with "regression to the mean", it's with all the other linear algebra and statistics and logic mistakes you've made over the course of this thread. Be happy that I'm only pointing out one of them - I flat out ignored the incorrect logic statement you posted earlier. For a refresher logic course, you can see this - first semester notes. Note that this particular document was been online since around 2006 so you've had plenty of time to read it if the information was not available elsewhere.
Once again I must point out that stringing together random terms you found on wikipedia is no substitute for actually knowing the subject.
I read your post. I ignored your claim of regression to the mean because there is no factual basis to support such a claim. That would necessitate that the trend is statistically insignificant,
There is no such requirement. Who gave you the idea that regression to the mean only applies to "statistically insignificant trends" (you made that up too, by the way - there's no such thing. "Statistical significance" applies to the testing of a null hypothesis)
which could easily be proved if it were true, In the social sciences, a P-value of only
The data sets consist of thousands of women graduating with CS degrees every year. It is not like astronomy and astrophysics where the number is low enough that there is some possibility of random noise distorting the signal over a period of a few years. With about a million data points over two decades, the Central Limit Theorem is very applicable.
Of course, if you can show using Gaussian probability in an appropriate regression model that the null hypothesis cannot be disproved, I would be willing to look over your calculations, but with so many data points, the Central Limit Theorem is clearly in full effect.
None of what you said makes sense - did you only just now look up statistics on wikipedia? You said above that regression to the mean does not apply, and now you say that the central limit theorem applies - those things go together (something you won't find out by skimming wikipedia, I'm afraid). Oh sure, you've thrown in some other words you don't understand, like Gaussian, but you still got the most elementary thing wrong - Regression to the mean applies whenever the central limit theorem applies.
I briefly taught both logic and statistics at a university, do you want me to try to find my old notes so you can quickly clue up on what all these things mean, and why your logic is off? Skimming wikipedia whenever you encounter a new term is not really a good way to learn anything, and it's obvious to those in the field when we meet the people who just skimmed for keywords.
I already posted evidence of the existence of artificial barriers. In fact, it was extremely relevant evidence as it was directly related to this article. The participation of women in academic computer science programs has decreased since the 1980s. By some measures, the decrease is by almost 200%.
All that proves is evidence of a decline. Nothing more.
There are two possible factors for that change:
1) Artificial Factors 2) Natural Factors.
Nope, there are more (which, had you bothered to even read my post you would have seen) such as regression to the mean (which was illustrated in my previous post).
A change in the actual physiological nature of women born over the last 30 years can be pretty thoroughly disproved, as I have done previously. By logical deduction: A+B->C => {C,'A}->B, we know that if natural factors can be disproved as a cause of this, then artificial factors must exist.
That is not a proof; I'm sorry, but that "proof" above really would be laughed off any respectable journal. Natural factors cannot be disproved of this because the current situation may be a regression to the mean (only one of several possible explanations).
Demonstrating that natural factors can cause experiences does not logically imply that natural factors cause a specific experience. That is akin to claiming that because most people die of natural causes, the person I found face down in a pool of his own blood with a knife in his back must have died of natural causes.
The question that I was asking was not whether there COULD be natural factors that contributed to the gender disparity in CS, but whether it could be conclusively demonstrated that natural factors were a significant factor. Can you demonstrate that women are naturally disinclined toward computer science the way that have conclusively demonstrated that smoking is a significant cause of lung cancer?
Please read my post again - just because I cannot conclusively prove that unicorns don't exist doesn't imply that your claim that they do exist must be true. In the same vein, just because I cannot conclusively prove the nature argument that doesn't imply that your nurture argument must be true. Science does not work that way - Just because A is unproven does not imply that B is proven.
So again, we get back to my original points which were:
1) There existence conclusive scientific evidence that artificial barriers exist that keep women out of computer science.
No, there doesn't. You keep claiming this, and you repeatedly claimed that there are several peer-reviewed studies to support this position but you have yet to post a link to any of them.
2) There is no conclusive scientific evidence that women are naturally disinclined toward entering computer science.
Because there is no evidence for A, you should assume that B is correct? My word...
It seems that more and more mathematicians are using a new, high level language named "research student".
