I don’t know. Perhaps the process is discriminatory and perhaps not, but stating naked percentages doesn’t tell you one way or another.
You mean are they getting hired at higher job titles 1 year out of school, then women?
The results of that study show that at whatever title they are starting out at, both men and women make the same.
Now you could say, are more men being hired at higher job titles than women (1 year out of school)? I.e., what is the chance that a man 1 year out of school is going to be hired as an Engineer II instead of Engineer I, compared to a woman. That’s a fair question, but that’s a separate study that then needs to control for all other variables which might lead someone to be hired straight out of college at a higher job level than someone else.
Either way, the study wasn’t making a determination as to which job title pays more.
Not if you don’t want it to tell you that, it won’t. I think maybe you are just wrapped up in “debating”. (seriously). Take a step back and look at it again. Do you really not think a 74% discrepancy is not tied to some form of discrimination or perceived bias?
Really???
We need to work extra hard to determine that in a country where the two genders are not treated equally that a 74% difference is not based primarily upon gender??? Look, the article you linked me too, I didn’t even read. Well, I read up until the part where it had twitter quotes after every paragraph. Did the article have any hard data that says the 74% pay gap is - not - due to gender bias?
No I do not. Some smaller percentage almost certainly is, but I work in tech and it’s clear that women often pursue a different career path even though they start with the same qualifications as men. That often leads to a different level of earnings. If you don’t believe me than ask my wife who also works in tech and actively promotes women in technology and has an executive position and makes hiring, firing, promotion and pay decisions for both men and women. She openly bemoans the fact that it is difficult to get women to do technical work and they opt to move into marketing or sales or other less technical areas. Frankly I don’t blame them, I only stick with the technical work for the money, if I was younger I’d want to do something less boring.
OK
You give me your real life experience, which unlike most people on SDMB, I accept, I don’t dismiss it as being “anecdotal”… you seem legit to me, I have no reason to doubt you. But then some other person posts three articles from journalists who say the exact opposite of what you are saying.
I can speak vicariously for the security industry It may not be that men and women are paid differently for the same work. There the discrimination is that men get almost all of the high paying senior level jobs because of the old-boys network.
Yes, it’s not. Or to say, the % difference between groups doesn’t tell you anything about why it is there.
Yes, the article is trying to explain a scientific study. Which they linked to. You can go read the actual study if you want.
But if you think that a simple % number is going to be enough for you to describe “discrimination”, than reading the study itself might not help.
As I said earlier, this is actually basic regression. One needs to understand how a regression works, what it says, in order to understand how you might get evidence for discrimination or not.
The results are pretty conclusive on this, from many studies: there is no, or very little evidence, of pay discrimination based on gender.
Those articles don’t say anything of significance. They give a simple % difference between groups. That’s not evidence of discrimination.
They are not scientific studies, which is what is needed here (and several have been linked to here, that support the argument that it’s not really happening).
The difference is this: given that you have, lets say, 30% difference in pay between men and women…overall…you want to know WHY there is a difference in pay.
So you run a regression (I’m simplifying here. Regressions can be very complex, but most work on the same basic principle as I’ll describe)
To do that, you get all sorts of data on things you think might affect pay. So you say, I think these variables affect the pay a person gets:
- Gender
- Level of education
- Number of years of experience
- Number of hours worked
- Number of jobs held over the last x years
- Number of overtime hours worked
- Type of job held
- Type of company working for
- bla bla bla
You put all these variables in a regression. Each one tries to describe a little bit about the variance…ie. the difference of 30% you observe…and tries to describe WHY it happens. Each one tries to explain its own contribution to the 30% difference you observe.
So the regression spits out some results for you. Each one of these variables has a number…a coefficient. This coefficient can be interpreted as the % of the variance it explains. I.e., the percent of the 30% gap you first observed. It also gives you a statistical significance level (meaning whether what you find is likely to be due to random chance, or is unlikely to be from chance). Lets ignore that for now, because it isn’t important in this context.
So this is what tells you whether…gender…is the reason why there is a 30% gap. All these models, however, are telling us that gender is…NOT…the reason. But that the 30% gap can be explained mostly by all these other variables, and gender itself is left to explain only a tiny % of the gap (low single digits).
That’s how you actually show what explains what (or is correlated with what, but lets not get into that right now).
So this means that, yes, overall women make 30% less then men. But it’s not because they’re women! It’s because they may have lower working hours, different job types, different companies, different education levels and types etc.
Now of course, the regression models can get much more complicated than this, especially in dealing with the error terms etc. But that’s not relevant here right now.
So this is why simple % difference in outcomes between 2 groups doesn’t mean discrimination, because there can be any number of other things different between those two groups (on average)…other than their group affiliation.
No they aren’t. They’re presenting numbers without analyzing them to explain why there are differences when gender criteria are used. I am sure there is discrimination and an unfair wage gap but using statistical jiggery-pokery isn’t helping to do anything about it.
Ok, good description you gave but as you say, lets keep it “scientific” lets focus on one area as much as possible and not compare the 30% across all jobs and careers and look at one category at a time. Men with graduate degrees earn 74% more than Women in Silicon Valley. If that were a 10% difference then I would say yes, the math is a little “fuzzy”. But 74% is not the same as 10%, is it?
http://peninsulapress.com/jointventure2014/?p=159
Of course. But 74%. That is a heck of a lot of “jiggery pokey”.
But it doesn’t matter what the % difference between any 2 groups is. The analysis is the same.
The link you gave only shows that men with graduate degrees make more than women with graduate degrees in the same industry. Ok. But that doesn’t tell us that the difference is due to them being women. Other variables need to be examined, such as:
- Type of graduate degree (since they group together graduate and professional degrees…there’s big differences between a MS and a PHD or a JD)
- Level of graduate degree
- Job title held by the person with the graduate degree
- Plus all the other stuff from the previous example
So it may be that men get more PhDs in Computer Science, and women get PhDs in Math. Or more of those women with grad or professional degrees are JD holders who are lawyers in those firms, instead of computer science PhDs.
You’d actually expect the differences there to be much larger…because a PhD in computer science might earn $250k starting salary at a Silicon Valley firm, but a JD Lawyer or an MS in Math holder might only make $100k starting salary. Are there a lot more women with MS in math working there, than PhDs in computer science? Almost certainly.
The “study” there doesn’t control for anything.
The criterion ‘Graduate Degree’ is only one of the factors and tells you nothing about how much someone would be paid on a fair basis. In Silicon Valley should a woman with a graduate degree in English Lit makes as much money as a man with a graduate degree in Engineering? In Silicon Valley should a woman with a graduate degree and 10 years experience make as much money as a man with a graduate degree and 20 years experience?
That second question is important because people with more experience, and also people who had better positions years back will be earning more money now, and possibly due to much greater discrimination in the past. Even if that discrimination is entirely removed the effect will still be seen in percentages that do not factor in experience.
Ok, I want to focus on this part. I can’t possibly “argue” with you because you obviously know this stuff a lot better than I do. But my basic point remains. If men have “better” graduate degree’s, that indicates to me men have preferential treatment in being accepted to graduate programs. Because, the other interpretation would be that, men don’t get preference, they are just smarter/more capable at match/science/computers than women are. I’m quite sure you don’t mean to say men are smarter. (Honestly)
ADDED with edit:
Ok, all good points. Very good points. But to what degree is their still an “old boy network” in silicon valley and IT jobs? Are we to say it no longer exists?
I don’t know to what degree and I’m sure it still exists. So what can be done about it? I don’t really know. I do know that many companies are currently using very fair pay standards now and we have to look at the statistics for the youngest employees and make comparisons in context to see if the past practice of discrimination is still occurring. It is there that at least the possibility of correcting the problem exists.
I’ll just be frank. The only places that seem to argue that the wage gap is a myth are anti-feminist websites. It’s really hard to find anyone who is neutral on the subject, but, generally speaking, feminists are more often right about women’s issues than anyone else is.
Of course raw numbers don’t tell the whole story, but the idea that the gap doesn’t exist isn’t even present in the one citation brought up by the new guy who apparently just signed up to discuss this topic.
The logic being used here, that since you can find some data that explains some of the wage gap, you know that the gap would be eliminated with more data–that’s just bad reasoning. You could just as easily find that additional data negates some of the explanations. Unknown data is just that, unknown.
And, no, looking at just the early years doesn’t prove a thing, because, as the article again says, the gender gap has always gotten wider with age. No one in the tech industry would ever claim that there is no discrimination towards women. Just because you try and address this by hiring more women doesn’t mean they don’t get discriminated against once they get there.
A gap that wide in the tech industry is hard to explain, as why would tech women be more affected by those same variables than people outside the tech industry? Unless you’re arguing lack of skill, but then that should be represented by lower grades and such.
Remember, even certain racists make scientific sounding arguments for their position, so we can’t just go by how it sounds right. Hopefully the board’s big hitters on this topic will come in. All I can do is point out flaws in logic and lack of citations.
Ok, I have enjoyed chatting with you about this. My mind is not made up to either side of the debate. I’m still stuck on “74%”. That doesn’t seem like a “marginal” difference or “fuzzy” math. At 14%, sure. But 74%??? I don’t know if you feel like responding again but surely you can see the point I get stuck on…
Does being anti-feminist make people doubt the wage gap, or does doubting the wage gap make people anti-feminist? Because finding out that somebody is cooking the books to justify discriminatory policies against you is a pretty good way to get soured to their position.
Doesn’t Silicon Valley have a lot of tech startups and the like, where the extremes on both sides will be skewed by the chances of winning big or losing big? Do female graduates take the same risks that sometimes lead to the Bill Gates of the world?
I’d like to point out too, that equal pay for the same job does not actually preclude women being subject to gender-based pay inequalities in the workplace. Because there is the issue that youhave to get hired in the first place
If women are not getting access to the higher-paying jobs due to hiring discrimination, then “women are paid X% less than men and this is a problem” is still a valid statment, even if when you analyse on a per-job basis you don’t find discrimination.
It strikes me as “wrongheaded” to compare the figures after only one year.
I don’t know of any company that explicitly pays women less than men - so both will be on the same salary for an entry level job.
So you’d need to look at other factors - such as experience, job senority, title, and see if these are skewed or unfairly biased towards one group or another to explain the difference.
Also to see if there are cultural aspects that are affecting the difference. For example, I’ve heard it said that men are more willing to ask for a pay rise than women - assuming that to be true, is it something that is caused by discrimination? Cultural factors? Can it be addressed and should it be addressed?
Also time out for childcare leading to less experience - how do you address that?
Working hours? Are men more willing to burn the midnight oil? Do men get ahead more because they “network” better (sports and after work drinks?). Is that discrimination or something else?
The former is far more likely simply because those with an agenda to push will do everything possible to cast doubt on opposing evidence (as this board frequently demonstrates). The latter, well…there’s a difference between “being soured to their position” and “becoming an anti-feminist evangelist”. I see a lot of questionable data but I don’t start up blogs specifically to rail against it.
If you want to get into the success rates of women vs men in obtaining venture capital (an entirely different topic), you’re going to find not only a lot of discrimination but a helluva lot of sexual harassmentas well.