U.S. pay gap by sex by occupation(statwonk.com)
statwonk.com
U.S. pay gap by sex by occupation
http://www.statwonk.com/blog/pay-gap-us-full-time-workers-by-sex/
15 comments
Personally, I've found that any time someone declares that a given visualization "speaks for itself" what they mean is that they want you to not ask questions about it. Occasionally this is justified, but more often it's a stunt of some sort.
PRs welcome! The source code is here: https://github.com/statwonk/paygap
I appreciate the gesture. Unfortunately, statistics is not my strong suit and R is not a language I am familiar with.
That said, did you consider the social and media context into which your work is being injected before you did so?
That said, did you consider the social and media context into which your work is being injected before you did so?
"Here's some misinformation for everyone! Fix it for me or keep your comments to yourself."
I am noticing that the pulled list of occupations and the generated output differed in size. Why is that?
For example I would like to see the data for "Automotive Body and Related Repairers".
For example I would like to see the data for "Automotive Body and Related Repairers".
The difference are non-published values. Really wish we had raw surveys, but I do understand the ethical challenges BLS deals with.
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I have a feeling this graph is going to be reposted across various social medias with less context and incite more people spreading misinformation.
Absolutely agreed. It's irresponsible to present incredibly nuanced data at such a shallow face value without making any attempt to show the full story, especially on such an incendiary and divisive topic. How is this helping clear up disinformation and progress gender wage gap dialogue?
That most occupations pay women less than men is a fact, the graph is just a reformulation of this table: http://www.bls.gov/cps/cpsaat39.htm
Facts do not absolve a data visualization from being potentially misleading.
I'm sorry you feel that way. I sincerely find it very informative. Before I got first glimpse of it, I thought there would be at least 10-15 professions where women edged out men.
This isn't just a feeling. The existence of phenomenon such as Simpson's Paradox mean that this is something that any data analysis must be very careful about. Presentations of aggregate data are particularly vulnerable.
The graph title really should include more details than just "pay". Based on the site linked in the github page's readme, it's graphing "Median weekly earnings of full-time wage and salary workers by detailed occupation and sex".
That kind of detail is important because these numbers are de-facto controversial (in that people argue angrily over them a lot).
That kind of detail is important because these numbers are de-facto controversial (in that people argue angrily over them a lot).
I agree. PRs welcome!
Misleading title. It does not say whether or not the salaries were normalized based on the type of job inside each occupation (hours, position, etc.). Almost surely they have not been.
So instead of indicating a level of inequality in pay for doing the same job, the data might indicate a level of sexism in the type of jobs people have (or number of hours worked, or number of years people are in the profession, etc). That still demonstrates there's a significant problem.
There is no way to read that graph, or the data behind it, that indicates things should stay the way they are.
There is no way to read that graph, or the data behind it, that indicates things should stay the way they are.
As I understand azth's objection, it basically means "This data has been stripped of all context that could make it meaningful". Which is to say it's a shocking, but ultimately useless graph.
You can say there's no way to read it as indicating things should stay the way they are. I believe azth's point is that there's no way to read it as saying anything coherent at all.
(EDIT: Typo.)
You can say there's no way to read it as indicating things should stay the way they are. I believe azth's point is that there's no way to read it as saying anything coherent at all.
(EDIT: Typo.)
> That still demonstrates there's a significant problem.
Of course, but it's a different problem with a different solution. Isn't that important to know?
Of course, but it's a different problem with a different solution. Isn't that important to know?
There absolutely are ways to read the graph in a positive light.
If pay is heavily influenced by seniority, and a profession used to be sexist in its hiring practices but no longer is, then it follows that there'll be a significant gender pay gap until the older - mostly male - members of a profession die out.
Of course, there are many ways to read it negatively too. It's so devoid of information that it's just meaningless.
If pay is heavily influenced by seniority, and a profession used to be sexist in its hiring practices but no longer is, then it follows that there'll be a significant gender pay gap until the older - mostly male - members of a profession die out.
Of course, there are many ways to read it negatively too. It's so devoid of information that it's just meaningless.
How about women are more likely to change professions/jobs, so they don't get to the same levels of seniority as men. That might indicate they have a more varied and interesting life. Maybe that suits women better than men. So yea the graph says nothing.
> So instead of indicating a level of inequality in pay for doing the same job, the data might indicate a level of sexism in the type of jobs people have (or number of hours worked, or number of years people are in the profession, etc). That still demonstrates there's a significant problem.
The graph alone doesn't tell us a whole lot, other than women are almost always compensated less than men. There seems to be quite a bit of variation across job functions, which might be unexpected. Understanding why that variation exists might be useful in addressing the perceived problem, and avoiding corporate policies that accidentally make things worse.
For example, if the bulk of pay gap is years of experience, it would be foolhardy to increase starting salary for women; you'd be giving equally qualified men a competitive advantage in hiring they don't need. Similarly, the situation could be understated -- if I'm reading the methodology correctly, CPS data doesn't include independent contractors, since they buy health insurance separately, I expect a number of men forgo insurance entirely and pocket the difference, a gamble few women of child bearing age dare take. Corporate policy here could try to prohibit independent contractors, but that would substantially reverse the trend. Better, IMO, would be single payer health care, or at least an end to the tax subsidy we give employer paid health care.
More dimensions will give us a more nuanced view of reality, and a better grasp on the degree to which the gap is systemic vs personal.
The graph alone doesn't tell us a whole lot, other than women are almost always compensated less than men. There seems to be quite a bit of variation across job functions, which might be unexpected. Understanding why that variation exists might be useful in addressing the perceived problem, and avoiding corporate policies that accidentally make things worse.
For example, if the bulk of pay gap is years of experience, it would be foolhardy to increase starting salary for women; you'd be giving equally qualified men a competitive advantage in hiring they don't need. Similarly, the situation could be understated -- if I'm reading the methodology correctly, CPS data doesn't include independent contractors, since they buy health insurance separately, I expect a number of men forgo insurance entirely and pocket the difference, a gamble few women of child bearing age dare take. Corporate policy here could try to prohibit independent contractors, but that would substantially reverse the trend. Better, IMO, would be single payer health care, or at least an end to the tax subsidy we give employer paid health care.
More dimensions will give us a more nuanced view of reality, and a better grasp on the degree to which the gap is systemic vs personal.
Is it sexism, or is it women not wanting to promote due to external factors? Is it women not asking for raises as often as men? There is a lot of missing data here.
Exactly! A big part of the problem is that women aren't promoted as often and much of the work they're expected to do (admin tasks, coordination that falls outside the scope of their official title) isn't accounted for in estimates of their work hours. Thanks for pointing out this important reason that there's a gender-based pay gap in so many occupations.
I'm reasonably certain that that is not what azth was attempting to communicate. Is there a particular reason you are commenting in this manner?
I was under the impression that they were pointing out the mechanisms responsible for the evident pay gap. What do you think they were attempting to communicate?
I believe azth was attempting to communicate that as processed and presented, this visualization can serve only to mislead. That it does not offer an accurate - and thus useful - amount of insight because it fails to account for a number of factors known to be significant.
Sourced from here:
http://www.bls.gov/cps/cpsaat39.htm
I somewhat trust the Bureau of Labor Statistics.
http://www.bls.gov/cps/cpsaat39.htm
I somewhat trust the Bureau of Labor Statistics.
I mostly trust the BLS, but I don't necessarily trust every statistical conclusion someone can draw from running a script on BLS data.
Just as an example of how the numbers might not mean what they appear to: "lawyers" is near the middle of the chart, at around the 82% mark, while "legal occupations" is way at the bottom, around 57%. Does "legal occupations" include lawyers, or is it everything else in the law field aside from lawyers? If lawyers are included, then there's an obvious explanation for the large gap in legal occupations as a whole (namely, more male lawyers, and lawyers being higher-paid than assistants etc., dragging up the median compensation of males in the legal field); if they're not included, then there's a huge and unexplained gender discrepancy in pay among legal assistants etc.
These numbers have a very different meaning if they don't account for seniority, hours worked, or level of responsibility than if they do.
Just as an example of how the numbers might not mean what they appear to: "lawyers" is near the middle of the chart, at around the 82% mark, while "legal occupations" is way at the bottom, around 57%. Does "legal occupations" include lawyers, or is it everything else in the law field aside from lawyers? If lawyers are included, then there's an obvious explanation for the large gap in legal occupations as a whole (namely, more male lawyers, and lawyers being higher-paid than assistants etc., dragging up the median compensation of males in the legal field); if they're not included, then there's a huge and unexplained gender discrepancy in pay among legal assistants etc.
These numbers have a very different meaning if they don't account for seniority, hours worked, or level of responsibility than if they do.
> These numbers have a very different meaning if they don't account for seniority, hours worked, or level of responsibility than if they do.
I don't undestand your point. Those are exactly the mechanisms most likely responsible for the pay gap. No employer would ever pay double wage for an y chromosome, but it's not unlikely that preconceived gender roles influence decisions about who gets promoted, who stays home with the kids and stuff like that.
I don't undestand your point. Those are exactly the mechanisms most likely responsible for the pay gap. No employer would ever pay double wage for an y chromosome, but it's not unlikely that preconceived gender roles influence decisions about who gets promoted, who stays home with the kids and stuff like that.
By failing to account for obvious and known confounds, the graph is rendered significantly less meaningful.
By way of analogy, one could look at rainfall averages over the whole of the US and conclude that some place is/is not in a drought. You could do this by ignoring the obvious confound that different places get different amounts of rainfall. For some places, it would be true. For others, not.
By way of analogy, one could look at rainfall averages over the whole of the US and conclude that some place is/is not in a drought. You could do this by ignoring the obvious confound that different places get different amounts of rainfall. For some places, it would be true. For others, not.
That's the crux of the matter.
Most people unhappy about the 'pay gap' are indeed implying that employers are paying double (or 21% more) wage for a y chromosome.
If the wage gap rather has to do with decisions employees make themselves (such as who stays home with the kids and thus works fewer hours / has less experience / doesn't get promoted) - then it's not really the problem of employers to contend with.
Most people unhappy about the 'pay gap' are indeed implying that employers are paying double (or 21% more) wage for a y chromosome.
If the wage gap rather has to do with decisions employees make themselves (such as who stays home with the kids and thus works fewer hours / has less experience / doesn't get promoted) - then it's not really the problem of employers to contend with.
"...O'Neill finds that when these factors are accounted for, the gender wage gap falls to approximately 97 cents on the dollar..."
http://www.ncpa.org/sub/dpd/?Article_ID=22058
http://www.ncpa.org/sub/dpd/?Article_ID=22058
When you read the source text, you can see that they have been fairly selective in the criteria in which they dismiss size of the wage gap. I would argue that the text shows the study was produced with a political leaning.
http://www.ncpa.org/pub/ba766
"O'Neill finds that single women without children, on average, make 8 percent more than their similarly situated male colleagues"
http://www.ncpa.org/sub/dpd/?Article_ID=22058#sthash.6sSZrCm...
http://www.ncpa.org/sub/dpd/?Article_ID=22058#sthash.6sSZrCm...
You can see how that is a narrow selection though? Men and women don't remain 'similarly situated' throughout their entire careers, particularly when you factor in child-rearing (paternity still being highly uncommon, and few countries offer it as a social benefit).
In in simplest form that is like saying "the pay divide between women and men is non-existent when women are effectively men."
In in simplest form that is like saying "the pay divide between women and men is non-existent when women are effectively men."
The data sourced here are full-time only workers, not part-time.
Would love to take a look at the souce code of that analysis, but I can't find it. Happen to know where I can get it?
Would love to take a look at the souce code of that analysis, but I can't find it. Happen to know where I can get it?
Wow if this were true even normalized for years of experience, education, hours worked, specialty, etc... (which it is not) seems the market would make it incredibly difficult for men to find a job https://www.youtube.com/watch?v=BDj_bN0L8XM
This may be very simplistic, and this cave-man doesn't have much knowledge in this arena, but part of me believes that discrimination can only exist in an anti-competitive environment. In competitive markets, the company with misogynist hiring mangers will end up with a less productive (can only pay so much per hour) and/or overpaid male-dominated staff. Competitors who don't discriminate will drive them out of business.
So either misogyny is so widespread that market participants agree to engage in it (collude), or there's some other explanation: risk of maternity leave, etc.. Anything else? Have there been any studies that show how well women do salary-wise once they're beyond child bearing years? Any studies on married vs. non-married men perhaps to see if married men negotiate more in order to support wives while on maternity leave/stay-at-home?
So either misogyny is so widespread that market participants agree to engage in it (collude), or there's some other explanation: risk of maternity leave, etc.. Anything else? Have there been any studies that show how well women do salary-wise once they're beyond child bearing years? Any studies on married vs. non-married men perhaps to see if married men negotiate more in order to support wives while on maternity leave/stay-at-home?
You have it exactly backwards. In a competitive market, hiring managers have every incentive to negotiate workers to take lower salaries. As it turns out, for various reasons, when forced to negotiate for salary women end up taking less than men. (More info here -- http://www.npr.org/sections/money/2014/04/08/300290240/why-w... -- and plenty more a Google away.)
So the theory is that women are concerned about their reputations, so they ask for less than their male counterparts. But with the people that a female candidate would be working with, only the hiring manager would (should) know. I think this has more to do with the rather recent changes of women in the workplace than women managing their reputation, but what do I know?
> You have it exactly backwards. In a competitive market, hiring managers have every incentive to negotiate workers to take lower salaries
I never stated anything to the contrary. You're talking about profit-maximizing behavior that we all engage in everyday. What I said had to do with deliberate discrimination, which can only be profitable if the market participants all agree to it.
> You have it exactly backwards. In a competitive market, hiring managers have every incentive to negotiate workers to take lower salaries
I never stated anything to the contrary. You're talking about profit-maximizing behavior that we all engage in everyday. What I said had to do with deliberate discrimination, which can only be profitable if the market participants all agree to it.
Visualizations like these certainly have their place, and I actually appreciate that the OP didn't offer commentary in this case. This graph acts as a blank canvas onto which people project their conversational biases. Each person has their own idea of what the pay gap is.
For me, the pay gap encompasses all sociological factors that lead to women making less than men. When the numbers are squeezed to only compare men and women by exact position, the question "why aren't women holding high power positions?" is implicitly answered with "because women are incapable," and that's a gross untruth. (This is not to say that such research has no value — it is quite important in the context of coming up with solutions.)
If you're quick to wave around the 97% number, you may not be treating this problem with the humility that it deserves.
For me, the pay gap encompasses all sociological factors that lead to women making less than men. When the numbers are squeezed to only compare men and women by exact position, the question "why aren't women holding high power positions?" is implicitly answered with "because women are incapable," and that's a gross untruth. (This is not to say that such research has no value — it is quite important in the context of coming up with solutions.)
If you're quick to wave around the 97% number, you may not be treating this problem with the humility that it deserves.
Sadly, it's known that women do get paid less in one way or the other (based on bls data and other sources that confirms the same). But what's missing is more research & data as to why this is the case. Such data would make a more interesting graph because it's more actionable.
A more actionable graph making its round on the internet is more helpful than a graph that can fuel and provoke.
A more actionable graph making its round on the internet is more helpful than a graph that can fuel and provoke.
does this control for years of experience?
Nope. They're median weekly wages. You can find the source code at github.com/statwonk/paygap PRs with other analyses or improvements welcome!
When talking to women helping them with equal pay I suggest reading "Negotiating Your Salary: How To Make $1000 a Minute" by Jack Chapman.
When they found a salaray they are confident with, they should up it by 10% percent (say $66k instead of $60k).
One of many reasons women earn less from my experience is that they are risk averse during interviews which accumulates over the years.
When they found a salaray they are confident with, they should up it by 10% percent (say $66k instead of $60k).
One of many reasons women earn less from my experience is that they are risk averse during interviews which accumulates over the years.
> risk averse during interviews which accumulates over the years
Careful now, that may be a commonly held belief but is also wrong. There are far more reasons why the pay gap exists and you can't simply clump it all together and blame it on the stereotypical view that women have an innate inability to negotiate as well as men.
Careful now, that may be a commonly held belief but is also wrong. There are far more reasons why the pay gap exists and you can't simply clump it all together and blame it on the stereotypical view that women have an innate inability to negotiate as well as men.
Thanks, I should put in another "from my experience of 20 years of IT recruiting and mentoring women" to make it clear I'm not generalizing and what I'm talking about.
As a sidenote your comment about the ability of women to negotiate was not what I've said. There is a distinction between risk aversity and negotiation ability.
[Edit: Science is murky here, some studies claim to have found evidence, others claim that women are better negotiators. One I found interesting, can't find it, said women are better negotiators but do not start negotiating when it is not clear that they can, but man do negotiate salaries there too.]
As a sidenote your comment about the ability of women to negotiate was not what I've said. There is a distinction between risk aversity and negotiation ability.
[Edit: Science is murky here, some studies claim to have found evidence, others claim that women are better negotiators. One I found interesting, can't find it, said women are better negotiators but do not start negotiating when it is not clear that they can, but man do negotiate salaries there too.]
Average I guess? I would be way more interested to see boxplots for men/women for each category discussed. Averages can be tricky to interpret, plus you need to answer you are comparing folks at the same level of experience and all.
They're medians specifically. The graph is a visual representation of this data: http://www.bls.gov/cps/cpsaat39.htm The raw data isn't made publicly available, so boxplots aren't possible, but that'd be really cool!
Some people believe that the secret to closing the gap is to ban salary negotiations: https://www.washingtonpost.com/posteverything/wp/2015/05/21/...
I don't see how that really helps. That just pushes it to being willing/unwilling to walk or having other offers in hand.
Which is to say it removes overt bargaining in favor of making it all covert. Is that really an improvement? I have some doubts.
Which is to say it removes overt bargaining in favor of making it all covert. Is that really an improvement? I have some doubts.
Does this ``gap" reduce as the employees considered get younger?---the data source doesn't include age demographics.
More skilled jobs seem to have more disparity which is extremely surprising.
Possibly a reflection of longer maternity leaves and work force re-entry?
I was really surprised by the gap for physicians and surgeons.
I read an article a couple years back that pointed out a sudden increase in the gender pay gap among medical professionals -- specifically, fresh graduates from medical school, going in to the same specialties. Men and women had basically been at parity within each specialty in the early 2000s, and then over the course of the last decade or so, a massive gap appeared.
I read a followup paper shortly after, where they had investigated the details and found that a significant percentage of recently-graduated women had asked for reduced hours and fewer overnight shifts in exchange for lower pay, while many men had volunteered for those sorts of conditions in exchange for higher pay. The gap had actually appeared in response to trends in the lifestyle decisions of employees, rather than discrimination on the part of employers.
I read a followup paper shortly after, where they had investigated the details and found that a significant percentage of recently-graduated women had asked for reduced hours and fewer overnight shifts in exchange for lower pay, while many men had volunteered for those sorts of conditions in exchange for higher pay. The gap had actually appeared in response to trends in the lifestyle decisions of employees, rather than discrimination on the part of employers.
That could easily reflect different specialties within medicine compensated differently. As I understand it, pediatrics is dominated by women and surgery by men, and they don't pay equally for a variety of reasons. So a chart like this strips away that sort of context and shows you a shocking number.
That's never the case with data visualization. Explanation helps remove ambiguity, and the lack of explanation behind the data source is why there is an excessive amount of criticism in the HN comments.
Regardless, the graph does not certainly speak for itself. There's no obvious correlation between which professions have a better gender pay split than others. If you're trying to make the point that most professions pay women less than men, then you need to justify that. (And provide evidence that the chart represents "most professions.")