Roughly speaking, the average woman in the U.S. earns 80% as much per year as the average man. (I'm not sure if that's over all people or just those employed)

I was raised in a time where people would bring up statistics like this to assert gender based discrimination in the work place leading to women earning 80% of what a man of equal ability would earn.

But that's not what the pay gap is. As I best understand things:

  • roughly half of that discrepancy is directly attributable to hours worked
  • roughly half of what remains is due to career choice
  • roughly half of what still remains is probably due to personality type

and what little remains has not been statistically shown to be due to gender-based discrimination.

But... people keep talking about the 80% figure as something we should care about. Even after acknowledging the explanations for the gap.

If it's not about gender-based discrimination in the workplace, then what is it about? What phenomenon are people trying to highlight by citing the gap? What changes are people hoping to bring about?

(Edit) To better clarify my question, this is not intended to be a "The wage gap is a myth: prove me wrong!" type posting.

Even if I suppose for the sake of argument the majority of the wage gap was conclusively attributed to the sort of gender discrimination I mention above, it's still the entire yearly earnings gap I regularly see brought up as the thing to talk about. And my question is to understand the point of making that statistic being made the topic of discussion.

  • 12
    Politics is driven more by the perception of problems than by "objective reality", were that attainable. Equality means a lot of things to a lot of people, but clearly, women have been at a historical income disadvantage, no matter the underpinnings. I believe the __% figures tokenize women's continued systemic economic disadvantages, the pink tax, lower board memberships, lower rates of governmental representation, etc.
    – dandavis
    Commented Apr 2, 2019 at 18:52
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    It's way more complicated than that, and it's not hard to show it's discrimination if you're willing to spend a few hours going through histories and data. The 80% is an easy number to see and discuss, so it's a simpler rallying point than "women's labor is systematically undervalued and their life choices are under supported compared to men's life choices which lead to systemic issues affecting women's total lifetime wages".
    – David Rice
    Commented Apr 2, 2019 at 18:58
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    Can you tell us what is your source of knowledge for all those bullet-ed facts? Commented Apr 2, 2019 at 21:33
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    "I'm aggregating many things I've read." Set aside for the moment that you haven't provided sources: you are linking these statistics together with "half of what remains". I don't see how you can do that from independent statistics. It's not valid to average averages, for example. Without actual source statistics, this question can't be discussed meaningfully.
    – JimmyJames
    Commented Apr 3, 2019 at 16:29
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    "As I best understand things" - your understanding would be incorrect. The claim is that the gap exists even when you control for those other factors listed. The claim is that it exists for equal hours, equal positions, equal experience/history, etc. Commented Apr 3, 2019 at 17:04

6 Answers 6


What this question seems to ask is why the unadjusted gender pay gap is often cited (which just compares the national average incomes of men and women) when we also have an adjusted gender pay gap statistic which apparently is "more correct"?

The answer is that both numbers are important, but they are important to point out different kinds of gender discrimination in our society.

The smaller, adjusted gender pay gap tells us if people who have the same profession and the same qualifications receive the same amount of money per hour for their work. This can be a strong indicator for gender discrimination in the workplace. The adjusted gender pay gap varies a lot between professions and between organizations. It is not a problem of the society as a whole, it is a problem for each organization which needs to be solved on the organizational level (or maybe organizations which employ more men have a competitive advantage which results in higher wages? might also be worth examining, but I digress...).

Politics can prevent some (but not all) instances of this by making laws and regulation to outlaw various forms of workplace discrimination and by setting good examples in their own employment policy and choice of leaders.

The larger, unadjusted gender pay gap, on the other hand, which can not be attributed to biases or sexism of individual decision makers in private companies, instead raises a number of sociological questions:

  • Why do "women's professions" get paid less than "men's professions"? Are they really less important work?
  • Why do women choose these lesser paid professions? Is it really a matter of personality or is it the result of social norms? If it's personality, is it possible that these personality traits are a result of nurture instead of nature? Why do men study STEM subjects (which almost guarantee a highly paid career) while women study education and humanities? Is it really a question of aptitude and interest or is it the result of gender roles? And does the reputation of the work environments in certain industries have an effect on the career choices of women?
  • Why does having children have a larger impact on the career of a woman than on the career of a man? And is it a fair gender stereotype that women are expected to take care of the children while men are expected to work? Do people actually want this role distribution or is it the result of social pressure?

These are all questions which do not have one right answer which can be easily proven with data. And that makes them very hard to discuss in a rational manner. However, assuming that we agree with the premise that these are relevant problems and that the norms of our society are to blame, then those problems can not be solved in the workplace. They need to be solved by changing social norms in general. And politics can not change society overnight with laws and regulation. Politics can try to set the agenda and create the necessary conditions for social equity to exist, but changing society itself is a long and hard process which needs to come from within.

So depending on whether you want to discuss workplace gender discrimination or structural gender discrimination, you have to use either the adjusted or the unadjusted gender pay gap to prove that the problem you want to discuss actually exists.

  • 14
    Excellent answer. Bullet 3 is one that I think we really don't deal with well in the US. For example, there are more states that require paid maternity leave than require paternity leave. Naively this is considered pro-woman but what it does in economic terms is make women of child-bearing age more risky to employ than men as well as taking away the choice of which parent will care for the child and take time off of work.
    – JimmyJames
    Commented Apr 3, 2019 at 16:48
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    I up voted this, but I think that while all you say is true, it's not actually the real answer. Call me a pessimist but I think the real reason many people quote the unadjusted pay difference when making arguments is because it is larger, making their argument of discrimination seem more blatant, and/or they don't understand statistics well enough to realize that the number should be adjusted. In short, ignorance and it makes a better sound bite is the main reason, not a nuanced understanding of the difference each implies.
    – dsollen
    Commented Apr 4, 2019 at 17:04
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    @dsollen I think what this answer gets at is that there's no easy way to say how the data should be adjusted and any attempt to do so requires making decisions about what is and is not influenced by gender discrimination (both acute and structural). So (perhaps being more optimistic) I think it's less of ignorance of the proper statistical adjustments, as it is real and legitimate disagreements about what factors should be adjusted for
    – divibisan
    Commented Apr 5, 2019 at 3:01
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    @JonathanReez The question which is being raised in that regard is how that inherent biological career disadvantage can be compensated. One political solution which already got realized in several countries is to encourage men to take parental leave of an equal timespan. And then there is the expectation in the workplace that women with children prioritize their children while men prioritize their career, leading to a preconception that fathers are more dedicated employees than mothers. Government-sponsored daycare facilities are one political measure to compensate this problem.
    – Philipp
    Commented Apr 5, 2019 at 12:04
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    @JonathanReez pregnancy no longer requires one limit their job career. Most jobs now of days a women can work just as well while pregnant. Similarly a child can be bottle fed, either formula or pumped breast milk, so that a women can still continue working. Other then a short absence for the actual birth and physical recovery from the birth a women could go right back into work and leave her husband (or wife, or any other caregiver) to care for the child. Many don't choose to do this, rather this is cultural influence, biological, or some combination of both is a common debate
    – dsollen
    Commented Apr 5, 2019 at 13:29

You have a very simple view of the gender wage gap. If it were correct, there'd indeed be nothing to worry about. But if you look at Wikipedia's article on the gender wage gap in the US, you get statements such as these (with sources to back them up):

A 2010 study by Catalyst, a nonprofit that works to expand opportunities for women in business, of male and female MBA graduates found that after controlling for career aspirations, parental status, years of experience, industry, and other variables, male graduates are more likely to be assigned jobs of higher rank and responsibility and earn, on average, $4,600 more than women in their first post-MBA jobs.

If you consider Catalyst biased there is also:

Using data from longitudinal studies conducted by the U.S. Department of Education, researchers Judy Goldberg Dey and Catherine Hill analyzed some 9,000 college graduates from 1992–93 and more than 10,000 from 1999–2000. The researchers controlled for a multitude of variables, including: occupation, industry, hours worked per week, workplace flexibility, ability to telecommute, whether employee worked multiple jobs, months at employer, marital status, whether employee had children, and whether employee volunteered in the past year. The study found that wage inequities start early and worsen over time. "The portion of the pay gap that remains unexplained after all other factors are taken into account is 5 percent one year after graduation and 12 percent 10 years after graduation. These unexplained gaps are evidence of discrimination, which remains a serious problem for women in the work force."

I quote only two, but you can hopefully see how simplistic your view is. These studies control for both concrete factors you mention (personality is hard to measure) and a whole lot more, and they still see a wage gap.

Once you appreciate how many studies have been done, how many variables have been controlled for, and how there remains an unexplained gap, you can see why people continue to think about it.

Edit: this answers your edit. We think about the 20% number because it is unambiguous. The methods used to measure it are (relatively) uncontroversial and indisputable. Other numbers don't have these qualities. For example, in the two examples above, you could argue that Catalyst has controlled for career aspirations while Judy Goldberg Dey and Catherine Hill have not, and therefore their results are unreliable. Or perhaps you could say that Catalyst's method for measuring career aspirations are less than ideal. For example, maybe Catalyst divided their subjects into "high career aspirations", "medium career aspirations", and "low career aspirations", and you think three categories are insufficient.

In other words, it's conceivable that a reasonable person thinking about the gender wage gap will not agree about other statistics, but everyone will agree that the 20% figure is true and accurate. In that case, it makes sense to quote that figure in the public discourse.

  • 11
    I don't disagree with the data here, but is it true that the large portion of the wage gap due to occupational segregation (what they called career choice) is nothing to worry about? If societal gender roles push men and women toward different jobs, is that a good thing? And some portion of that disparity is due to the fact that women are less likely to be hired for higher-paying jobs.
    – Obie 2.0
    Commented Apr 2, 2019 at 20:59
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    There's also the fact that the nations which afford women the greatest number of career choices have the greatest disparity in career choices.
    – EvilSnack
    Commented Apr 3, 2019 at 3:29
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    @Hurkyl There's a simple explanation for that: politics. A concrete number like "20%", which is justifiable, makes for an easier emotional attachment, and a bigger public concern, than smaller numbers or less concrete things like "even controlling for many variables we still see a difference, suggesting systemic inequalities". To mathematically minded people that last one is a big draw, but for most people it's just a bunch of nonsense and they might think you're just looking down on them rather than trying to explain something to them. Commented Apr 3, 2019 at 9:31
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    I think this answer misses the question. The question is not asking for confirmation that the adjusted gender pay gap is real. It is asking why people still quote the unadjusted gender pay gap when there is also an adjusted gender pay gap which is apparently "more true".
    – Philipp
    Commented Apr 3, 2019 at 10:50
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    @AHamilton I think they're upvoting it because this was the answer that led the OP to edit the question.
    – Allure
    Commented Apr 3, 2019 at 10:57

While we wait on your data source, there is this additional point to make regardless:

the adjusted gender wage gap really only narrows the analysis to the potential role of gender discrimination along one dimension: to differential pay for equivalent work. But this simple adjustment misses all of the potential differences in opportunities for men and women that affect and constrain the choices they make before they ever bargain with an employer over a wage. [...]

Put another way, we cannot look at our adjusted model and say that discrimination explains at most 13.5 percent of the gender wage gap. Why? Because, for example, by controlling for occupation, this adjusted wage gap no longer includes the discrimination that can influence a woman’s occupational choice.

  • 1
    This is sort of exactly what my question is about. When I see someone talk about "pay gap", I'm expecting specifically someone talking about things like potential gender discrimination causing differential pay for equivalent work. So if a person invokes the pay gap intending to invoke something completely different, that intent is completely lost in the communication. The point of my question is to learn what, if any, those completely different issues are.
    – user8229
    Commented Apr 3, 2019 at 5:57
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    That's a great point. By choosing to control for a variable, we're making a judgement that that variable is independent of the variable we're testing for. Especially in messy fields like social science and economics, this is not always a valid assumption and this decision leaves a lot of room for researchers' biases to influence the results
    – divibisan
    Commented Apr 3, 2019 at 17:26
  • @divibisan I don't think that's the point at all. Controlling for a variable is specifically done because you know or suspect they're not independent, but, you have deemed that dependence to be unimportant (for your scientific inquiry) and so do not want to see it in the data. That's why you control for it. The quote argues certain variable controls equate to declaring that discrimination itself isn't relevant and so is not worth seeing in the data. And this rather defeats the entire point of the "gender pay gap" investigation. Commented Apr 6, 2019 at 6:45
  • 2
    @zibadawatimmy Thanks for pointing that out – I was sloppy in my terminology. Unless I'm misunderstanding, though, I think the point remains: as you say, you control for a variable because "you have deemed that dependence to be unimportant for your scientific inquiry". If you decide to control for occupational choice, then, you're making a decision that it is unimportant to the question of gender discrimination. But if that decision is not justified, ie. if occupational choice is influenced by discrimination, then by controlling for it you improperly remove part of your true effect
    – divibisan
    Commented Apr 6, 2019 at 20:37

It's an extremely complex issue and causality is a big problem here.

Suppose, as an example, you do some statistics - a regression involving gender, career choice and hours worked and the income gap. You find the values you give, half of the gap can be 'explained' by hours worked and a quarter by career choice, with little from gender. What does this tell you?

It tells you that, given information on someone's career choice and hours worked, you can improve your prediction of that person's income, and that adding gender to the information you have gives you little extra ability to predict it.

It does not tell you anything about causality. It does not tell you the difference in income caused by someone's gender. It's an unfortunate fact about statistics that in a non-interventional study you can't get causal information out without putting causal assumptions in.

Here's an example. You say in your question that about a quarter of the gap is 'due to' career choice and, implicitly, that this excludes the possibility of it being caused by gender. However, women may look ahead, see that women are discriminated against in certain careers and choose not to enter them.

Similarly, women may work fewer hours because each hour pays less (and a related issue is that their spouses' pay per hour is likely to be higher, which may be because of gender or may be because of age, or many other issues).

Given the complexity of the issue and the difficulties with causality, it's very unlikely that many of the people speaking about it have a good understanding (and I include myself here). Even if they did, the chances of getting it across whilst meeting their political goals is very small. Instead, it's more likely that their audience would say 'urgh, this is complicated, better avoid the issue'. If you're, say, campaigning for better childcare in the workplace, or an end to the US's highly unusual lack of statutory maternity leave, or whatever, you're going to use nice simple sounding numbers that people think they can understand.

  • 1
    The #1 reason the husband’s salary tends to be higher is because of the selection bias of married men. Women notoriously hate men who don’t earn enough and only want to marry men who earns more than themselves.
    – Blaszard
    Commented Apr 6, 2019 at 9:19
  • 1
    @Blaszard "Notoriously" = I have no evidence for it beyond ancedote. A decent study would be called for; while it certainly happens, there's a lot of counterexamples, and it's hard to tell whether that had any effect on the marriage of most people. One could also blame it on the men; men notoriously want trophy wives, to what statistical effect the same study could ferret out.
    – prosfilaes
    Commented Feb 11, 2022 at 15:00

Most answers so far dive too deeply into the question of gender equality, when the actual answer is very simple:

Publications will pick the number that serves their purpose and tells their story.

There are almost always different statistics with different numbers, plus your choice of quoting absolute or relative numbers, focus on the current number or the change from last year, etc. etc.

Most media and most people in the west today are for equality and thus reporting the larger number fits better into the story that there is still something that needs to be done. And that is the story that most of us believe in and want to read. Reporting a smaller number, especially when it is one well within the normal wage differences between people or companies, doesn't tell that story. And people who intentionally want to tell the other story (that the gender pay is really quite small or whatever) are in the minority, so the number they pick appears much less in the media.

This is not just the case for gender pay gap stories. There are many other examples where carefully picking your numbers can greatly enhance the impact of your headline.


As Mark Twain once noted, there are three types of lies: Lies, Damn Lies, and Statistics.

For example, it is well known that Russia is the most likely country to be struck by a meteorite.. and the rate was much higher under the Soviet Union. Clearly there is a God and he's American!

Of course, once you realize that Russia is the largest country by landmass in the world, and the Soviet Union was bigger because Russia was one of a handful of nations within the Soviet Union, it has nothing to do with Russia and everything to do with with being a large country. If a meteor is going to hit earth, the most likely impact zone is somewhere in the ocean because 75% of Earth is ocean. But if it's going to strike a country, it's most likely to hit Russia because Russia is bigger than any other country.

Another fun one, it is a well known fact that in the United States, ice cream sales and violent youth crime increase and decrease at identical rates during identical observation times. Natrually we must ban Ice Cream, which is corrupting our youth! THINK OF THE CHILDREN!

Of course, what's omitted is that an increase in ice cream sales and an increase in youth crime at similar rates would normally be observed in Late Spring to Summer, while the decrease would occur in late fall and winter... because Ice Cream is typically sold in summer months to beat the heat, which also is when school is out, which leads to kids having more free time to do things kids do... including Youth Crimes. Don't give up your 31 flavors for just that.

Another thing to look at, when citing sources related to nations, is to look at sample size, rather than total numbers. Take a look at the leader boards on this Wikipedia Page for Nations by Gun Homicide. First it's important to note that all figures are sampled at a a per capita rate of 100,000 citizens, so that each country can be comparable in rates of incidents EXCEPT for the total available guns per capita, which is for 100 people. I'll be putting that stat into 100,000 for convenience so that I can sub Per Capita for 100,000 population (also cause the page does not clearly show this.). It should also be noted that the total guns available assumes all weapons, legally owned or otherwise.

If we look at this page, we can see that the United States clearly leads the pack in gun ownership at a rate of 112,600 guns per capita and is the only nation with more guns than people on this chart! In total numbers, 12,999 individuals died in gun related homicide (The 14th highest world wide). The Gun Homicide Rate in the United States is 4.2 deaths per capita (The 88th highest world wide). So how can this be?

Well, we're measuring several different statics. First, gun ownership rates have little to do with gun homicide rates or total homicides. For example, by total numbers alone, the top three Leaders are Brazil (40,974), India (~40,752), and Mexico (~25,757) and have respected 8,000, 4,200, and 15,000 guns per capita. The gun homicide rates are also surprising as there is a respected, 21.0 per capita, 3.4 per capita, and 16.9 per capita. India, despite having nearly 4 times as many total gun homicides than the United States is lower in it's incident rate than The United States and Mexico, but all three of those pail in comparison to Brazil's rate, which isn't the highest rate in the world (Houndoras, at 91.6 has the highest rate).

Like the Russia trick, size matters. India is second largest nation in the world by population and one of only 2 nations with over a billion people. The United States is a distant Third, with about 320 million people. Brazil is sixth with 210 million people. Mexico is 11th with 123 million people. Per Capita statics are measured by dividing the total number by the total population and than multiplying by 100,000 (or what ever your per capita rate is. There's no rule that says it has to be 100,000, but these stats are usually given in per 100,000 members of population). Thus, 40,000 divided by 210 million is a much larger number than 40,000 divided by 1 billion people, while 25,000 into 123 million and all are larger than 13,000 into 320 million (Cause that's how fractions work). But these numbers are big because like Russia's "Mo' land, Mo' Metorites" problems, these nations operate under "Mo' People, Mo Problems". If you had to pick a country anywhere in the world that would likely to have a gun homicide, you'd go for the ones with larger populations because there is a greater chance to have someone who will kill another person in that country.

And because I got into a debate with some British people about how you need a Per Capita rate when comparing countries with various populations sizes, I can say with confidence that U.S. Medicare and Medicade cover more people than the UK's Universal Health Care plan. This is because the two programs cover 120 million people combined, which is double the entire population of the United Kingdom (~60 million). With Per Capita standardization, we're treating all stats without discrepancy of the population. Thus, the question of "Who's Health Care system is better?" doesn't rely on the United States being more than 5 times the population size of the U.K. but which is better to have? 287 million people out of a total 320 million covered OR 60 million out of 60 million people covered? If we are going by sheer bulk, than the United States wins in a landslide. If we're talking in percentage of population, than the U.K. is the winner.

I throw these numbers up not to pick a side, of any debate (except that, in summer, I scream for Ice Cream and I scream for solutions to kids graffiti my house, but that doesn't mean the later is caused by the consumption of the former). I merely selected them to show that anyone can take the numbers and torture them enough to say something that supports them.

With respect to the gender pay gap, the statistic (I think it's 78% of what a man makes, not 80% but that's a quibble at best), the figure was taken by finding the average salary of men and the average salary of women and divided tha latter by the former. Yes, that pay gap exists... but it does not indicate that a woman and a man doing the same identical job, for the same amount of time and same quality of work will see a difference in pay, which leads to debates about the gender pay gap. It is correct to say that in the United States, the average salary for woman is 80% of the Average salary for men. It is also correct to state that women in the work place have faced behaviors from men that are inappropriate. It is also correct that some of these inappropriate behaviors have been reduced pay for women. It is incorrect to say that this 20% difference in pay is solely attributed to malicious actions by men (it contributes but isn't the only factor). Just like it is correct to say that Ice Cream Sales and Youth Crime both experience peaks and troughs at the same periods of time, it is incorrect to say that more Ice Cream corrupts the kiddies or that youth offenders favor ice cream over any other snack... there could be some cross over. I'm sure Ice Cream does rate high if you want to know what Youth Offenders like to snack on and some youth offenders may try to steal ice cream from stores, but the connection between Ice Cream and Youth offenders are not co-dependent.

Another example is the (in)famous book Seduction of the Innocent which suggested that Comic Books were corrupting children and killed the Golden Age period of Comic Books and damn near the entire industry... during this time, Superheroes weren't the only genre... there was also horror, fantasy, tales of Soap Opera styled lives... but these were written for adults and teens, not children. The two most damning accusations in the book was that Batman and Robin promoted a homosexual lifestyle and Wonder Woman had sexual subtext promoting Lesbianism. In the Batman and Robin charge, this was uncovered by the author interviewing boys who were institutionalized for Homosexuality and learning that they liked to read Batman and Robin and identified with Robin. It failed to take into account that Robin was meant to be a character for the young male audience to identify with and damn near every superhero had a childhood sidekick during this time. If he were to ask Straight kids who their favorite Batman character was, they probably would answer with Robin too. In the case of Wonder Woman, its a case of "right for the wrong reason". Wonder Woman was contracted to a professor to write and tasked him to write a "Superman for Girls" character. Unknown at the time, the professor was a polygamist and into bondage... he also invented the polygraph. And now you know why Wonder Woman's signature weapon is a Lasso of Truth. It also explained why Wonder Woman's early comics involved tying up other women or herself being weakened when bound. Like in the case of Robin, gay girls enjoyed reading Wonder Woman because she was written as a superhero that young girls would enjoy reading about. Straight girls probably liked the stories just as much as gay girls.

And like all of these statisitics, when accounting for other factors, such as equal pay in the same job/job field (i.e. pay differences between men and women in computer programing or teaching) and hours worked, quality of work, and all other factors, there is still a gap favoring men, but that gap is reduced to 1-2% difference. $0.98 for ever $1 a male makes. In statistics, this is an insignificant difference that falls within margin of error and can be attributed to factors not controlled for, possibly misogyny in the system, or possibly over or under reporting or other data entries. There could be a relationship, there could not be. More study required. The reason the greater gap is touted though is to bring attention to an issue. It's a popular talking point and some people use it knowing that society disadvantages are not the root cause, but the assumption that is what is happening is the root cause and others use it because they got the stat from somewhere citing it.

Or as Homer Simpson, who's intelligence is legendary, once noted, "Anyone can make up a statistic. 40% of all people know that!"

  • 3
    ...I have no clue where you're coming up with your "1-2% difference" though. Blau and Kahn (2017)'s analysis on the subject is by far the most comprehensive, and they find an 8 to 9% gap that's unexplainable by any observable characteristics (other than gender).
    – AndrewC
    Commented Apr 3, 2019 at 17:12
  • 3
    Moreover, it's worth pointing out that even if the gap was only $.01 you can't possibly say it would be insignificant and falling within the MoE. The margin is driven largely by sample size, and given these studies often use the ACS, a one cent gap could still absolutely be significant.
    – AndrewC
    Commented Apr 3, 2019 at 17:15
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    @AndrewC: I'll have to look at that, but I've heard the difference as much lower, I just cannot recall where. But the fact that the only observable difference is gender does not mean that it is necessarily the cause of that difference. After all, they did say it was unexplained, so they're stumped as to what cause it in the first place and if it was intentionally malicious in nature?
    – hszmv
    Commented Apr 3, 2019 at 17:56
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    This doesn't seem to attempt to answer the question at all.
    – Geobits
    Commented Apr 4, 2019 at 12:14
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    @hszmv Why would you think that would even be a thing? Most racist people aren't racist because they're running around like cartoon villains insulting and attacking minorities. Most of them are simply raised in a world and system that subtly imparts, actively fails to prevent, or even rewards racism. Same with sexism. That's one reason why anyone who is pointed out for obviously racist/sexist/whatever acts almost immediately says "No I'm not!". Because few people are actively and willfully so. They are subtly sculpted as such and have little awareness of it. Commented Apr 6, 2019 at 7:02

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