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Newsflash: PayScale Releases Big Data on Gender Pay Gap

Seattle, Gender Equality OverallMartha BurwellComment

From Jennifer Lawrence and Bradley Cooper, “Awkard Black Girl” to NBA Cheerleaders, people have been talking about the gender pay gap

Now, we’ve got some new numbers to arm ourselves with when your coworker says women get paid less because of their individual choices.   

Seattle-based PayScale.com just released a study on the gender pay gap, in which they drew from their large database of salary information to compile data from 1.4 million full-time employees in the U.S. 

The report used a proprietary algorithm to compare wages between women and men based on industry, marital status, whether they were parents, and other variables. This information was taken from survey results that full-time workers submitted over the last 2 years. 

Though much of the data confirmed what we already know, there were some interesting, if disheartening new statistics. 

"Lucie & ses parents-4" by Thomas Sauzedde is is licensed under CC BY 2.0.

For example, it’s known that being married and having children unfairly penalizes women in the workforce.  But did you also know that a family actually gives a career boost to men? The PayScale data shows that married men with children were the highest wage earners in the country ($67,900 for married men with children, $60,800 for those without children), while single mothers earn the lowest wages in the country.  Those that need the pay the most earn the least.

 

Yet strangely, the data also showed that men prioritize home and family responsibilities more often than women.  How could this be? We know that women still spend more working hours each year taking care of children and family obligations.  But remember, the PayScale data was based on survey responses.  The answer becomes clear in another piece of information: “The more often a woman tells us that she prioritizes home/family over work, the larger the controlled gender pay gap becomes, even when compared to men with similar characteristics who say they prioritize home/family over work with the same frequency.” 

Ah.  There it is.  Women cannot even say that they would prioritize their family if they had to, because they are penalized for it. 

Unsurprisingly, some of the industries with the highest gender pay gap were male dominated ones such as mining, oil and gas extraction, and forestry.  Yet even within female-dominated industries such as health care and social assistance (79% women), there still exists a large pay gap. This reflects how we devalue women’s work overall as a society, regardless of the industry.  Currently, the PayScale data showed a 24.3% “uncontrolled” pay gap, and a 1.7% “controlled” pay gap for healthcare.

1.7 percent! That doesn’t seem so bad, does it?  Let’s take a look at what that actually means.   PayScale offered two data sets for each item they examined.  One was “uncontrolled” in which they simply looked at all full-time wages, regardless of job level, experience, etc.  The other was “controlled” in which they only compared wages that had the same job level and experience.  It’s tempting to want to celebrate the smaller wage gap for the controlled data.  However, it does not communicate one very critical point: much of the wage gap exists because women are blocked from advancing into higher positions.  It also misses out on the fact that jobs of equal skill and education level are valued less if they are jobs traditionally held by women.  So the uncontrolled data shows what women’s wages are in a more complete sense.

Another finding new to me was the age at which worker’s pay plateaus.  From our first jobs, our wages continue to increase until we reach a certain age, when they flatten out or even drop.  According to PayScale, men can expect their wages to keep increasing until they are 50-55, while women, shockingly, can only expect their pay to rise until they are 35-40.  What does this say about how we value women as they age, compared to men? 

Finally, I wonder if the data includes the most marginalized industries, which are often female-dominated, and/or have a majority of people of color, such as housekeeping and home care.  Does the data include those pieces of the population?  Who don't have access to the PayScale survey, don't speak English, or don't use a computer?

However, the big data PayScale compiled is still telling. So what do we do with it?  How can we use it to make the pay gap smaller? 

It should be seen as a wake-up call.  We tend to think that we are somehow ‘past’ the gender pay gap.  That it’s a choice.  That women should just work harder or be more confident.  But this data shows that it’s much, much more than a personal journey.  It’s an enormous, ingrained bias that we all hold (women too!).  But even more so, it's our systems and the way our businesses and industries are defined. This data helps us understand the pay gap in our own industries.  So how about instead of changing the women, we upgrade the workplace?  Other developed countries are doing this with practical things like paid family leave (not just maternal leave), more time off, better benefits, and affordable childcare.  We could utilize 'unconscious bias training' and hiring techniques to diversify leadership roles. The U.S. is still lagging behind.  But if our labor laws aren’t changing fast enough, individual businesses can step up and implement change themselves.  Because it’s not just the right thing to do.  It’s also good for business

To view PayScale’s report, visit http://www.payscale.com/data-packages/gender-pay-gap


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