White Canadians earn more, because they have white privilege.

White Canadians earn more than non-white Canadians, even when comparing only the whites and non-whites with the same education and of the same age. Comparing only the foreign-born white Canadians with the foreign-born non-white Canadians, white people earn more. Comparing only the second-generation, Canadian-born white Canadians with the second-generation, Canadian-born non-white Canadians, white people still earn more.

In other words, even when controlling for age, education, and generation, white Canadians earn more than non-white Canadians. Racial appearance causes the difference in earnings.

Wellesley Institute’s study, Canada’s Colour Coded Labour Market, was released in March 2011 and draws on data from the last mandatory long-form Census (which has been cancelled recently by the politically-conservative Harper government):

THE LAST AVAILABLE CENSUS DATA before the federal government cancelled the country’s mandatory long form Census reveals a troubling trend in Canada.

Despite years of unprecedented economic growth and an increasingly diverse population, this report confirms what so many Canadians have experienced in real life: a colour code is still at work in Canada’s labour market.

Racialized Canadians encounter a persistent colour code that blocks them from the best paying jobs our country has to offer.

[…]

Default explanations like “it takes a while for immigrants to integrate” don’t bear out. Even when you control for age and education, the data show first generation racialized Canadian men earn only 68.7% of what non-racialized first-generation Canadian men earn, indicating a colour code is firmly at play in the labour market. Here, the gender gap — at play throughout the spectrum — becomes disturbingly large: Racialized women immigrants earn only 48.7 cents for every dollar non-racialized male immigrants earn.

The colour code persists for second generation Canadians with similar education and age. The gap narrows, with racialized women making 56.5 cents per dollar non-racialized men earn; while racialized men earn 75.6 cents for every dollar non-racialized men in this cohort earn.

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Othering and Projection: Chinese is confusing vs. Chinese are confused

In English, a person says, “It’s all Greek to me,” when they do not understand the words of someone else. In Greek, when a person does not understand, they say it sounds like Chinese. Many languages have an expression that names another language as epitome of unintelligibility. It turns out that in a directed graph, most languages converge on Chinese as the unintelligible language.

Directed graph shows various languages as nodes with arrows pointing at other languages, eventually pointing to the 'Chinese' node. The 'Chinese' node points to 'Heavenly Script'.

This is understandable. Chinese writing, especially Traditional Chinese, is very visually complex. Chinese characters are logograms, which makes learning how to read Chinese difficult.

However, there is a difference between finding Chinese writing confusing and alleging that Chinese people are confused.

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This is an example of sexism in tech recruitment.

This is an example of unconscious sexism in tech recruitment that assumes that women are bad with math and computers.

A public transit ad shows a brain with two hemispheres. A box pointing to the left hemisphere asks, 'Can you solve one of our puzzles?' A box pointing to the right hemisphere asks, 'Can you explain it to your mom?' Text at the bottom says, 'We're hiring hackers with people skills. itasoftware.com/careers' There is a real yellow sticky note stuck on to the ad that says, 'My mom has a PhD in math.'

The yellow sticky note says, “My mom has a PhD in math”.

Close up of yellow sticky note that says, 'My mom has a PhD in math'

I am not a mother, but if I reproduced, I would be.

The job ad is also based on the same stereotype of female technical ineptitude as “So simple, your mother could do it”.

Original photo by Jessie Bennett (via Sociological Images and Geek Feminism Blog)

Discrimination against job applicants with non-white names continues.

Muslim ‘refused job because of his name’ accuses airline bosses of racism:

A Muslim airport worker has accused airline Cathay Pacific of racism after he was refused a job interview – only to be offered one when he applied two days later using a fake white British-sounding name.

Algerian-born Salim Zakhrouf applied to Cathay Pacific for a job as a passenger services officer at Heathrow Airport.

Mr Zakhrouf, 38, who has lived in Britain since 1991 and is a UK citizen, was told by email he had not been selected for interview.

But applying 48 hours later as ‘Ian Woodhouse’ with an identical CV and home address, he was invited for an interview by the same personnel officer who had first refused him.

via Resist racism, who points out, “For clarity:  My name is not the problem, as others have suggested.  Racism is the problem.”.


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Myths about Girls, Math, and Science

Top 5 Myths About Girls, Math and Science (LiveScience 2007):

Myth 1: From the time they start school, most girls are less interested in science than boys are.

Reality: In elementary school about as many girls as boys have positive attitudes toward science. A recent study of fourth graders showed that 66 percent of girls and 68 percent of boys reported liking science. But something else starts happening in elementary school. By second grade, when students (both boys and girls) are asked to draw a scientist, most portray a white male in a lab coat. Any woman scientist they draw looks severe and not very happy. The persistence of the stereotypes start to turn girls off, and by eighth grade, boys are twice as interested in STEM (science, technology, engineering, math) careers as girls are. The female attrition continues throughout high school, college and even the work force. Women with STEM higher education degrees are twice as likely to leave a scientific or engineering job as men with comparable STEM degrees.

[…]

Myth 3: Science and math teachers are no longer biased toward their male students.

Reality: In fact, biases are persistent, and teachers often interact more with boys than with girls in science and math. A teacher will often help a boy do an experiment by explaining how to do it, while when a girl asks for assistance the teacher will often simply do the experiment, leaving the girl to watch rather than do. Research shows that when teachers are deliberate about taking steps to involve the female students, everyone winds up benefiting. This may mean making sure everyone in the class is called on over the course of a particular lesson, or asking a question and waiting 10 seconds before calling on anyone. Good math and science teachers also recognize that when instruction is inquiry-based and hands-on, and students engage in problem solving as cooperative teams, both boys and girls are motivated to pursue STEM activities, education and careers.


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Can you spot the female geek?

''... developing new Drupal modules and building complex websites!'' There is a double-arrow pointing to a white man flexing his bicep and a white woman wearing a bikini and holding a whip. The double-arrow says, ''A PERFECT GAME FOR GEEKS TO CONNECT WITH NON-GEEKS''I have been a geek for most of my life. However, my geek identity is rarely recognized in meatspace interactions, probably because I am female. You would expect that people’s assumptions about the science, math, and tech abilities of girls and women would be challenged upon encountering female geeks in real life, but I have found that being a female geek actually reinforces sexist convictions that girls and women do not really belong in science, math, and tech.

I remember when I won some physics award in high school, a male rival complained bitterly in the library that the physics award he felt he should have won ended up going to “some girl”. He actually said that, emphasizing the word girl, as if my very gender invalidates my right to win a physics award. He complained loudly on purpose so that I would overhear the barb. I was shocked that people could say such blatantly sexist things in [current year], in which sexism was no longer supposed to exist, especially among my youthful generation. Instead of challenging gender stereotypes, my physics geekery apparently reinforced this guy’s perception that male rights are being eroded by uppity females who get awards we don’t really deserve. If he remembers me at all, he probably won’t remember me as the geeky girl in the library, but as some bitch from high school.

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Women did not evolve against risk-taking and tech startups.

This is cross-posted at Geek Feminism.

There is a common idea that women are underrepresented in tech startups because we are “nurturing and not risk-taking enough by nature”, an idea often proposed and upvoted in Hacker News discussions. Roy F. Baumeister, Professor of Psychology, also argues something similar in his defense of Lawrence Summers’ hypothesis that fewer women than men have high innate ability in science. Professor Baumeister argues that men evolved to take risks, and women evolved to play it safe, because we are allegedly descendants of risk-taking men and risk-averse women.

However, there are a few problems with this explanation of why women are underrepresented among tech entrepreneurs. One problem is that top venture capitalist John Doerr consciously and deliberately invests in tech startups run by white men over women and racial minorities, and even encourages other VCs to follow his lead. Even more, it is understood that this is “the way the venture-capital industry operates”. While other industries call this “stereotyping” or “profiling”, VCs call it “pattern recognition”. In other words, there is systemic discrimination in the tech industry based on gender, as well as race and age.

Another problem with the hypothesis of female risk-aversion is that outside of the tech industry, women have been launching new businesses at twice the rate of men for three decades:

The phenomenal growth of women-owned businesses has made headlines for three decades—women consistently have been launching new enterprises at twice the rate of men, and their growth rates of employment and revenue have outpaced the economy.

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