

What Does Bias Look Like?  - cwan
http://www.theatlantic.com/national/archive/2011/02/what-does-bias-look-like/71153/

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OasisG
Someone should point back to this article every time there is a discussion
about the lack of women/blacks/latinos in tech. I don't generally go into a
situation thinking people are looking to exclude me, but I've experienced
instances of many of the institutional biases throughout my life.

I've always tried to be open to all sorts of people and situations, but it can
be very hard to be surrounded by people who simply assume their way of being
is the norm. I've been in situations where everyone except me is talking about
the concert they went to. Why? Because no one thought to invite me since it
wasn't a rap/r&b concert.

It makes me nostalgic for my high school years where there were so many kids
of so many different ethnicities, incomes, and interests that we always had to
take special care to understand each other.

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rflrob
> They're all right, of course: you can't simply infer bias from statistical
> underrepresentation

Technically speaking, if something is statistically under- or over-
represented, then there is a source of bias ("an extraneous latent influence
on, unrecognized conflated variable in, or selectivity in a sample which
influences its distribution and so renders it unable to reflect the desired
population parameters"). Whether that bias reflects overt or covert
discrimination on the part of those in academia is another question, of
course.

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glenjamin
_One meta-analysis of studies, for example, found that "discrimination against
blacks was more likely to occur when potential helpers had more opportunities
to rationalize decisions not to help" by invoking "justifiable explanations
having nothing to do with race."_

Isn't this saying that when people had reasons to make a decision not based on
race, they actually did make a decision based on race. How can you actually
produce that conclusion?

~~~
felixc
No, it's suggesting that, for example, when interviewing a black and a white
candidate, each of whom has a reference letter and a set of test scores, the
interviewer would favour test scores if the white candidate had higher test
scores, but would favour reference letters when the black candidate had higher
test scores. If only test scores or only reference letters were available,
they'd hire based on merit.

In other words, people engaged in discriminatory behaviour when there was a
way to rationalize/cover it up, and pretend they weren't doing it -- possibly
telling themselves that, too.

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detokaal
Power.

That is the answer pure and simple. You can cloak it in deep discussions about
statistics and attitudes and backgrounds. But there it is, naked for all to
see. Liberals OWN acadamia and will not give it any of their power over the
curriculum, philosophies, budgets and directions to any group who holds other
ideas, much less ideas the may change the balance of power they hold.

Sadly, the most important part of her article, "We are never the best
interrogators of our ideas. It requires motivated critics to lay bare our
hidden assumptions, our misreading of the data, our factual inaccuracies" will
go unoticed by the people who need to hear this information the most. It is
ironic that the very essence of universities: scholarship and research, are
the things most damaged by conservative discrimination. The ideals that should
be held highest are the ones most damaged, and also the things LEAST cared
about, behind money and power.

People will be people won't they?

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georgecmu
_Those people offered their own alternate theories [snip]_

Another theory not in his list: Reality itself has a well-known liberal bias.

~~~
joh6nn
yeah, i hear that one all the time. based on some arguments i've gotten into
with liberals recently (i'm a centrist), i can state somewhat definitively
that it's not true.

~~~
sorbus
You're using anecdotal evidence to refute anecdotal evidence. A bit surreal,
at least to my mind.

~~~
rflrob
To be fair, he's using anecdotal evidence to refute an overly broad,
unsupported generalization. Some evidence is better than none at all, but only
barely.

