You have to wonder about the effects of bright flashy colors- people like charts and graphs and other things because they seem like factual data, and they feel trustworthy. But they are super easy to fake or edit
How do you know that there is gender bias in academia? Are you biased? Is your university asking you to threat men "better" than women? Therefore: BULLSHIT ;-) Everyone makes decisions, decisions based on one own experience and preferences, maybe even prejudice ... However, even if you end up with 100% men or 100% women, you are not biased, as long gender is not the relevant factor for making the decision. According to feminist this would be "unconscious bias" which in fact is no bias at all! And exactly here is the BULLSHIT! As soon you start consciously considering sex while making a decision, you became biased in EVERY decision by considering how the individual decision would affect the overall number.
Interesting series of lectures. Fixing the audio levels would be a good improvement.
Loving the course so far
You have to wonder about the effects of bright flashy colors- people like charts and graphs and other things because they seem like factual data, and they feel trustworthy. But they are super easy to fake or edit
How does your example explain the "too good to be true" thing?
That's what I thought about Francesca Gino's work...
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So much bull shit in the world
How do you know that there is gender bias in academia?
Are you biased?
Is your university asking you to threat men "better" than women?
Therefore: BULLSHIT ;-)
Everyone makes decisions, decisions based on one own experience and preferences, maybe even prejudice ...
However, even if you end up with 100% men or 100% women, you are not biased, as long gender is not the relevant factor for making the decision.
According to feminist this would be "unconscious bias" which in fact is no bias at all!
And exactly here is the BULLSHIT!
As soon you start consciously considering sex while making a decision, you became biased in EVERY decision by considering how the individual decision would affect the overall number.