3 thoughts on “Gender Disparities In Science And Tech”
My experience over several university physics departments is that female students were encouraged, helped and made exceptions in their favor far more often than male students. Technical women in aerospace have been given better jobs, faster promotion and larger raises for the last 30 years. Ironically, as more women engineering managers take over, younger women find themselves judged more harshly than their female predecessors and I expect the same to happen in the university environment as more female professors take the places of men.
Which is beside the actual point of the present push for “equality”, which is all about political power blocks using union/minority perk models to energize their constituency.
Rand, All, first I am going to everyone to a Rand posting that is four years old. Rand titled it Worker Abuse. It points to a blog posting by Eric Raymond. I did make a few comments of my own. I also wrote some years ago a policy paper I titled Aerospace Workforce Issues.
More and more people are starting to pay attention to, among other things, sleep deprivation. The lead piece in the February Mensa Bulletin was titled Zombie Nation. It is about how sleep deprivation is causing all sorts of problems in our country. NASA got a mention in the first paragraph because of Challenger.
There is much more, but I am trying to keep this brief.
The lynchpin of the article is the claim that studies of gender bias don’t show enough bias. While other arguments are presented to explain away the bias that the studies show, or rationalize it, those are side arguments to the argument of degree.
If this sounds like a good argument to you, then you must be forgetting that the real world isn’t a petri dish. Becoming an employment statistic isn’t a single shot process. The author rightly recognizes that the data he’s looking at is dependent upon graduation statistics. Those statistics are dependent upon acceptance statistics. Those statistics are dependent upon statistics of prior learning, etc, etc. He also seem to to forget that employment statistics are dependent upon employment statistics – people who are employed in an industry are likely to remain there unless forced out. Those statistics back up the argument of gender bias.
All that said, statistics are a completely unnecessary science when it comes to gender bias in the tech industry. Just go work there! If you can’t see it happening around you ever day, you’re probably blind. If you want a similar experience, try being a libertarian in academia. You don’t need any statistics to see the institutional bias there either.
My experience over several university physics departments is that female students were encouraged, helped and made exceptions in their favor far more often than male students. Technical women in aerospace have been given better jobs, faster promotion and larger raises for the last 30 years. Ironically, as more women engineering managers take over, younger women find themselves judged more harshly than their female predecessors and I expect the same to happen in the university environment as more female professors take the places of men.
Which is beside the actual point of the present push for “equality”, which is all about political power blocks using union/minority perk models to energize their constituency.
Rand, All, first I am going to everyone to a Rand posting that is four years old. Rand titled it Worker Abuse. It points to a blog posting by Eric Raymond. I did make a few comments of my own. I also wrote some years ago a policy paper I titled Aerospace Workforce Issues.
More and more people are starting to pay attention to, among other things, sleep deprivation. The lead piece in the February Mensa Bulletin was titled Zombie Nation. It is about how sleep deprivation is causing all sorts of problems in our country. NASA got a mention in the first paragraph because of Challenger.
There is much more, but I am trying to keep this brief.
The lynchpin of the article is the claim that studies of gender bias don’t show enough bias. While other arguments are presented to explain away the bias that the studies show, or rationalize it, those are side arguments to the argument of degree.
If this sounds like a good argument to you, then you must be forgetting that the real world isn’t a petri dish. Becoming an employment statistic isn’t a single shot process. The author rightly recognizes that the data he’s looking at is dependent upon graduation statistics. Those statistics are dependent upon acceptance statistics. Those statistics are dependent upon statistics of prior learning, etc, etc. He also seem to to forget that employment statistics are dependent upon employment statistics – people who are employed in an industry are likely to remain there unless forced out. Those statistics back up the argument of gender bias.
All that said, statistics are a completely unnecessary science when it comes to gender bias in the tech industry. Just go work there! If you can’t see it happening around you ever day, you’re probably blind. If you want a similar experience, try being a libertarian in academia. You don’t need any statistics to see the institutional bias there either.