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#13 | ||||
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Read? I only know how to write.
Join Date: Jan 2001
Posts: 11,933
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Problem with these hypothesis is a serious lack of good experimental evidence. Since social rhetoric (ie cultural training) is not easily separated from what the brain actually prefers. Also completely missing in so many denials is what Summers noted. A statistical trend was completely misunderstood by many who then became emotional and critical. Boys in math and science classes do significantly better. Numbers say so. That remains undisputed. But numbers also say boys do worse. That part gets ignored. IOW a standard deviation (variation) among girls is much smaller. Girls tend to do equally well. Whereras some boys are really good at STEM while others are particuarly the worst. So many only observe the best boys are better than the best girls. They only hear a soundbyte and do not demand details - the reasons why. Therefore they fail to learn a number of simply competant girls in math (for example) is greater than the number of simply competant boys. In short, many make errors by assuming 'binary' logic (a characteristic of extremism). In this case, conclusions are completely different when using ternary categories. Starting at the age of 14 is significant. Since that is when a pre-frontal cortex begins taking over. When 'thinking as an adult' takes over 'from thinking as a child'. Biases (and abilities) may indeed be based in gender differences that become especially distinct when an 'adult' brain forms and takes control. Quote:
This entire subject has no honest answer. Virtually everyone with an answer is using emotion or speculation to justify a conclusion. Because facts and experimental evidence are lacking. We know the results. Statistics identify a sharp decrease in women in the more STEM oriented subjects. But reasons why remain ambiguous or speculative. An example: Does blue and pink packaging reinforce gender preferences? Or does it instead help create the bias? Unfortunately observation (proposed as experimental evidence) is from a closed loop system. Observations of a closed loop system cannot define an "X results in Y" conclusion. Requoted by Quote:
To use color as an example of gender preference or as to how it promotes bias, one must also say why pink, that was manly in 1900, is no longer manly in 2000. And again, no definitive answers exist; only speculation by some and hypothesis by others. Due to lack of good reasons why, appreciate how emotional this becomes. Many proclaim a "give me a fucking break" attitude that implies an emotional (ie primitive) attitude rather than one based in hard facts (ie numbers). Hard facts are missing. Many curioius observations exist - only sufficient to form a hypothesis. Many viciously attacked Larry Summers in 2005 for simply proposing those hypothesis and suggesting strategies based in those hypothesis. Larry Summers was attacked because too many have hardened (radical) beliefs in a subject that has no good answers. Their conclusions and allegations were only based in emotion or other personal biases. Since missing experimental evidence, from controlled environments or from statistacal analysis of an open loop system, is unavailable. A soundbyte conclusion is dishonest or unreasonable. Leading to disagreements only based in primitive emotions. No definitive answers statistically define the relevant gender differences. We only know the best boys in math tend to do the better than the best girls. And that the worst boys do even worse than the worst girls. We know the statisical trends / conclusions. It is not clear why. |
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