Women's Brains Bias

WOMEN'S BRAINS Bias

by Stephen J. Gould in "The Panda's Thumb" 1980 (pp 152-159)

DISCUSSION QUESTIONS

1. What is the general point that Gould is presenting? 

Gould is presenting the point that all of this data is irrelevant, inconclusive, and bias. It doesn’t matter if you are woman or man, big-brained or not, white or black. It doesn’t mean you are smarter than the next person

1. What is the general evidence on which that conclusion is based? 

Gould uses different scientists’ data to show ALL the facts and he exploits the faults in them. He shows both sides of the argument however, he does come back and make the reader believe his points.

1. What is the gender of all the researchers producing those data and conclusions? 

Most of the scientist who think males are smarter than females are males themselves. They are being gender bias.

1. What weaknesses or problems with those data and their interpretation does Gould point out? 

Gould talks about the experiment performed by Broca and finds that the brains of the females that Broca examined were significantly older than those of the male brians he examined. Older brains weigh less than younger ones, so this is a weakness in Broca’s data.

1. a) Name the one woman anthropologist mentioned who studied the subject of this essay. 

Maria Montessori.

1. What did she find after proper correction of Broca's data? 

She found that women had slightly larger brains than men.

c) What were her conclusions from that finding?

She concluded that women were intellectually superior, but men had more hierarchy because of physical force.

1. What conclusion does Gould reach about the central issue?

Gould believes that biological value upon groups is heinous. He says himself “I would apply it (classification of smarts) more widely—not only to those whose dreams are flouted but also to those who never realize that they may dream...” This opens a new door to comparing by disadvantaged groups to advantaged groups and seeing who is more intelligent.

1. Make a general statement about the role of bias and assumptions in the collecting, processing, and interpretation of data in scientific studies.

Everyone has a background which unfortunately sets our brains into thinking some sort of bias towards something. Everyone is bias towards something and everyone interprets things differently. How we share our data is also unfortunate because most scientist shed more light on the data in their favor rather than the data they don’t want.

8. What other kinds of bias can you think of that might influence observations and interpretations in science?

I think if people are bias towards vanity than it could be a HUGE problem. For example, if someone was doing an experiment too see if brunettes were smarter, and they were a brunette themselves, their conclusions could be very biased. The same goes for blonde, blue eyed, big-eared, etc. people.

1. Describe your initial feelings (about the subject, the author, etc.) after reading the first 4 pages.

I thought it was completely false information and I was outraged at the views of the biased scientists.

1. Describe your feeling after finishing the entire article.

I felt content with what Gould’s view was, it was certainly much more fair then the other scientists.