If you’re going to make an argument about anything, making sure the evidence you use to support it is solid and accurate is of the highest importance. Maybe what you’re saying makes sense, and that’s great; unless you support it with evidence collected and organized by a sixth grader for his or her yearly science fair project. This causes everything you say to immediately become suspicious and for readers or listeners to become increasingly dubious about your entire piece.
Lubinski and Benbow’s ‘Sex Differences in Personal Attributes for the Development of Scientific Expertise,’ explores how differences in, “ability or motivational pattern for learning and work,” affects the career paths people take, as well as how willing they are to work long, hard hours (93). They provide many a table and graph to help support their claims and illustrate the studies they cite, using evidence that shows how even when males and females show similar skill in the STEM fields during youth, far more women end up pursuing careers outside of STEM than men. This they attribute to differing interest levels (due to females’ biological interest in people and males’ in objects), motivation levels, and willingness to work long hours.
While reading, I found myself agreeing with what the authors were saying on a certain level. They writing was logical and clear, and I found their points to be reasonable. But as soon as I wrapped my mind around the first figure they presented, my previous contentment was severely diminished. They base one argument (that boys tend to vary on the extremes more than girls) on a study done in Scotland in 1932 comparing IQ scores of 11 year old girls and boys. Almost a century ago this information was collected. Haven’t times changed? Are 11 year old children the same now as they were back then? The kids in this study had no access to technology, and grew up in a very different social atmosphere than the children of this generation. And wouldn’t you think the average IQ levels would have changed by now? Is an IQ test really an effective measure of a person’s capability? Also – these children all live in Scotland. Does this have an influence on how they perform? Would results be different in American children? Too many questions arise when assessing this figure, and the author’s credibility is bumped down a level.
The next blow came when Lubinski and Benbow cited a figure comparing favorite and least favorite high school course at age 18 of males and females, then the degrees these same students earned at age 23. All of this is graphed on a scale of level of SAT-M versus SAT-V scores. This information would be relevant….if it hadn’t already been proven that the SAT-M has a bias against female brain processes. Spelke and Grace report that while all research findings show that men and women perform at the same level considering math, “the SAT- M systematically underpredicts the college mathematics performance of women, in relation to men,” (60).
And so all the logic and clear explanation the authors write instantly transforms into dubious speculation.
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