It is often suggested that Australia, and especially higher (i.e. university) education in Australia, is “meritocratic.” Using the statistics, identify a pattern in one demographic that seems to challenge this. Using academic sources, explain some theories and academic research that has sought to explain this pattern.
Use sociological or psychological theory relevant to analysing the phenomenon
Use at least 5 or 6 academic references and use resents please
with size 12 font Times New Roman or Arial, 1.5
1500 words
Gender statistics:
http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4102.0Main+Features20Sep+2012#HIGHER
you must get reference from this article : ( Australian Article please )
Editorial
Complex Questions Rarely Have
Simple Answers
SusanM.Barnett
Wolfson College, Cambridge University, and Cornell University
The subject of this monograph—sex differences in science and
mathematics—is controversial. Although a topic of discussion
for years, this issue was brought to public attention again in
2005 by the much-quoted comments of Lawrence Summers,
then president of Harvard University, suggesting that at least
part of the reason for the dearth of women at the top in math and
science professions is a lack of intrinsic aptitude. Any claim that
genetic differences between the sexes are somewhat responsible
for the underperformance of women in some valued field is going
to provoke debate, and this was no exception. Both academic
and public debate ensued.
This monograph follows on the heels of a report by the blue-
ribbon Committee on Maximizing the Potential of Women in
Academic Science and Engineering (2006), of the National
Academy of Science (NAS), which concluded that ‘‘It is not lack
of talent, but unintentional biases and outmoded institutional
structures that are hindering the access and advancement of
women’’ (p. S1) in these fields. Although intended to resolve
some of the debate, that report generated controversy of its own,
including suggestions of environmentalist bias in the makeup of
the committee. The current monograph was written by a smaller
group of eminent experts in the study of sex differences. The
authors come from different subdisciplines that have histori-
cally not agreed about the causes of sex differences in mathe-
matically intensive STEM fields (science, technology,
engineering, mathematics). When a diverse group such as this
can unite behind at least some conclusions, we are rewarded
with a bedrock of knowledge upon which to build. Some of the
stronger claims that individual contributors might have wished
to include have no doubt been left out—that is the price of
consensus—but what is left should be largely beyond dispute.
Unlike the more policy-oriented report of the NAS task force,
this article focuses on the scientific evidence regarding the
causes of the underrepresentation of women in STEM fields.
The authors conclude that ‘‘early experience, biological fac-
tors, educational policy, and cultural context affect the number
of women and men who pursue advanced study in science and
math and that these effects add and interact in complex ways’’
(p. 1). They note that, if readers were expecting a single
conclusion, they ‘‘are surely disappointed’’ (p. 41). Perhaps so,
but complex questions rarely have simple answers.
The authors point out that one problem in attributing causa-
tion in the area of sex differences is that, although relationships
can often be found between variables, the direction of causality
is often unclear because experimental manipulation is fre-
quently impossible. For example, the monograph reviews con-
siderable evidence showing that men’s and women’s brains
differ, but conclusions are necessarily hard to draw: Is it that
innate brain differences cause males and females to have
differing interests and abilities? Or are the observed brain
differences the consequence of differing experiences? As the
authors mention, the brain ‘‘remains plastic into very old age’’ (p.
3). Similarly, girls’ and boys’ interests also differ, but are males
more interested in STEM fields because they are better at them,
or could they be better because they are more interested or are
socialized to believe they are more competent?
One of the most frequently cited bodies of evidence men-
tioned in the article, suggesting ability differences as a major
cause of the dearth of women in advanced STEM fields, is the
Study of Mathematically Precocious Youth (SMPY) by Benbow
and Stanley. This research program has consistently shown
strong male superiority in math aptitude scores for mathemati-
cally advanced middle schoolers. However, even these results
are open to interpretation. According to the monograph, ‘‘25
years ago there were 13 boys for every girl who scored above 700
on the [mathematics portion of the SAT] at age 13. Now the ratio
is only 2.8:1’’ (p. 13). Such rapid changes suggest strong envi-
ronmental effects, highlighting Halpern et al.’s caution that
ability is an environmentally influenced measure, not a pure
measure of innate talent. The finding that international differ-
ences in math performance swamp intranational sex differences
also suggests that cultural factors play an important role.
The authors sought evidence for sex differences earlier in life,
to reduce the potential for environmental causation, and found a
considerable body of evidence—but again, without clear-cut
conclusions. Young boys are better than girls at many measures
of early visuospatial skill, but it is unclear how important these
various visuospatial skills are for high-level mathematics and
PSYCHOLOGICAL SCIENCE IN THE PUBLIC INTEREST
Volume 8—Number 1
i
Copyright
r
2007 Association for Psychological Science
science performance in adulthood, in comparison with verbal
and other skills at which girls often excel. Similarly, evolu-
tionary psychology has many plausible hypotheses about how
observed differences between men and women may be the ge-
netic result of evolutionary pressures, but whether or not abili-
ties selected due to their utility in spear throwing and animal
tracking are the determinants of modern-day male dominance in
mathematically based fields is a question requiring more re-
search. Both of these examples highlight a more general point:
Efforts to understand why there are more males than females in
mathematically intensive STEM-based careers are unlikely to
be successful until we have a theoretically based understanding
of the cognitive and other requirements that determine success
in these careers. That is currently lacking.
Finally, the ability of women to build successful careers in
STEM and other fields is dependent upon the time and effort
they can devote to their work. As long as women continue to play
a greater role in child rearing than men, they will have fewer
hours to invest in their careers. And in demanding fields like
science and mathematics, this is likely to affect their success.

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